knot-server-0.5.3 is not a library.

knot-server

knot-server is a distributed REST API and background task scheduler for managing and indexing Git repositories across a cluster. It sits on top of the core knot indexing engine, transforming it from a single-machine CLI tool into a highly available, cluster-aware enterprise service.

See CHANGELOG.md for the full version history.

knot-server and the knot indexing engine are in beta. Expect rough edges, occasional breaking changes, and indexing quirks as we approach a stable 1.0 release.

⚠️ Upgrading to v0.2.9 (knot 1.5.1) — automatic full re-index. knot 1.5.1 bumps the on-disk index-state format (v3 → v4) and switches stored file_path values to repo-relative form. The older state is incompatible, so the first sync of each repository after upgrading is a full re-index (expect it to take as long as the initial index). No manual action is required — knot-server detects the stale state, discards it, and rebuilds the Neo4j/Qdrant entries automatically. See the CHANGELOG for details.

⚠️ Upgrading to v0.2.19 (knot 1.5.6) — re-index Groovy repos. knot 1.5.6 adds Groovy property accessor synthesis, bare property declarations, and parser/Javadoc fixes. Existing Groovy repositories must be re-indexed (POST /api/repos/{id}/sync) for the new entities and OVERRIDES edges to materialize. See the CHANGELOG for details.

With knot-server, you can register Git repositories via a REST API, trigger automatic codebase indexing through webhooks (GitHub, GitLab, Bitbucket), and query the vector (Qdrant) and graph (Neo4j) databases—all while coordinating work safely across multiple server instances via NFS/EFS workspace locks.

🧮 Token Efficiency — Measured, Not Claimed

An LLM agent exploring an unfamiliar codebase pays for every byte it reads. Without an index it greps and then reads whole files; with knot-server's REST APIs, it receives targeted answers, bringing the exact same token-saving performance of the core knot engine to multi-node enterprise environments. The difference was measured on three real indexed repositories across nine realistic exploration tasks:

Repo	Lang	Task	knot-server/knot tokens	Read-the-code tokens	Reduction
spring-ai	Java	discovery — how does the chat client run the advisor chain?	1 092	10 168	89.3%
spring-ai	Java	callers — who uses `ToolCallingManager`?	8 808	15 554	43.4%
spring-ai	Java	explore — structure of `DefaultChatClient.java`	4 865	7 838	37.9%
puppeteer	TypeScript	discovery — how is a CDP session created?	609	4 149	85.3%
puppeteer	TypeScript	callers — who calls `createCDPSession`?	1 004	39 878	97.5%
puppeteer	TypeScript	explore — structure of the `Page` API	7 287	25 300	71.2%
knot	Rust	discovery — how are call intents resolved?	594	14 824	96.0%
knot	Rust	callers — who calls `format_references_result`?	461	10 949	95.8%
knot	Rust	explore — structure of the graph query module	978	12 103	91.9%
TOTAL	—	9 tasks	25 698	140 763	81.7%

≈ 5.5× fewer tokens for the same nine questions — 115 000 tokens saved, enough to keep a long refactoring session inside a single context window.

Both sides are measured on the exact bytes an LLM would receive as tool output, counted with OpenAI's cl100k_base tokenizer (tiktoken):

Task	knot-server/knot side	Read-the-code side
`discovery`	`GET /api/repos/{id}/search?q=<question>`	`rg -l <keyword>` (candidate list) + full read of the files that actually answer the question
`callers`	`GET /api/repos/{id}/callers?entity=<symbol>`	`rg -n "\b<symbol>\b"` + full read of the first 5 distinct files with hits
`explore`	`GET /api/repos/{id}/explore?path=<file>`	full read of the file

The baseline is deliberately generous, so the measured saving is a lower bound:

greps are restricted to the source files of the language (-t java, -t ts, -t rust) — no changelogs, no generated docs, no node_modules;
for discovery the baseline is given oracle file selection: it reads only the files that answer the question, with zero wasted reads;
for callers it reads at most 5 files, while a rigorous impact analysis would need every file with a textual hit.

Honest caveats: knot-server's cost scales with the number of results, not with repo size. The weakest row (spring-ai / ToolCallingManager, 43%) is a symbol with 156 references — knot-server/knot enumerates all of them with exact call sites, while the capped baseline reads only 5 files and still cannot tell a call from a comment. The explore rows for large classes are also the least favourable, because signatures plus docstrings are a large fraction of a well-documented file.

Repositories measured (as indexed): spring-ai 2 406 files / 25 733 entities, puppeteer 1 832 files / 19 310 entities, knot 222 files / 4 000 entities.

✨ Key Features & API Endpoints

knot-server provides a comprehensive REST API to manage the lifecycle of your codebases.

📦 Repository Management

POST /api/repos: Register a new Git repository. Accepts a JSON body with a URL, name, and optional authentication. This endpoint is idempotent: if a repository with the same derived ID already exists, the server treats the call as a re-registration — the existing database entries and local files are cleaned up and the repository is cloned from scratch. The response message indicates whether the call was a fresh registration or a re-registration.

{
  "url": "https://github.com/raultov/knot.git",
  "name": "knot-core",
  "branch": "master",
  "webhook_secret": "your-secret-token",
  "auth": { "type": "none" }
}

Field	Required	Description
`url`	Yes	Git repository URL (HTTPS, SSH, or local path)
`name`	No	Display name (auto-derived from URL if omitted)
`branch`	No	Branch to clone (defaults to `"main"`)
`webhook_secret`	No	Shared secret for validating webhook signatures (HMAC-SHA256 or token). Required to use the `/api/webhook` endpoint.
`auth`	No	Authentication method: `{"type": "ssh"}`, `{"type": "https", "token": "..."}`, or `{"type": "none"}` (default: `{"type": "ssh"}`)

Local filesystem paths in url: When url is an absolute path to a directory on the local filesystem (e.g. /home/raul/workspace/my-app), the server bypasses git clone / git fetch and instead mirrors the source's working tree into the workspace. This means uncommitted working-tree changes in the source are picked up by the next sync — useful when indexing a repository you are actively developing. A regular git fetch only transfers committed objects, so it would miss in-flight edits. See the Indexing local repositories section below for the recommended Docker setup.

