Specialist AI agents that just work.
The open-source runtime for community-built experts — any domain, zero setup, no vendor lock-in.
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:golangagent, adoctor:ecgagent, alawyer:gdpragent — 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 |
| 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
- Installation & Setup
- The Tap — Using & Publishing Agents
- Configuration Reference
- Providers & Models
- Sessions & Adaptive Compression
- Layers, Workflows & Sub-agents
- WebSocket & ACP Protocol
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