axocoatl
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Agentic runtime in Rust — persistent, supervised agents. Self-hosted, local-first, zero telemetry. Apache 2.0.
Axocoatl
The Rust runtime for self-coordinating multi-agent systems.
Kill the server mid-task — the agent restarts from its last checkpoint, not from zero. 100% local.
Axocoatl runs persistent AI agents that coordinate through a stigmergic event
lattice — agents activate when their dependencies complete, driven by
pheromone-style signals with no central orchestrator. Built in Rust on theractor actor model: low memory, fast cold start, provider-agnostic.
60-second quickstart
# 1. Install (no Rust toolchain required)
curl -fsSL https://raw.githubusercontent.com/axocoatl/axocoatl/main/scripts/install.sh | sh
# 2. Interactive setup wizard — picks a provider, scaffolds a project
axocoatl onboard
# 3. Check your environment
axocoatl doctor
# 4. Start the daemon + API, then chat
axocoatl dev
axocoatl chat -a assistant
Prefer Cargo? cargo install axocoatl-cli (requires Rust 1.82+).
Skipping
onboard? Copyaxocoatl.example.yaml
toaxocoatl.yaml— two agents and one workflow, fits on one screen.
The fullaxocoatl.yamlshipped in the repo is the larger demo (12 agents,
scheduled runs, MCP servers).
Why Axocoatl
| Capability | Axocoatl | AutoAgents | CrewAI |
|---|---|---|---|
| Language / runtime | Rust / actors | Rust / actors | Python |
| Stigmergic coordination (no orchestrator) | ✅ | ❌ | ❌ |
| HTN symbolic planning | roadmap | ❌ | ❌ |
| Auction-based agent selection | roadmap | ❌ | ❌ |
| Per-agent token budgets | ✅ | ❌ | partial |
| 4-tier persistent memory + checkpointing | ✅ | partial | partial |
| MCP client + server | ✅ | partial | ✅ |
| A2A protocol | ✅ | ❌ | ❌ |
| Provider-agnostic (Ollama/OpenAI/Anthropic/…) | ✅ | ✅ | ✅ |
Interactive onboarding + doctor |
✅ | ❌ | ❌ |
The differentiator is the coordination layer: define agents withdepends_on, and the event lattice cascades work through them automatically.
agents:
- id: researcher
provider: ollama
model: llama3.2
depends_on: []
- id: summarizer
provider: ollama
model: llama3.2
depends_on: [researcher] # activates when researcher completes
workflows:
- id: research-and-summarize
agents: [researcher, summarizer]
entry_point: researcher
axocoatl workflow run research-and-summarize -i "What is photosynthesis?"
Core concepts
- Agents — persistent
ractoractors with a provider, tools, 4-tier
memory, and a token budget. Survive restarts via checkpointing. - Stigmergic coordination — agents publish
TaskCompletedevents; anEventLatticeaccumulates pheromone signals and activates downstream agents
when thresholds are crossed. No scheduler, no glue code. - Workflows — declarative multi-agent DAGs via
depends_on/entry_point. - Providers — Ollama, OpenAI, Anthropic, Mistral, Gemini, OpenRouter. No lock-in.
- Protocols — MCP (consume & expose tools) and A2A (agent interop).
See the docs site for the full picture, the
marketing site for the positioning, ordocs/ARCHITECTURE.md anddocs/TROUBLESHOOTING.md for the in-repo
quick reference.
Roadmap
Built and tested in the axocoatl-coordination crate, but not yet wired into
the shipped runtime:
- HTN symbolic planning — task decomposition without LLM calls.
- Auction-based agent selection — pick agents by tool capability, load, and
remaining token budget. - Stronger sandbox isolation tiers — the shipped sandbox is a hardened
rootless Podman container (capabilities dropped, no-new-privileges,
network-isolatable); microVM-class isolation (Firecracker) is planned.
CLI
axocoatl onboard Interactive setup wizard
axocoatl doctor Environment / dependency health check
axocoatl init <name> Scaffold a project non-interactively
axocoatl validate <config> Validate a config file
axocoatl dev | serve Run daemon (+ IPC) / production server
axocoatl chat -a <agent> Interactive chat
axocoatl workflow list | run Inspect / execute multi-agent workflows
axocoatl agents list|status|restart
axocoatl tokens report Per-agent token usage
axocoatl mcp servers|tools Inspect connected MCP servers/tools
HTTP API
GET /health POST /api/agents/{id}/execute
GET /api/agents GET /api/agents/{id}/status
POST /api/agents/{id}/restart GET /api/tokens/report
GET /api/workflows POST /api/workflows/{id}/execute
GET /api/mcp/servers GET /api/mcp/tools
GET /ws (WebSocket streaming)
Examples
Runnable, mock-LLM (no keys needed) — see examples/:research-assistant, code-reviewer, customer-support.
Build from source
git clone https://github.com/axocoatl/axocoatl
cd axocoatl
cargo build --release # binary: target/release/axocoatl
cargo test --workspace # 340+ tests
License
Apache-2.0 — see LICENSE. Changes: CHANGELOG.md.
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