Ignored artifact directories: The local sync never copies the following build / dependency / IDE directories (matched by base name anywhere in the tree), and removes any that may have accumulated in the mirror from a previous unfiltered sync:

target/, node_modules/, build/, dist/, out/, .gradle/, .next/, .nuxt/, .svelte-kit/, .cache/, __pycache__/, .pytest_cache/, .mypy_cache/, .ruff_cache/, .tox/, .idea/, .vscode/

This keeps the workspace small and keeps sync time bounded (a Rust project's target/ is routinely 10s of GB and would otherwise be mirrored on every sync). The .knot/ indexer-state directory and .knot.lock are never copied from the source — the mirror's own incremental state is always preserved.

GET /api/repos: List all registered repositories, along with their current status (pending, cloning, pulling, indexing, indexed, error) and last indexed timestamp.
GET /api/repos/:id: Retrieve detailed information about a specific repository.
DELETE /api/repos/:id: Remove a repository from the registry and delete its local workspace. (No request body required).

🔄 Indexing & Webhooks

POST /api/repos/:id/sync: Manually trigger an asynchronous sync and re-indexing job for a repository. (No request body required).
GET /api/repos/:id/progress: Get live indexing progress (percent_complete, stage, parsed files, ingested entities). Note that progress reflects the latest pipeline run and resets when a new sync starts. If the server is restarted during indexing, progress may show as idle until the next scheduled sync auto-heals it.
GET /api/progress: Batch progress for every registered repository in a single call. Each entry resolves via the in-process ProgressTracker first, then falls back to the on-disk snapshot at <workspace>/progress/<id>.json (written by whichever node is currently indexing that repo), so a request served by node B reports the real progress of a job running on node A. Ideal for refreshing a UI dropdown with one HTTP request.
POST /api/webhook/:id: Endpoint for Git provider webhooks (GitHub, GitLab, Bitbucket). Securely validates payload signatures (HMAC-SHA256) or tokens, triggering a fast, incremental background re-index on push events. The request body should be the standard JSON webhook payload sent by the Git provider.

🔍 Code Intelligence Search

GET /api/repos/:id/search?q=...: Semantic + structural search. Find code by meaning, class name, method signature, or docstrings.
GET /api/repos/:id/callers?entity=...: Reverse dependency lookup. Identify callers, dead code, and perform impact analysis. Rows carry repo_name / target_repo_name (knot 1.8.1), so callers are self-labeling.
GET /api/repos/:id/explore?path=...: File anatomy inspection. Quickly see all classes, interfaces, methods, and functions in a specific file.
GET /api/repos/:id/deps: View repository dependencies (transitive and reverse) across the indexed ecosystem.

The per-repo routes above remain single-repo by design. For queries spanning several (or all) registered repositories, use the cross-repo routes below.

Cross-repo search & callers

GET /api/search?q=...&repo=...&max_results=...: Semantic + structural search across one, several, or all registered repositories. Every result entity carries repo_name, so multi-repo results are self-labeling.
GET /api/callers?entity=...&repo=...: Reverse dependency lookup across repositories. Every row identifies the repository of the caller (repo_name) and of the referenced entity (target_repo_name) — a genuine cross-repo reference is the row where the two differ. resolution.targets[] is labeled too.

Both routes share the same repo scope syntax:

`repo` value	Meaning
(omitted)	All registered repositories
`all` or `*` (case-insensitive)	All registered repositories (sentinel)
`repo-a`	Exactly one repository
`repo-a,repo-b`	Union of the listed repositories
(any, empty registry)	Empty result, `200` — the databases are not queried

Caveats:

max_results (search only, default 5, clamped to 1..=100) is a global cap across the whole scope: with repo=all one dominant repository can crowd out the others.
/api/callers has no max_results: the response is bounded by knot's 25-target resolution cap, surfaced as resolution.truncated. Under repo=all a common name resolves against every registered repository, so the cap fills faster — pass a qualified name (Namespace.Type.Member) or narrow the scope to avoid it.
A repository literally named all (or *) is not addressable through these routes (the token is the sentinel); use /api/repos/all/search and /api/repos/all/callers, which build a single-repo scope directly.
Unknown repository ids are rejected with 400 Unknown repository ids: .... A registered but not-yet-indexed repo is a valid scope member that simply contributes no rows.
repo=all — and an omitted repo — are confined to the registry: the sentinel expands to the registered repository ids, so rows from repositories that were deleted from the registry are never returned (previously the query ran unfiltered against the databases). With an empty registry both spellings return an empty result with 200 without querying.

🧬 Graph Visualization (Web UI)

GET /graph: Interactive 3D codebase graph viewer. Open in your browser to visually explore entity relationships.
- Dynamic Filtering: Real-time toggles for relationship types (Calls, Extends, Implements, Overrides, Contains, etc.) and entity kinds (Classes, Interfaces, Functions).
- Node Interaction:
  - Click: Automatically discover and expand neighbors.
  - Focus on Entity: Isolate a specific entity and its deep relationship subgraph.
  - Back to Overview: Return to the global entry-points view.
- High-Contrast Selection: The currently selected node is highlighted in white for maximum visibility.
- Performance Optimized: Default overview mode excludes noisy child relationships (CONTAINS), while focused mode uses physical hierarchy edges to maintain connectivity. Nested declarations (inner classes, C# nested records/enums) are included in the default overview.
- Smart Tooltips: Hover over nodes to see Fully Qualified Names (FQN), kind, file path, and line numbers.
- Contextual Search: Find entities by FQN or name; results include package/module context.
- Cross-Repository Search: An "All repos" checkbox next to the search box switches it from the selected repository to every registered repository at once. Results are grouped and badged by repository, and clicking a result from another repository switches the active repository before focusing the entity. The 3D graph itself remains single-repo.

GET /api/repos/:id/graph?entity=...: Query the entity subgraph for a given repository root entity. Returns nodes and edges in JSON format for programmatic consumption.

