# AGENT33 PUBLIC

> Local-first multi-agent orchestration platform with built-in governance, evidence capture, multi-tenant isolation, workflows, skills, packs, tools, and observability. FastAPI engine, React frontend, Docker Compose / Kubernetes deploy.

- **Type:** MCP server
- **Install:** `agentstack add mcp-mattmre-agent33-public`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [mattmre](https://agentstack.voostack.com/s/mattmre)
- **Installs:** 0
- **Category:** [Cloud & Infrastructure](https://agentstack.voostack.com/c/cloud-infrastructure)
- **Latest version:** 0.1.0
- **License:** Apache-2.0
- **Upstream author:** [mattmre](https://github.com/mattmre)
- **Source:** https://github.com/mattmre/AGENT33-PUBLIC

## Install

```sh
agentstack add mcp-mattmre-agent33-public
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# AGENT-33

### Local-First Multi-Agent Orchestration Platform

Governance · Evidence · Workflows · Multi-tenant Isolation · Observability

[](LICENSE)
[](CHANGELOG.md)
[](https://github.com/mattmre/AGENT33-PUBLIC/actions/workflows/ci.yml)
[](https://github.com/mattmre/AGENT33-PUBLIC/actions/workflows/security-scan.yml)
[](https://www.python.org/)
[](https://www.docker.com/)
[](https://fastapi.tiangolo.com/)
[](https://ollama.com/)
[](https://github.com/pgvector/pgvector)
[](https://github.com/mattmre/AGENT33-PUBLIC/discussions)
[](https://github.com/mattmre/AGENT33-PUBLIC/issues)
[](https://github.com/mattmre/AGENT33-PUBLIC/pulls)
[](https://github.com/mattmre/AGENT33-PUBLIC/network/members)
[](https://github.com/mattmre/AGENT33-PUBLIC/stargazers)
[](https://github.com/mattmre/AGENT33-PUBLIC/graphs/contributors)
[](CONTRIBUTING.md)

#### Local-First · Approval-gated automation · Audit trail by design · Multi-tenant

[**Quick Start**](#quick-start)  ·  [**Architecture**](docs/architecture/overview.md)  ·  [**API Reference**](docs/api-reference.md)  ·  [**Onboarding**](docs/ONBOARDING.md)

[Use Cases](docs/use-cases.md)  ·  [Walkthroughs](docs/walkthroughs.md)  ·  [Self-Improvement](docs/self-improvement/README.md)  ·  [Operator Runbooks](docs/operators/)

---

## At a Glance

  
    
      AGENTS
      6
      Reference agent definitions
    
    
      WORKFLOWS
      DAG
      Composable, with retries
    
    
      TOOLS
      7
      Schema-validated builtins
    
    
      SUBSYSTEMS
      20+
      Lifespan-wired services
    
    
      LLM PROVIDERS
      20+
      Auto-registered from env
    
    
      TENANCY
      Native
      Multi-tenant by design
    
  

---

## Why AGENT-33

AGENT-33 is a local-first AI agent orchestration platform for teams that want **real workflows, explicit governance, and a usable control plane** instead of a pile of disconnected scripts. It combines an API runtime, workflow engine, memory stack, review/release controls, and a first-party frontend so you can run guarded automation from one system.

- **Local-first runtime** — FastAPI backend, Docker Compose bootstrap, Ollama-friendly model routing
- **Contained Agent OS** — optional Linux operator workspace with first-party tools, state, and stack connectivity
- **Guardrailed automation** — scopes, approvals, autonomy budgets, and review/release workflows
- **Agent + workflow orchestration** — invoke agents directly or compose repeatable DAG workflows
- **Operational visibility** — health, dashboard surfaces, traces, evaluations, and rollout telemetry
- **Extensible platform** — packs, tools, memory, webhook intake, and improvement loops

```mermaid
flowchart LR
    U[Operator / Client] -->|HTTP · WebSocket · SSE| API[FastAPI Surface]
    API --> AR[Agent Runtime]
    AR --> WF[Workflow EngineDAG · retries · checkpoints]
    AR --> SK[Skill RegistryL0 / L1 / L2 disclosure]
    AR --> TG[Tool Governanceallowlist · autonomy · approvals]
    AR --> MEM[(Memorypgvector + BM25 RRF)]
    WF --> TP[Trace Pipelinefailure taxonomy · retention]
    TG --> TP
    AR --> TP

    style API fill:#0ea5e9,color:#fff
    style AR fill:#10b981,color:#fff
    style TG fill:#ef4444,color:#fff
    style TP fill:#f59e0b,color:#fff
    style MEM fill:#8b5cf6,color:#fff
```

For the full lifespan startup order, runtime modes (lite, standard, enterprise), and middleware chain, see [`docs/architecture/overview.md`](docs/architecture/overview.md).

---

## Repository Layout

- `engine/` — FastAPI runtime, orchestration services, API routes, tests, Docker Compose stack
- `frontend/` — AGENT-33 control plane UI served at `http://localhost:3000`
- `core/` — orchestration specs, policy packs, protocol references, workflow materials
- `docs/` — canonical operator, setup, onboarding, and release-readiness documentation

---

## Quick Start

### 30-Second Try

Spin up the stack and confirm it's alive in under a minute:

```bash
cd engine && docker compose up -d
curl http://localhost:8000/health
```

Then continue below for the full operator setup (JWT minting, agent invocation, control plane).

### Full Operator Setup

#### Prerequisites

- Docker Desktop or Docker Engine with Compose
- Python 3.11+
- `curl`
- Ollama reachable from the stack (`http://host.docker.internal:11434` by default), or use the bundled/local override paths documented in the setup guides

### 1. Start the stack

