Documentation · Community Tap · Website
Table of Contents
- The Problem
- The Solution: Tap Agents
- Quick Start
- How It Works
- Runtime Self-Extension
- Key Features
- Installation
- Usage
- Configuration
- Architecture
- Contributing
- License
The Problem
You want an AI that actually knows your domain. Instead you get:
- 45 minutes of setup — MCP servers, system prompts, tool configs, wiring everything together
- Rate limit walls mid-task — Claude Code throttles you, Cursor burns your budget, you lose the thread
- Context rot — session fills up, agent forgets decisions from an hour ago, you restart from zero
- One-size-fits-all — the same generic assistant whether you're debugging Rust, interpreting a blood test, or reviewing a contract
Every AI tool in 2026 is a coding assistant that lets you swap models. That's it.
The Solution: Tap Agents
Octomind is different. It's not a framework you configure. It's a runtime for specialist agents — any domain — where the community has already done the hard work.
You just run it.
# Install once
|
# Run any community-built specialist — zero setup
What Happens When You Run octomind run doctor:blood
→ Fetches the agent manifest from the tap registry
→ Installs required binaries automatically (skips if already present)
→ Prompts once for any credentials → saves permanently, never asks again
→ Spins up the right MCP servers for this domain
→ Loads specialist model config, system prompt, tool permissions
→ Ready in ~5 seconds. Not 45 minutes.
This isn't a prompt or a skill. It's packaged expertise — ready to run.
The Tap Registry
The tap is a community-driven Git registry. Each agent is a complete, battle-tested configuration built by a domain expert:
- ✅ The optimal model for that field
- ✅ The right MCP servers pre-wired (databases, APIs, domain tools)
- ✅ A specialist system prompt written by someone who knows the domain
- ✅ Tool permissions scoped correctly
- ✅ Dependencies that auto-install on first run
- ✅ Credential management — asks once, stores permanently
Not a prompt file. Not a skill injection. The full stack, configured by the community, ready to run.
# Official tap included by default — just run
# Add any community or team tap
# Agents from your new tap are immediately available
Each tap is a Git repo. Each agent is one TOML file. Pull requests are contributions.
Want to add your expertise? A
developer:golangagent, adoctor:ecgagent, alawyer:gdpragent — one file, and everyone benefits. How to write a tap agent →
Quick Start
# Install (macOS & Linux)
|
# One API key gets you all providers (or use any directly)
# Start with a specialist agent — no setup required
That's it. You're in an interactive session with a Rust specialist that can read your code, run commands, and edit files.
How It Works
Core MCP Tools
Octomind has 5 built-in MCP tools that every agent has access to:
| Tool | Purpose |
|---|---|
plan |
Structured multi-step task tracking for complex work |
mcp |
Enable/disable MCP servers at runtime — agents can acquire new capabilities on demand |
agent |
Spawn specialist sub-agents mid-session — delegate to the right expert |
schedule |
Schedule messages to be injected at future times |
skill |
Inject reusable instruction packs from taps |
Filesystem Tools (via octofs)
File operations come from octofs — a companion MCP server for file read/write/edit:
| Tool | Purpose |
|---|---|
view |
Read files, directories, search content |
text_editor |
Create files, replace text, undo edits |
batch_edit |
Atomic multi-file edits with rollback |
shell |
Execute commands with output capture |
semantic_search |
Search codebase by meaning |
structural_search |
Search code by AST patterns |
workdir |
Get/set working directory |
octofs is external but recommended. Tap formulas include it by default — plug and play.
Memory & Knowledge Tools (via octomem)
Long-term memory and knowledge indexing:
| Tool | Purpose |
|---|---|
remember |
Semantic search over stored memories |
memorize |
Store information for future sessions |
knowledge |
Index and search documents, URLs, files |
graphrag |
Knowledge graph queries over codebase |
octomem is external but recommended. Included in tap formulas that need persistent context.
Runtime Self-Extension
This is the capability nobody else has.
Octomind agents have two built-in power tools — mcp and agent — that let them acquire new capabilities and spawn specialist sub-agents mid-session, without any restart or config change.
User: "Cross-reference our Postgres metrics with the deployment log and find the anomaly"
Agent:
→ Uses `mcp` tool: registers + enables a Postgres MCP server on the fly
→ Uses `agent` tool: spawns a log_reader sub-agent for the deployment log
→ Both run in parallel, results merged
→ Agent disables the Postgres MCP when done
→ Presents the analysis
The tap gives the agent its starting configuration. The mcp and agent tools give it room to go beyond — acquiring exactly what it needs, when it needs it, and nothing more.
No other tool lets the AI extend its own capabilities at runtime. This is the octopus advantage: eight arms, infinite domains, one coordinated mind.
Key Features
🎯 Zero Config. Infinitely Configurable.
For most people: install, run, done. No config file needed.
For power users and teams: Octomind has the deepest configuration system in the space — all TOML, no code required.
# Per-role: independent model, temperature, MCP servers, tools, system prompt
[[]]
= "senior-reviewer"
= "anthropic:claude-opus-4"
= 0.2
[]
= ["filesystem", "github"]
= ["view", "ast_grep", "create_pr"]
# Multi-step workflows: each step its own model + toolset
[[]]
= "deep_review"
[[]]
= "analyze" # gemini-2.5-flash for broad context gathering
= "context_researcher"
[[]]
= "critique" # claude-opus for precision judgment
= "senior_reviewer"
# Spending limits — never get surprised
= 0.50
= 5.00
# Sandbox: lock all writes to current directory
= true
🧠 Infinite Sessions With Adaptive Compression
Context rot is the silent productivity killer. Session fills up → quality drops → agent forgets what it decided an hour ago → you restart and lose everything.