Parameter	Type	Default	Description
`entity`	String	optional	Name or FQN of the root entity. If omitted, returns a repository overview (including nested declarations like inner classes, C# nested records/enums).
`depth`	u32	`2`	Traversal depth (1–5)
`relationships`	CSV	`CALLS,EXTENDS,IMPLEMENTS`	Edge types to follow.
`direction`	String	`both`	`outgoing`, `incoming`, or `both`
`kinds`	CSV	`classes,interfaces`	Entity types to include.

GET /api/repos/:id/graph/repos: Query repository-level dependency graph (DEPENDS_ON relations). Returns nodes and edges in JSON format for repository-level cross-dependency tracking.

Parameter	Type	Default	Description
`depth`	u32	`3`	Traversal depth (1–5)
`direction`	String	`both`	`outgoing`, `incoming`, or `both`

Note on Repo-Deps View: Enables 3D codebase visual tracking of dependencies/dependents across the indexed ecosystem in the web UI. Requires repositories with build manifests (such as Cargo.toml or package.json) to be indexed.

Response (200 OK):

{
  "root_id": "app",
  "nodes": [
    { "id": "app", "name": "app", "build_system": "cargo", "group_id": "", "artifact_id": "app", "version": "1.0.0", "is_root": true, "registered": true, "relation": "root" }
  ],
  "edges": [
    { "source": "app", "target": "lib", "type": "DEPENDS_ON" }
  ],
  "total_nodes_found": 2
}

Note on Overview Mode: When no entity is provided, the server identifies "entry points" (entities not contained by others) and traverses from them using the selected relationship types. Disconnected nodes are automatically pruned in focused views.

Response (200 OK):

{
  "root_id": "abc123...",
  "nodes": [
    { "id": "...", "name": "handleRequest", "kind": "rust_function", "language": "rust", "file_path": "src/handler.rs", "start_line": 42, "signature": "fn handleRequest(req: Request) -> Response" }
  ],
  "edges": [
    { "source": "...", "target": "...", "type": "CALLS" }
  ],
  "truncated": false,
  "total_nodes_found": 15
}

GET /api/repos/:id/graph/expand?entity=...&exclude=...: Same as /graph but with depth=1 fixed, plus an exclude parameter (CSV of UUIDs) to skip nodes the frontend already has. Used by the graph viewer when clicking on unexpanded nodes.

📖 Interactive API Documentation (Swagger UI)

GET /docs: Interactive Swagger UI page where you can browse every endpoint, inspect request/response schemas, and execute live "Try it out" requests — no external tools needed. The header shows the knot-server version, the linked knot library version, and the OpenAPI 3.1 stamp side by side, so you always know which versions produced the spec.
GET /api-docs/openapi.json: Raw OpenAPI 3.1 JSON spec for importing into Postman, Insomnia, or generating client SDKs.
Postman Collection: We also include a knot-server.postman_collection.json file in the repository root to help you quickly test the API with Postman.

The spec is auto-generated at compile time via utoipa and embedded directly in the binary — no external CDN or internet access required.

⚙️ Cluster & Health

GET /api/health: Check the health of the server, including connections to Qdrant and Neo4j, and view repository statistics.
Distributed Locking: File-based locking (.knot.lock) allows multiple knot-server instances to share a single NFS/EFS workspace, ensuring only one instance indexes a given repository at a time.
Background Scheduler: Automatically detects and cleans up stale locks, and periodically re-indexes repositories that haven't been synced recently.

🛠️ Development & Quality Gates

make check                                  # Run all local quality gates (fmt, clippy, test, dupes)

# Or run gates individually:
cargo clippy --all-targets -- -D warnings  # Must pass
cargo fmt -- --check                        # Must pass
cargo test --all-targets                    # Run unit tests
cargo dupes check                           # Code duplication check

🛠️ Installation

Option A: Let an LLM do it

Paste this into any LLM agent (Claude Code, OpenCode, Cursor, etc.):

Install knot-server via Docker Compose and then install the agent skills by following: https://raw.githubusercontent.com/raultov/knot-server/master/README.md

Step-by-Step Instructions

Follow these two phases in order. Ask the user for input where indicated.

Phase 1: Docker Compose Installation

Check prerequisites: Verify Docker and Docker Compose are installed:
```
docker --version && docker compose version
```
If either is missing, stop and tell the user to install Docker first.
Choose an install directory: Ask the user where to install the Docker Compose files. Default: ~/knot-server.
```
mkdir -p ~/knot-server && cd ~/knot-server
```

Download the required files:

curl -O https://raw.githubusercontent.com/raultov/knot-server/master/docker-compose.yml
curl -O https://raw.githubusercontent.com/raultov/knot-server/master/.env.example
curl -O https://raw.githubusercontent.com/raultov/knot-server/master/up.sh
curl -O https://raw.githubusercontent.com/raultov/knot-server/master/down.sh
chmod +x up.sh down.sh
cp .env.example .env

Configure .env: Ask the user if they want to index local repositories.
- If yes, ask for the parent directory path (e.g. /home/user/workspace) and set KNOT_LOCAL_REPOS_DIR in .env.
- If no, leave the default.
Create the placeholder directory (required on first run):
```
mkdir -p ~/.knot/empty
```
Start the stack:
```
./up.sh -d
```
Verify the server is healthy (wait up to 30 seconds for services to start):
```
sleep 15 && curl -fsS http://localhost:3000/api/health | jq
```
Expected: "status": "ok". If it fails, retry after another 15 seconds. If it still fails, check docker compose logs for errors.

Phase 2: Agent Skills Installation

Run the skills installer:
```
curl -fsSL https://raw.githubusercontent.com/raultov/knot-server/master/.knot-server-agent-skills.sh | bash
```
This extracts 9 skill documentation files and prompts interactively to register them with your AI agent (OpenCode, Claude Code, Gemini CLI, or universal).

