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Octomind — AI Agent Runtime

Specialist AI agents that just work.
The open-source runtime for community-built experts — any domain, zero setup, no vendor lock-in.

License GitHub stars Website

Documentation · Community Tap · Website


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.

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.


This Is What "Just Works" Looks Like

# Install once
curl -fsSL https://raw.githubusercontent.com/muvon/octomind/master/install.sh | bash
export OPENROUTER_API_KEY="your_key"

# Run any community-built specialist — zero setup
octomind run developer:rust       # Senior Rust dev, full toolchain pre-wired
octomind run doctor:blood         # Medical lab analyst, reads your actual results
octomind run devops:kubernetes    # K8s operator with kubectl + helm ready
octomind run security:pentest     # Security specialist, offensive tooling attached
octomind run legal:contracts      # Contract reviewer, jurisdiction-aware
octomind run finance:analyst      # Financial analyst, wired to your data sources

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.


Quick Start

# Install (macOS & Linux)
curl -fsSL https://raw.githubusercontent.com/muvon/octomind/master/install.sh | bash

# One API key gets you all providers (or use any directly)
export OPENROUTER_API_KEY="your_key"

# Start with a specialist agent — no setup required
octomind run developer:rust

The Tap: Community-Packaged Expertise

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
octomind run developer:rust
octomind run doctor:blood
octomind run doctor:nutrition

# Add any community or team tap
octomind tap yourteam/tap              # clones github.com/yourteam/octomind-tap
octomind tap yourteam/internal ~/path  # local tap for private agents

# Agents from your new tap are immediately available
octomind run finance:analyst
octomind run legal:contracts

Each tap is a Git repo. Each agent is one TOML file. Pull requests are contributions.

Want to add your expertise? A developer:golang agent, a doctor:ecg agent, a lawyer:gdpr agent — one file, and everyone benefits. How to write a tap agent →


Agents That Grow Beyond Their Configuration

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.


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 — and it's all TOML, no code required.

# Per-role: independent model, temperature, MCP servers, tools, system prompt
[[roles]]
name = "senior-reviewer"
model = "anthropic:claude-opus-4"
temperature = 0.2
[roles.mcp]
server_refs = ["filesystem", "github"]
allowed_tools = ["view", "ast_grep", "create_pr"]

# Multi-step workflows: each step its own model + toolset
[[workflows]]
name = "deep_review"
[[workflows.steps]]
name = "analyze"   # gemini-2.5-flash for broad context gathering
layer = "context_researcher"
[[workflows.steps]]
name = "critique"  # claude-opus for precision judgment
layer = "senior_reviewer"

# Spending limits — never get surprised
max_request_spending_threshold = 0.50
max_session_spending_threshold = 5.00

# Sandbox: lock all writes to current directory
sandbox = true

Every role, every layer, every workflow gets its own model, tools, and temperature. Mix providers freely. Build multi-model pipelines. Customize everything — with just a config file, no code.


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
/model deepseek:v3

# Override for one session
octomind run --model openai:gpt-4o

# 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
Google 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
octomind run developer:rust

# Non-interactive — pipe tasks directly from scripts or CI/CD
echo "review this PR for security issues" | octomind run --format jsonl

# Daemon mode — long-running background agent
octomind run --name myagent --daemon --format plain

# Send messages to running daemon from anywhere
echo "check the build status" | octomind send --name myagent

# WebSocket server — connect IDE plugins, dashboards, automation
octomind server --port 8080

# ACP protocol — drop into any multi-agent system as a sub-agent
octomind acp developer:rust
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.


Built-in Tools

Category Tools
Search ast_grep — structural code search (not regex), view — smart file/dir reader
Editing text_editor, batch_edit — atomic multi-file edits with rollback
Execution shell — full command execution with output capture
Planning plan — structured multi-step task tracking
Self-extension mcp — enable/disable MCP servers at runtime, agent — spawn sub-agents on demand

Installation

# One-line install
curl -fsSL https://raw.githubusercontent.com/muvon/octomind/master/install.sh | bash

# Build from source
git clone https://github.com/muvon/octomind.git
cd octomind && cargo build --release

macOS and Linux. Single Rust binary. Fast startup. No runtime dependencies.


Documentation


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.

How to write a tap agent → | Open issues →


Octomind by Muvon | Website | Issues

License: Apache 2.0 — © 2025–2026 Muvon Un Limited