docs
Introduction
Ninetrix is an open-source platform for building, shipping, and observing AI agents as Docker containers. agentfile.yaml is to AI agents what Dockerfile is to containers — a portable, version-controlled definition that works anywhere.
Open source, Apache 2.0
Ninetrix is fully open source. Self-host the entire stack on your own infrastructure, or use Ninetrix Cloud for a managed experience.
The problem it solves
Building AI agents today means gluing together frameworks, writing boilerplate, reinventing observability, and figuring out deployment on your own. Ninetrix gives you a standard:
- One YAML file defines your agent — provider, model, tools, memory, triggers, governance
ninetrix buildcompiles it into a Docker image with a full generated runtimeninetrix runexecutes it with traces, checkpoints, and approvals built inninetrix upstarts a multi-agent network on a shared Docker bridge- Self-host the entire stack — dashboard, API, MCP gateway — with one
docker compose up
Key features
| Feature | Description |
|---|---|
| Multi-provider | Anthropic, OpenAI, Google, DeepSeek, Mistral, Groq, Together AI, OpenRouter, Cerebras, Fireworks, AWS Bedrock, Azure OpenAI, MiniMax — switch without code changes |
| MCP-native tools | Connect any MCP server: GitHub, Slack, filesystem, browser, and more |
| Persistent memory | API-based checkpoints — resume any session with --thread-id, no database config required |
| Durable Runs | Automatic crash recovery — Docker restarts the container, agent resumes from last checkpoint |
| Multi-agent | Agents hand off to each other via collaborators on a Docker bridge |
| Human-in-the-loop | Gate specific tool calls on human approval before executing |
| Planned execution | Agent generates a plan first, executes step-by-step with verification |
| Triggers | Webhook and cron schedule triggers built into the container |
| Governance | Per-run budget limits, approval gates, rate limits |
| Observability | Full trace view in the dashboard — every tool call, every step |
| Self-hostable | One docker compose up — air-gap ready, no vendor calls |
How it works
ninetrix build reads your agentfile.yaml, renders Jinja2 templates into a Python runtime and Dockerfile, then runs docker build. The resulting image contains everything your agent needs — the LLM client, tool connectors, checkpoint logic, trigger servers, and approval handlers.
Bash
# Install (auto-detects pipx, uv, or pip3)
curl -fsSL https://install.ninetrix.io | sh
# Or manually:
# pip install ninetrix
# uv tool install ninetrix
# Start local stack (Postgres, API, MCP gateway, dashboard)
ninetrix dev
# Build and run your first agent
ninetrix build
ninetrix run
Next steps
- Quick Start — build your first agent in 5 minutes
- Installation — full install guide with prerequisites
- agentfile.yaml — the full YAML reference
- MCP Tools — connect GitHub, Slack, and any MCP server