Verification

After both phases, confirm everything works:

# Server health
curl -fsS http://localhost:3000/api/health | jq

# Open the Swagger UI (optional)
# http://localhost:3000/docs

# Open the graph viewer (optional)
# http://localhost:3000/graph

Prerequisites

Component	Version	Notes
Docker	20.10+	For running Qdrant and Neo4j
qdrant	1.x	Vector database (docker)
neo4j	5.x	Graph database (docker)

🐳 Official Docker Image

The official Docker image is available on Docker Hub: raultov/knot-server:latest

This image is lightweight (debian:trixie-slim based) and comes pre-packaged with the knot-server binary, git, and SSH clients — everything needed to clone and index repositories. It is the recommended way to deploy knot-server in containerized environments (Docker, Docker Compose, or Kubernetes).

Option A: Quick Install (curl)

A single command that auto-detects your OS and architecture — no sudo or manual platform selection needed:

curl --proto '=https' --tlsv1.2 -LsSf https://github.com/raultov/knot-server/releases/latest/download/knot-server-installer.sh | sh

For a specific version, replace latest with the version tag:

curl --proto '=https' --tlsv1.2 -LsSf https://github.com/raultov/knot-server/releases/latest/download/knot-server-installer.sh | sh

Option B: Docker Compose (Pre-built Image)

The easiest way to run knot-server with its dependencies. Just download the docker-compose.yml file and run:

curl -O https://raw.githubusercontent.com/raultov/knot-server/master/docker-compose.yml
curl -O https://raw.githubusercontent.com/raultov/knot-server/master/.env.example
curl -O https://raw.githubusercontent.com/raultov/knot-server/master/up.sh
curl -O https://raw.githubusercontent.com/raultov/knot-server/master/down.sh
chmod +x up.sh down.sh
cp .env.example .env          # edit .env to set KNOT_LOCAL_REPOS_DIR etc.
# Create the required empty placeholder directory (only needed once)
mkdir -p ~/.knot/empty
./up.sh -d

This pulls the pre-built raultov/knot-server image from Docker Hub along with Qdrant and Neo4j — no compilation needed.

The up.sh and down.sh scripts are convenience wrappers around docker compose. See the Convenience Scripts section below for usage details.

SSH credentials for private repositories

The container copies your SSH keys at startup and fixes permissions automatically (avoiding the Bad owner or permissions error that occurs with a direct bind-mount into /root/.ssh).

By default it uses ~/.ssh. Override with KNOT_SSH_KEYS_DIR:

# Use a specific key directory (e.g. corporate Bitbucket keys)
KNOT_SSH_KEYS_DIR=/path/to/your/ssh/keys docker compose up

Passphrase-protected keys (corporate / enterprise environments)

Copying SSH key files alone is not enough when keys are protected by a passphrase — the ssh-agent running on the host must be forwarded into the container. The docker-compose.yml does this automatically by mounting the host socket:

environment:
  - SSH_AUTH_SOCK=/ssh-agent
volumes:
  - ${SSH_AUTH_SOCK}:/ssh-agent:ro

Make sure your host ssh-agent is running and the key is loaded before starting the stack (ssh-add ~/.ssh/id_rsa).

Indexing local repositories

To index a repository that lives on your host machine instead of a remote URL, mount the parent directory into the container at the same absolute path so that paths you pass to the API resolve transparently.

The easiest way is to set KNOT_LOCAL_REPOS_DIR in the .env file (copy .env.example as a starting point):

# .env
KNOT_LOCAL_REPOS_DIR=/home/raultov/workspace

Then just run docker compose up. Alternatively, prefix the variable on the command line:

KNOT_LOCAL_REPOS_DIR=/home/raultov/workspace docker compose up

Then register the repo with its local path:

curl -X POST http://localhost:3000/api/repos \
  -H "Content-Type: application/json" \
  -d '{
    "url": "/home/raultov/workspace/github/ui",
    "name": "ui",
    "branch": "master",
    "auth": { "type": "none" }
  }'

Note: KNOT_LOCAL_REPOS_DIR is mounted read-only. The server will read the existing repo from that path — it skips git clone because .git already exists — and index it in place.

If you already have Neo4j and Qdrant running on your host machine (not in containers), use --network host so the container can reach them via localhost:

docker run --network host \
  -v ${HOME}/.ssh:/tmp/ssh_keys:ro \
  raultov/knot-server:latest

Note: The raultov/knot-server image does not include Neo4j or Qdrant. Running docker run without --network host and without pointing to external databases will fail — the container defaults to localhost which refers to itself, not your host.

Option C: Build from Source

Clone the repository and build the binary:

git clone https://github.com/raultov/knot-server
cd knot-server
cargo build --release

Running with Docker Compose from source

The repo includes docker-compose.dev.yml, a development overlay that adds build: . on top of docker-compose.yml. Use it when you want docker compose to build the image locally instead of pulling from DockerHub:

# Build the image from source
docker compose -f docker-compose.yml -f docker-compose.dev.yml build

# Start the full stack using the locally built image
docker compose -f docker-compose.yml -f docker-compose.dev.yml up

# Rebuild and start in one step
docker compose -f docker-compose.yml -f docker-compose.dev.yml up --build

# With local repos exposed (see "Indexing local repositories" above)
KNOT_LOCAL_REPOS_DIR=/home/user/workspace \
  docker compose -f docker-compose.yml -f docker-compose.dev.yml up

Tip: You can add a shell alias to avoid repeating the -f flags:
alias dc-dev='docker compose -f docker-compose.yml -f docker-compose.dev.yml'
dc-dev up --build

Convenience Scripts

The repo includes up.sh and down.sh wrappers around docker compose.