```bash
cd engine
cp .env.example .env
docker compose up -d
curl http://localhost:8000/health
```

If you reuse an Ollama container from another Compose project:

```bash
docker compose -f docker-compose.yml -f docker-compose.shared-ollama.yml up -d
```

### 2. Open the control plane

- Frontend: `http://localhost:3000`
- API docs: `http://localhost:8000/docs`

Default local credentials from `.env.example`:

- username: `admin`
- password: `admin`

### 3. Mint a local JWT for API access

```bash
docker compose exec -T api python -c "import os,time,jwt; now=int(time.time()); payload={'sub':'local-admin','scopes':['admin','agents:read','agents:write','agents:invoke','workflows:read','workflows:write','workflows:execute','tools:execute'],'iat':now,'exp':now+3600}; print(jwt.encode(payload, os.getenv('JWT_SECRET','change-me-in-production'), algorithm=os.getenv('JWT_ALGORITHM','HS256')))"
```

Set the token in your shell:

```bash
export TOKEN=""
```

PowerShell:

```powershell
$env:TOKEN = ""
```

### 4. Verify the first agent flow

List agents:

```bash
curl http://localhost:8000/v1/agents/ \
  -H "Authorization: Bearer $TOKEN"
```

Invoke the orchestrator:

```bash
curl -X POST http://localhost:8000/v1/agents/orchestrator/invoke \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "inputs": {
      "task": "Create a short rollout plan for adding cache metrics"
    },
    "model": "llama3.2",
    "temperature": 0.2
  }'
```

## First 5-Minute Operator Path

1. Start the stack and confirm `/health`
2. Sign in to `http://localhost:3000`
3. Mint a local JWT or use the UI token flow
4. List agents with `GET /v1/agents/`
5. Invoke an agent or execute a minimal workflow
6. Explore the dashboard, traces, reviews, evaluations, and autonomy surfaces from the UI

For a fuller beginner path, use:

- [Getting Started](docs/getting-started.md)
- [Operator Onboarding](docs/ONBOARDING.md)
- [Walkthroughs](docs/walkthroughs.md)

## Security and Production Warning

**Bootstrap auth is for local development only. Do not expose AGENT-33 publicly with default credentials or default secrets.**

Before any shared, VPS, or production deployment:

- set `AUTH_BOOTSTRAP_ENABLED=false`
- rotate `API_SECRET_KEY`
- rotate `JWT_SECRET`
- rotate `ENCRYPTION_KEY`
- review [SECURITY.md](SECURITY.md)
- work through the [Release Checklist](docs/RELEASE_CHECKLIST.md)

## Documentation Map

### Start here

- [Getting Started](docs/getting-started.md)
- [Operator Onboarding](docs/ONBOARDING.md)
- [Setup Guide](docs/setup-guide.md)
- [Walkthroughs](docs/walkthroughs.md)
- [Use Cases](docs/use-cases.md)
- [Agent OS Runtime](docs/operators/agent-os-runtime.md)
- [API Surface](docs/api-surface.md)
- [Release Checklist](docs/RELEASE_CHECKLIST.md)
- [Documentation Index](docs/README.md)

### Deep references

- [Functionality and Workflows](docs/functionality-and-workflows.md)
- [Production Deployment Runbook](docs/operators/production-deployment-runbook.md)
- [Operator Verification Runbook](docs/operators/operator-verification-runbook.md)
- [Horizontal Scaling Architecture](docs/operators/horizontal-scaling-architecture.md)
- [Incident Response Playbooks](docs/operators/incident-response-playbooks.md)

## Who this is for

- **Operators** who need a guarded local or self-hosted AI control plane
- **Platform teams** building approval-aware automation and workflow execution
- **Engineering teams** running review, release, evaluation, and autonomy gates in one runtime
- **Researchers and builders** experimenting with packs, memory, training, and improvement loops

## Roadmap

AGENT-33 is under active development. Near-term public direction:

- **Ecosystem growth** — broader pack catalog, community-contributed skills and tools, signed pack distribution
- **MCP integrations** — richer hosted MCP server surface and tighter MCP client interop with the agent runtime
- **Public benchmarking** — continued evaluation against [SkillsBench](https://github.com/benchflow-ai/skillsbench) with CTRF reporting and weekly full-tier runs
- **Provider depth** — first-class support for additional local-inference backends (llama.cpp, LM Studio, AirLLM) and embedding providers
- **Operator UX** — visual workflow builder polish, sub-agent execution trees, knowledge ingestion cron expansion

See [CHANGELOG.md](CHANGELOG.md) for release history.

## Contributors

  

Every commit, issue, review, and Discussion thread makes the project better. Thank you.

## Star History

  
    
    
    
  

## License

Apache License 2.0. See [LICENSE](LICENSE).

---

**[Documentation](docs/)**  ·  **[API Reference](docs/api-reference.md)**  ·  **[Architecture](ARCHITECTURE.md)**  ·  **[Changelog](CHANGELOG.md)**  ·  **[Presentation Suite](presentation/index.html)**  ·  **[Discussions](https://github.com/mattmre/AGENT33-PUBLIC/discussions)**

AGENT-33 v2.1.0 · Apache License 2.0 · Local-first multi-agent orchestration with built-in governance

## Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [mattmre](https://github.com/mattmre)
- **Source:** [mattmre/AGENT33-PUBLIC](https://github.com/mattmre/AGENT33-PUBLIC)
- **License:** Apache-2.0

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** yes
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** yes
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/mcp-mattmre-agent33-public
- Seller: https://agentstack.voostack.com/s/mattmre
- Browse the marketplace: https://agentstack.voostack.com/browse

---
Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.