What is Quelch?
Quelch v2 is a knowledge-platform operator tool for teams using Jira and Confluence. It ingests data into Cosmos DB as the system of record, uses Azure AI Search (via the embedded rigg library) for hybrid semantic retrieval, and exposes a five-tool MCP API that agents (Copilot Studio, VS Code Copilot, Claude, Codex) can call directly.
One Rust binary, one YAML config file, three runtime roles: quelch ingest, quelch mcp, and the operator CLI.
Architecture overview
Sources → quelch ingest → Cosmos DB → AI Search Indexer → AI Search Index
↑ ↑
└─ quelch-meta (cursors) │
│
quelch mcp ────────────────────────────┘
↑
Agent (Copilot Studio / VS Code / Claude / etc.)
See docs/architecture.md for details.
Features
- Cosmos DB as system of record — exact queries, counts, exhaustive listings, and cursor-based pagination without hitting search
- Azure AI Search via rigg — indexes, skillsets, indexers, knowledge sources, and knowledge bases all managed from
quelch.yaml - Five-tool MCP API —
search(Knowledge Base agentic retrieval),query(Cosmos SQL),get(point-read),list_sources,aggregate - Incremental sync — minute-resolution windows with safety lag, backfill resume, soft-delete reconciliation
- Agent bundle generator —
quelch agent generateproduces grounded bundles for Copilot Studio, Claude Code, VS Code Copilot, Copilot CLI, Codex, and Markdown - On-prem artefacts —
quelch generate-deploymentwrites docker-compose, systemd, or Kubernetes manifests; Quelch never SSHes anywhere - Operator CLI —
azure plan,azure deploy,azure indexer,azure logswith Bicep +azshell-outs - Rich TUI — fleet dashboard showing live ingest state per worker, polling
quelch-meta
Installation
Homebrew (macOS/Linux)
Cargo
Binary download
Download pre-built binaries from the latest release.
Quick start
# Generate a starter config interactively
# Validate the generated config
# Plan Azure resources (Bicep + rigg files) — no Azure calls yet
# Deploy to Azure (calls az + rigg-client)
# Run the ingest worker
# Start the MCP server
CLI surface
quelch — Cosmos + AI Search knowledge platform operator
COMMANDS:
validate Validate config without running
effective-config Print the resolved config for a deployment
status Show live ingest state from quelch-meta
ingest Run the ingest worker
mcp Start the MCP HTTP server
dev Run sim + ingest + MCP in one process (no Azure needed)
azure plan Show Bicep + rigg diff against live Azure
azure deploy Apply Bicep + rigg to Azure
azure pull Pull live rigg state to disk
azure indexer Run / reset / status the AI Search Indexer
azure logs Tail Container Apps log stream
azure destroy Tear down all Azure resources for a deployment
query Run a Cosmos SQL query from the CLI
search Run a Knowledge Base search from the CLI
get Fetch a single document from Cosmos
reset Reset ingest cursors
generate-deployment Generate docker-compose / systemd / k8s artefacts
agent generate Generate agent or skill bundles for agent platforms
init Interactive config wizard
ai Configure AI (ailloy) embedding model
OPTIONS:
-c, --config <PATH> Config file (default: quelch.yaml)
--help Print help
--version Print version
See docs/cli.md for every command and flag with examples.
Documentation
| Doc | Purpose |
|---|---|
| docs/README.md | Vision and 5-minute overview |
| docs/architecture.md | Components, data flow, topology |
| docs/configuration.md | quelch.yaml reference |
| docs/cli.md | Every command + flag |
| docs/sync.md | Sync correctness algorithm |
| docs/mcp-api.md | Five MCP tools, schemas, pagination |
| docs/deployment.md | Azure plan/deploy + on-prem artefacts |
| docs/agent-generation.md | quelch agent generate targets |
| docs/examples.md | End-to-end agent usage walkthroughs |
License
MIT