Start the stack:

# Default (port 3000)
./up.sh

# Detached mode
./up.sh -d

# With custom port
KNOT_SERVER_PORT=6060 ./up.sh -d

# Rebuild from source (dev overlay)
KNOT_SERVER_PORT=6060 docker compose -f docker-compose.yml -f docker-compose.dev.yml up --build -d

Stop the stack:

# Stop containers, keep all data
./down.sh

# Stop and delete DB volumes (Qdrant, Neo4j, workspace)
./down.sh --clean

# Stop and delete only repos.json (keep DB volumes)
./down.sh --json

# Stop and delete EVERYTHING (volumes + repos.json)
./down.sh --all

Flag	Effect
(none)	Stop containers, preserve all data
`--clean` / `-c`	Also delete Docker volumes (Qdrant, Neo4j, workspace, fastembed cache)
`--json` / `-j`	Also delete `~/.knot/repos/repos.json` (repository registry)
`--all` / `-a`	Delete volumes AND repos.json

🤖 Using with AI Assistants (Cursor, Copilot, Claude, Gemini)

knot-server transforms any LLM with terminal access (Cursor, GitHub Copilot, Claude Code, Gemini CLI, opencode, Cline, Aider) into a codebase-aware engineer. By teaching the LLM to call the REST API via curl, you give it semantic understanding of your entire codebase — far beyond what grep or file embeddings can provide.

The AI learns five code intelligence skills that replace traditional text search:

#	Skill	Endpoint	Use Case
1	Semantic Search	`/search?q=`	Find code by meaning, not exact text
2	Callers Analysis	`/callers?entity=`	Impact analysis — who uses this function?
3	File Exploration	`/explore?path=`	Get a file's structure without reading it
4	Dependency Graph	`/deps`	Cross-repo dependencies
5	Graph Visualization	`/graph`	Interactive 3D entity relationship explorer
6	Index Repository	`/index`	Register & index the current repo (OpenCode)

These skills teach the LLM to always prefer knot-server curl calls over grep/find/rg for code exploration, dramatically improving accuracy and reducing hallucinations.

Install Agent Skills

Download the pre-built skill instructions to teach your AI agent how to use the knot-server REST API.

Option 1: One-liner (Recommended) Downloads and runs the interactive installer, which extracts the 9 skills and prompts you to register them with your AI agent (OpenCode, Claude Code, Gemini CLI, or universal).

curl -fsSL https://raw.githubusercontent.com/raultov/knot-server/master/.knot-server-agent-skills.sh | bash

Option 2: Local Script (for developers) If you cloned the repo, you can run the installer locally:

./scripts/install-agent-skills.sh

(Note: If you edit the skills/*.md files, run python3 scripts/generate_skills_script.py to regenerate the .knot-server-agent-skills.sh bundle).

Option 3: Per-file Downloader If the tarball is blocked by your firewall, download the .md files individually:

curl -fsSL https://raw.githubusercontent.com/raultov/knot-server/master/scripts/download-agent-skills.sh | bash

Manual Registration

If you skipped auto-registration or use a different AI tool (like Cursor or Copilot), point your tool's system prompt to the downloaded .md files.

For Cursor (.cursorrules):

echo "Read the agent skills in .knot-server-agent-skills/ and use the REST API." >> .cursorrules

For GitHub Copilot (.github/copilot-instructions.md):

mkdir -p .github && echo "Read the agent skills in .knot-server-agent-skills/ and use the REST API." >> .github/copilot-instructions.md

For OpenCode (opencode.json snippet if you skipped auto-registration):

  "skills": {
    "knot-server-preflight": { "description": "MANDATORY STEP 0: Server health and index status check", "location": "file:///path/to/.knot-server-agent-skills/preflight.md" },
    "knot-server-search": { "description": "Use knot-server for semantic code discovery across indexed repositories", "location": "file:///path/to/.knot-server-agent-skills/search.md" },
    "knot-server-callers": { "description": "Use knot-server to find reverse dependencies and perform impact analysis", "location": "file:///path/to/.knot-server-agent-skills/callers.md" },
    "knot-server-explore": { "description": "Use knot-server to get a structural overview of a source file", "location": "file:///path/to/.knot-server-agent-skills/explore.md" },
    "knot-server-deps": { "description": "Use knot-server to traverse the repository dependency graph", "location": "file:///path/to/.knot-server-agent-skills/deps.md" },
    "knot-server-graph": { "description": "Use knot-server to query raw entity relationship subgraphs", "location": "file:///path/to/.knot-server-agent-skills/graph.md" },
    "knot-server-list-repos": { "description": "Use knot-server to list, register, sync, and delete repositories", "location": "file:///path/to/.knot-server-agent-skills/repos.md" },
    "knot-server-workflows": { "description": "Multi-step knot-server workflows: impact analysis, cross-repo exploration, refactoring patterns", "location": "file:///path/to/.knot-server-agent-skills/workflows.md" },
    "knot-server-index": { "description": "Register and index the current repository in knot-server", "location": "file:///path/to/.knot-server-agent-skills/index.md" }
  }

The `/index` Command (OpenCode only)

OpenCode supports a /index command that registers the current repository in knot-server. After installing with option 2 or 3 (OpenCode registration), the command is automatically installed in ~/.config/opencode/commands/index.md. You can then type /index in the OpenCode chat to:

Check if knot-server is running
Register the current repository (if new) or trigger a re-index (if already registered)
Wait for indexing to complete
Verify the repo is queryable with a quick search

Note: The /index command is supported in OpenCode (option 2/3), Claude Code (option 4), and Gemini CLI (option 5). For other tools (Cursor, Copilot, Codex), simply ask the agent: "Index this repository in knot-server" and it will use the [[repos]] skill to do it.

How It Works

Each skill file injects a system prompt into the LLM that defines:

When to use each endpoint (trigger phrases)
How to construct the curl command (parameters, jq filters)
How to interpret the JSON response (field meanings)

The LLM learns to:

Instead of grep "authenticate", call GET /api/repos/{id}/search?q=authentication+logic
Instead of searching for callers manually, call GET /api/repos/{id}/callers?entity=handleRequest
Instead of cat src/file.rs, call GET /api/repos/{id}/explore?path=src/file.rs to get the outline first
Before breaking a shared library, call GET /api/repos/{id}/deps to see the impact

Example: AI-Assisted Code Exploration

User: "Where is the password hashing logic?"
AI (via knot-server):
  curl "/api/repos/myproject/search?q=password+hashing" | jq
  → Found `hash_password` in `src/auth/crypto.rs:142`
  → Reads only lines 142-180 instead of entire file

⚙️ Configuration

knot-server is configured entirely via environment variables or CLI flags.