Octomind's adaptive compression engine runs automatically in the background:
- Cache-aware — calculates if compression is worth it before paying for it
- Pressure-level system — compresses more aggressively as context grows
- Structured preservation — keeps decisions, file references, architectural choices; discards noise
- Fully automatic — you never think about it
Work on a hard problem for 4 hours. The agent still knows what it decided in hour one.
🔄 13+ Providers. Switch Instantly. Zero Lock-in.
# Hit a rate limit? Switch mid-session — no restart, no lost context
# Override for one session
# Mix providers across workflow layers
# cheap model for research → best model for execution
| Provider | Notes |
|---|---|
| OpenRouter | Every frontier model, one API key |
| OpenAI | GPT-4o, o3, Codex |
| Anthropic | Claude Opus, Sonnet, Haiku |
| Gemini 2.5 Pro/Flash | |
| Amazon Bedrock | Claude + Titan on AWS |
| Cloudflare | Workers AI |
| DeepSeek | V3, R1 — best cost/performance ratio |
Real-time cost tracking per session and per request. Know exactly what you're spending.
🌐 Works Everywhere — Plug Into Anything
Octomind isn't just an interactive terminal tool. It runs in every context you need:
# Interactive — daily driver
# Non-interactive — pipe tasks directly from scripts or CI/CD
|
# Daemon mode — long-running background agent
# Send messages to running daemon from anywhere
|
# WebSocket server — connect IDE plugins, dashboards, automation
# ACP protocol — drop into any multi-agent system as a sub-agent
| Mode | Use For |
|---|---|
| Interactive CLI | Daily work, any domain |
--format jsonl pipe |
CI/CD pipelines, shell scripts, automation |
--daemon + send |
Background agents, continuous monitoring, long-running tasks |
| WebSocket server | IDE plugins, web dashboards, external integrations |
| ACP protocol | Multi-agent orchestration, being called by other agents |
One binary. Every workflow. Eight arms, infinite domains.
Installation
One-Line Install
|
Detects your OS and architecture, downloads the latest release, installs to ~/.local/bin/.
Package Managers
# Cargo (Rust)
Requires Rust 1.82+. See Building from Source for development setup.
Build from Source
API Key Setup
Set at least one provider API key:
# OpenRouter (recommended — access to many providers)
# Or use a specific provider
Add to your shell profile (~/.bashrc, ~/.zshrc) for persistence.
Verification
macOS and Linux supported. Single Rust binary. Fast startup. No runtime dependencies.
Usage
Interactive Session
# Default: interactive with tools
# Named session (resume later)
# Resume a session
# Tap agent (fetches specialized config)
Non-Interactive Mode
# Single message, plain output
# Structured JSON output for pipelines
Session Commands
| Command | Description |
|---|---|
/help |
Show all commands |
/info |
Token usage and costs |
/model <provider:model> |
Switch AI model mid-session |
/role <name> |
Switch role mid-session |
/save |
Save current session |
/exit |
Exit session |
See Session Commands for the full list.
Configuration
Configuration lives at ~/.local/share/octomind/config/config.toml.
# View current config
# Validate config
Key configuration areas:
- Roles — model, temperature, system prompt, MCP servers, tool permissions
- Workflows — multi-step AI processing with validation loops
- Pipelines — deterministic script-driven pre-processing
- MCP Servers — external tools and capabilities
- Spending Limits — per-request and per-session thresholds
See Configuration Reference for all options.
Architecture
CLI / WebSocket
|
v
ChatSession <- src/session/chat/session/ (core.rs, main_loop.rs)
|
+-- Roles <- src/config/roles.rs (model, system prompt, MCP servers per role)
+-- Layers <- src/session/layers/ (chained AI sub-agents, run after each response)
+-- Pipelines <- src/session/pipelines/ (deterministic script steps, run before workflows)
+-- Workflows <- src/session/workflows/ (multi-step orchestrated task runners)
+-- Learning <- src/learning/ (cross-session lesson extraction and injection)
|
+-- MCP servers <- src/mcp/
+-- core/ plan, mcp, agent, schedule, skill (built-in)
+-- (filesystem tools provided by external octofs MCP server)
+-- (memory tools provided by external octomem MCP server)
+-- agent/ agent_* tools -> route tasks to configured layers
Config is the single source of truth. All defaults live in config-templates/default.toml. The resolved config drives everything: which model, which MCP servers, which layers, which role. No hardcoded values anywhere in code.
See Architecture for detailed internals.
Contributing
The most impactful contribution isn't code — it's agents.
Every domain expert who publishes a specialist makes Octomind useful for an entirely new audience. A cardiologist publishing doctor:ecg. A tax attorney publishing lawyer:tax. A genomics researcher publishing scientist:genomics. One TOML file — and everyone with that problem gets a specialist-grade AI instantly.
accountant:tax, devops:terraform, designer:ux-review, scientist:genomics — the registry grows one file at a time.
Documentation
- Installation & Setup
- Quickstart
- Configuration
- Providers & Models
- Sessions & Compression
- Roles
- MCP Tools
- Workflows
- Pipelines
- Learning
- WebSocket & ACP
- CLI Reference
- Config Reference
Full documentation index: doc/README.md
License
Apache License 2.0 — see LICENSE.
Octomind by Muvon | Website | Documentation