Environment Variable	Default Value	Description
`KNOT_SERVER_PORT`	`3000`	Port the REST API binds to
`KNOT_SERVER_BIND_ADDR`	`0.0.0.0`	Address the server binds to
`KNOT_WORKSPACE_DIR`	`/var/lib/knot/repos`	Directory where Git repos are cloned & locks are managed. Ensure the user running the server has write access (e.g., `export KNOT_WORKSPACE_DIR=$HOME/.knot/repos`).
`KNOT_SERVER_QDRANT_URL`	`http://localhost:6334`	URL to the Qdrant instance
`KNOT_SERVER_QDRANT_COLLECTION`	`knot_entities`	Qdrant collection name
`KNOT_SERVER_NEO4J_URI`	`bolt://localhost:7687`	URI to the Neo4j instance
`KNOT_SERVER_NEO4J_USER`	`neo4j`	Neo4j username
`KNOT_NEO4J_PASSWORD`	(required)	Neo4j password
`KNOT_SERVER_EMBED_DIM`	`384`	Embedding dimension (must match the model)
`KNOT_SERVER_RAYON_THREADS`	(all cores)	Number of threads for parallel source code parsing. Reduces CPU usage when set to a low value (e.g. `2`).
`KNOT_SERVER_BATCH_SIZE`	`64`	Number of code entities buffered in memory per indexing batch. Lower values reduce RAM usage.
`KNOT_SERVER_INGEST_CONCURRENCY`	`4`	Number of concurrent async tasks for embedding computation and database ingestion. Lower values reduce RAM and CPU usage.
`KNOT_SERVER_POLL_INTERVAL_SECS`	`86400` (24h)	How often the background scheduler runs
`KNOT_SERVER_MAX_INDEX_AGE_SECS`	`86400` (24h)	Age before a repository is automatically re-indexed
`KNOT_SERVER_STALE_LOCK_TIMEOUT_SECS`	`3600` (1h)	Timeout before a `.knot.lock` file is considered orphaned and removed
`KNOT_SERVER_QUEUE_CAPACITY`	`16`	Maximum number of jobs in the background indexing queue. Returns `429 Too Many Requests` when full.
`RUST_LOG`	`info`	Log level (`debug`, `info`, `warn`, `error`)
`KNOT_SERVER_METRICS_ENABLED`	`true`	Enable Prometheus metrics endpoint at `/metrics`

Note: When using Docker Compose, export KNOT_SERVER_PORT before docker compose up so the port mapping in docker-compose.yml also changes (defaults to 3000:3000). Example: KNOT_SERVER_PORT=8080 docker compose up

Docker Compose Host Variables

These variables are consumed by docker compose itself (not by the server binary) to configure volume mounts. Copy .env.example to .env and set the values there so you do not have to prefix them on every docker compose up.

Variable	Default	Description
`KNOT_SSH_KEYS_DIR`	`~/.ssh`	Directory of SSH key files to make available inside the container. Keys are copied to `/root/.ssh` with correct ownership and permissions at startup.
`SSH_AUTH_SOCK`	(host socket)	Path to the host SSH agent socket. Forwarded into the container at `/ssh-agent` so passphrase-protected keys work without re-entering the passphrase. Requires the host `ssh-agent` to be running with the key already loaded (`ssh-add`).
`KNOT_LOCAL_REPOS_DIR`	`~/.knot/empty`	Host directory to mount at the same absolute path inside the container (read-only). Set this to the parent directory of any local repos you want to index by path.

🎛️ Performance Tuning

knot-server is highly parallel by default, which can cause high CPU and memory usage during indexing. Three environment variables control resource consumption:

Variable	Controls	Default	Effect of lowering
`KNOT_SERVER_RAYON_THREADS`	CPU	all cores	Fewer parallel parsers → lower CPU, slightly slower
`KNOT_SERVER_BATCH_SIZE`	RAM	`64`	Fewer entities buffered in memory → lower RAM
`KNOT_SERVER_INGEST_CONCURRENCY`	RAM + CPU	`4`	Fewer concurrent embedding + DB writes → lower RAM and CPU

Preconfigured Profiles

Profile	RAYON_THREADS	BATCH_SIZE	INGEST_CONCURRENCY	Expected RAM	Expected CPU
Kubernetes / Low memory	`2`	`16`	`1`	< 1 GiB	~200%
Balanced	`4`	`32`	`2`	~2 GiB	~400%
Maximum throughput (default)	all cores	`64`	`4`	~5 GiB	all cores

Docker run with tuning

docker run --network host \
  -v ${HOME}/.ssh:/root/.ssh:ro \
  -e KNOT_SERVER_RAYON_THREADS=2 \
  -e KNOT_SERVER_BATCH_SIZE=16 \
  -e KNOT_SERVER_INGEST_CONCURRENCY=1 \
  raultov/knot-server:latest \
  --neo4j-password <your-password> \
  --workspace-dir /var/lib/knot/repos

Docker Compose with tuning

services:
  knot-server:
    image: raultov/knot-server:latest
    ports:
      - "3000:3000"
    environment:
      - KNOT_WORKSPACE_DIR=/var/lib/knot/repos
      - KNOT_SERVER_QDRANT_URL=http://qdrant:6334
      - KNOT_SERVER_NEO4J_URI=bolt://neo4j:7687
      - KNOT_SERVER_NEO4J_USER=neo4j
      - KNOT_NEO4J_PASSWORD=knotsecret
      - KNOT_SERVER_RAYON_THREADS=2
      - KNOT_SERVER_BATCH_SIZE=16
      - KNOT_SERVER_INGEST_CONCURRENCY=1
    volumes:
      - knot_workspace:/var/lib/knot/repos
    depends_on:
      qdrant:
        condition: service_started
      neo4j:
        condition: service_started

📊 Metrics

knot-server exposes Prometheus metrics at GET /metrics on the same port (default 3000). The endpoint requires no authentication and is served outside the OpenAPI spec (not visible in Swagger UI).

Configuration

Variable	Default	Description
`KNOT_SERVER_METRICS_ENABLED`	`true`	Enable/disable the Prometheus metrics endpoint

Prometheus Scrape Config

scrape_configs:
  - job_name: 'knot-server'
    scrape_interval: 15s
    metrics_path: '/metrics'
    static_configs:
      - targets: ['knot-server:3000']

Metric Reference

HTTP

Metric	Type	Labels
`knot_http_requests_total`	counter	`route`, `method`, `status`
`knot_http_request_duration_seconds`	histogram	`route`, `method`
`knot_http_requests_in_flight`	gauge	—

Indexing Pipeline

Metric	Type	Labels
`knot_indexing_jobs_total`	counter	`repo_id`, `kind` (clone\|pull), `result` (ok\|err)
`knot_indexing_duration_seconds`	histogram	`kind`, `result`
`knot_indexing_percent_complete`	gauge	`repo_id`, `stage`
`knot_indexing_parsed_files`	gauge	`repo_id`
`knot_indexing_total_files`	gauge	`repo_id`
`knot_indexing_entities_ingested`	gauge	`repo_id`
`knot_indexing_last_success_timestamp_seconds`	gauge	`repo_id`

Registry & Queue

Metric	Type	Labels
`knot_repositories_total`	gauge	—
`knot_repositories_by_status`	gauge	`status` (pending, queued, indexed, cloning, pulling, indexing, error)
`knot_queue_available_capacity`	gauge	—

Process

Metric	Type	Labels
`knot_process_uptime_seconds`	gauge	—
`knot_build_info`	gauge (=1)	`version`, `knot_version`

Example Grafana Queries

Panel	PromQL
Request rate per route	`sum by (route) (rate(knot_http_requests_total[1m]))`
5xx error rate	`sum(rate(knot_http_requests_total{status=~"5.."}[5m]))`
Latency P95	`histogram_quantile(0.95, sum by (le, route) (rate(knot_http_request_duration_seconds_bucket[5m])))`
Requests in flight	`knot_http_requests_in_flight`
Repos by status	`knot_repositories_by_status`
Queue capacity	`knot_queue_available_capacity`
Indexing duration P95	`histogram_quantile(0.95, sum by (le, kind) (rate(knot_indexing_duration_seconds_bucket[15m])))`
Failed jobs per hour	`sum(increase(knot_indexing_jobs_total{result="err"}[1h]))`
Progress by repo	`knot_indexing_percent_complete`
Age of last index	`time() - knot_indexing_last_success_timestamp_seconds`
Uptime	`knot_process_uptime_seconds`

Security Note

/metrics has no authentication — it assumes deployment on an internal network. If port 3000 is exposed publicly, protect the endpoint via a reverse proxy (nginx, Traefik) rather than modifying the server.

🔭 Tracing (OpenTelemetry)

knot-server supports distributed tracing via OpenTelemetry, exporting spans to any OTLP gRPC compatible collector (Jaeger, Tempo, OpenTelemetry Collector, etc.).

Configuration

Variable	Default	Description
`KNOT_SERVER_TRACING_ENABLED`	`false`	Enable/disable OpenTelemetry tracing
`KNOT_SERVER_OTLP_ENDPOINT`	`http://localhost:4317`	OTLP gRPC endpoint URL
`KNOT_SERVER_TRACE_SAMPLE_RATIO`	`1.0`	Sampling ratio (0.0 to 1.0)

When enabled, knot-server automatically instruments:

All incoming HTTP requests (with http.route and status codes)
Background worker jobs (git clone/pull, index pipeline)
Scheduler poll loops
W3C traceparent context propagation across service boundaries

Here is an end-to-end example of managing a repository with knot-server using curl:

1. Start the server

export KNOT_WORKSPACE_DIR=$HOME/.knot/repos
export KNOT_NEO4J_PASSWORD=mysecret
export KNOT_SERVER_QDRANT_URL=http://localhost:6334
export KNOT_SERVER_NEO4J_URI=bolt://localhost:7687
knot-server

2. Register a repository

curl -X POST http://localhost:3000/api/repos \
  -H "Content-Type: application/json" \
  -d '{
    "url": "https://github.com/raultov/knot.git",
    "name": "knot-core",
    "branch": "master",
    "webhook_secret": "my-webhook-secret"
  }'

The server will instantly clone the repository and queue it for indexing.

3. Check indexing status

curl http://localhost:3000/api/repos/knot-core

Wait until "status": "indexed".

4. Perform a semantic search

curl "http://localhost:3000/api/repos/knot-core/search?q=webhook+validation"

5. Trigger manual re-index (Sync)

curl -X POST http://localhost:3000/api/repos/knot-core/sync

6. Setup Git Webhooks In your GitHub/GitLab repository settings, add a webhook pointing to: http://your-server.com/api/webhook/knot-core

Set the secret/token to the same value as webhook_secret you used when registering the repository. Whenever a push occurs, knot-server will validate the signature and automatically perform a fast incremental update.

7. Browse the interactive API documentation Open http://localhost:3000/docs in your browser to explore all endpoints with Swagger UI. Use "Try it out" to test requests directly, or import http://localhost:3000/api-docs/openapi.json into Postman.

8. Explore the codebase visually Open http://localhost:3000/graph in your browser. Select a repository from the dropdown, search for an entity, and click nodes to expand their call/relationship graph in 3D.

🚀 Cluster & High-Availability Deployment

knot-server is designed to run in horizontal scale-out clusters. Multiple instances share a common workspace directory (NFS, EFS, or Kubernetes RWX PVC) and coordinate via file-based locks — no distributed consensus protocol required.

Docker Compose (Multi-Instance)

services:
  knot-server:
    image: raultov/knot-server:latest
    environment:
      - KNOT_WORKSPACE_DIR=/var/lib/knot/repos
      - KNOT_SERVER_QDRANT_URL=http://qdrant:6334
      - KNOT_SERVER_NEO4J_URI=bolt://neo4j:7687
      - KNOT_SERVER_NEO4J_USER=neo4j
      - KNOT_NEO4J_PASSWORD=your-secure-password
      # Performance tuning (see Performance Tuning section)
      # - KNOT_SERVER_RAYON_THREADS=2
      # - KNOT_SERVER_BATCH_SIZE=16
      # - KNOT_SERVER_INGEST_CONCURRENCY=1
    volumes:
      - knot_shared_workspace:/var/lib/knot/repos
      - ~/.ssh:/root/.ssh:ro
    deploy:
      replicas: 3
    depends_on:
      - qdrant
      - neo4j

  qdrant:
    image: qdrant/qdrant:latest
    volumes:
      - qdrant_data:/qdrant/storage

  neo4j:
    image: neo4j:5
    environment:
      - NEO4J_AUTH=neo4j/your-secure-password
    volumes:
      - neo4j_data:/data

volumes:
  knot_shared_workspace:
    driver: local
  qdrant_data:
  neo4j_data:

Kubernetes

You can deploy the official raultov/knot-server:latest image to Kubernetes with a standard Deployment.

Reference: The included docker-compose.yml file is the canonical reference for configuring knot-server. It documents the exact environment variables, service dependencies (Qdrant + Neo4j), and volume mounts you need to translate into Kubernetes Deployments, Services, and ConfigMaps.

In Kubernetes, the key requirement for horizontal scaling is a PersistentVolumeClaim with accessModes: [ReadWriteMany] (RWX). This allows all knot-server Pods to share the workspace and coordinate safely.

apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  name: knot-shared-workspace
spec:
  accessModes:
    - ReadWriteMany
  resources:
    requests:
      storage: 50Gi
  # storageClassName: nfs-client  # or efs-sc, cephfs, etc.
---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: knot-server
spec:
  replicas: 3
  selector:
    matchLabels:
      app: knot-server
  template:
    metadata:
      labels:
        app: knot-server
    spec:
      containers:
        - name: knot-server
          image: raultov/knot-server:latest
          ports:
            - containerPort: 3000
          env:
            - name: KNOT_WORKSPACE_DIR
              value: /var/lib/knot/repos
            - name: KNOT_SERVER_QDRANT_URL
              value: http://qdrant.default.svc.cluster.local:6334
            - name: KNOT_SERVER_NEO4J_URI
              value: bolt://neo4j.default.svc.cluster.local:7687
            - name: KNOT_SERVER_NEO4J_USER
              value: neo4j
            - name: KNOT_NEO4J_PASSWORD
              valueFrom:
                secretKeyRef:
                  name: knot-secrets
                  key: neo4j-password
            - name: KNOT_SERVER_RAYON_THREADS
              value: "2"
            - name: KNOT_SERVER_BATCH_SIZE
              value: "16"
            - name: KNOT_SERVER_INGEST_CONCURRENCY
              value: "1"
          resources:
            requests:
              memory: "512Mi"
              cpu: "500m"
            limits:
              memory: "1Gi"
              cpu: "2000m"
          volumeMounts:
            - name: shared-workspace
              mountPath: /var/lib/knot/repos
      volumes:
        - name: shared-workspace
          persistentVolumeClaim:
            claimName: knot-shared-workspace

Any Pod can receive webhook events or sync requests; the shared workspace (repos.json, .knot.lock files) ensures exactly-once processing per repository.

🗺️ Roadmap

- Language support in the knot library: Java, Kotlin, JavaScript, TypeScript, Rust, Python, and Varnish have been refined and are polished for production use. Groovy has received significant improvements in v1.5.6 (property accessor synthesis, parser/Javadoc hardening); further refinement is planned to complete verified coverage of the JVM family. C# has been recently added: knot-server categorises every C# declaration kind so C# repositories render correctly in the graph overview. C/C++ follows as the most widely used languages still pending deep verification.

Implement language-based color coding in the /graph view to distinguish nodes by programming language.
Resolve cross-file aliases for JavaScript and TypeScript (require, import): when a local alias shadows an imported entity, graph relationships should resolve to the original definition rather than the alias constant. Python alias resolution to follow. See PR2 plan in the knot repository.
After alias resolution: add a dedicated TypeScriptModule entity kind for synthetic <module> entities generated by re-export-only files, with its own color and filter toggle in /graph.
Add a HELP section in the /graph viewer to assist users in understanding the graph visualization.

📜 License

This project is licensed under the MIT License. See LICENSE for details.

knot-server 0.5.3

knot-server

🧮 Token Efficiency — Measured, Not Claimed

✨ Key Features & API Endpoints

📦 Repository Management

🔄 Indexing & Webhooks

🔍 Code Intelligence Search

Cross-repo search & callers

🧬 Graph Visualization (Web UI)

📖 Interactive API Documentation (Swagger UI)

⚙️ Cluster & Health

🛠️ Development & Quality Gates

🛠️ Installation

Step-by-Step Instructions

Phase 1: Docker Compose Installation

Phase 2: Agent Skills Installation

Verification

Prerequisites

🐳 Official Docker Image

Option A: Quick Install (curl)

Option B: Docker Compose (Pre-built Image)

SSH credentials for private repositories

Passphrase-protected keys (corporate / enterprise environments)

Indexing local repositories

Option C: Build from Source

Running with Docker Compose from source

Convenience Scripts

🤖 Using with AI Assistants (Cursor, Copilot, Claude, Gemini)

Install Agent Skills

Manual Registration

The /index Command (OpenCode only)

How It Works

Example: AI-Assisted Code Exploration

⚙️ Configuration

Docker Compose Host Variables

🎛️ Performance Tuning

Preconfigured Profiles

Docker run with tuning

Docker Compose with tuning

📊 Metrics

Configuration

Prometheus Scrape Config

Metric Reference

HTTP

Indexing Pipeline

Registry & Queue

Process

Example Grafana Queries

Security Note

🔭 Tracing (OpenTelemetry)

Configuration

🚀 Cluster & High-Availability Deployment

Docker Compose (Multi-Instance)

Kubernetes

🗺️ Roadmap

📜 License

The `/index` Command (OpenCode only)