What you’ll have in ~10 minutes: a local org of AI agents — coordinated by a single markdown file, visible in a real-time dashboard, with tasks flowing through a hierarchy you define.
OpenSpawn is a coordination layer for AI agents. It is not an agent framework — you keep using whatever you already use (LangGraph, Claude Code, CrewAI, raw API calls). OpenSpawn adds the layer most multi-agent systems are missing: structure.
ORG.md → OpenSpawn parses it → agents spawn → tasks flow through hierarchy → dashboard shows everything
The key idea: One file — ORG.md — defines your entire agent organization. Roles, hierarchy, culture, budget policies, and operating procedures all live in one readable, version-controlled markdown file. The document IS the system.
Q: How is this different from CrewAI / LangGraph / AutoGen?
Those are agent frameworks — they build agents. OpenSpawn is a coordination layer — it organizes agents you already have. Use them together.
Q: Do I need to rewrite my agents?
No. OpenSpawn coordinates existing agents via standard protocols (MCP, A2A).
Define your org’s alignment values. The wizard offers 8 values — 5 enabled by default — each injected into agent system prompts (~50 tokens each) to shape decision-making without rigid rules.
Value
Default
Agent Behavior
Ownership
Yes
Single-threaded task ownership; ships or escalates
Transparency
Yes
Escalate instead of silently failing
Measurement
Yes
Report outcomes with evidence
Subsidiarity
Yes
Solve at lowest competent level
Continuous Improvement
Yes
Auto post-mortems, process updates
Speed
No
Bias toward action, ship small
Rigor
No
Depth over speed, verify first
Frugality
No
Cheap models for mechanical tasks
Each value draws from established organizational research — Edmondson’s work on psychological safety, Drucker’s management by objectives, Katzenbach & Smith’s team accountability model. Each directive is deliberately short (~50 tokens) so it fits in a system prompt without consuming your context window.
See the Values Framework guide for the full rationale behind each value and how they interact.
Select the default model for your agents. Default: Anthropic with claude-sonnet-4-20250514. Agents at L7+ automatically get upgraded to claude-opus-4-20250514 for complex reasoning tasks.
This boots the Python API server (FastAPI) with SQLite locally — no Docker required. The dashboard opens with no login by default (AUTH_MODE=none). The server provides:
Dashboard — real-time view of agents, tasks, and events at http://localhost:8787
MCP server — tool interface for agents at POST /mcp
Agent spawning — Claude Code CLI subprocesses with configurable concurrency cap
Background jobs — asyncio scheduler for SLA monitoring, escalation, and status sync
Under the hood, openspawn start invokes uv run uvicorn to launch the FastAPI app. SQLite is used for local persistence — zero external dependencies.
Q: Do I need to set up authentication?
Not for local use. By default, openspawn start runs with AUTH_MODE=none — the dashboard is open and the API accepts all requests. When you’re ready to add protection, set AUTH_MODE=local for a simple password or AUTH_MODE=full for JWT-based auth. See the API reference for details.
Locally, openspawn start uses SQLite and an asyncio scheduler — perfect for development. For production, upgrade to PostgreSQL:
Terminal window
npxopenspawninit--deploy
This generates a docker-compose.yml alongside your org scaffold:
services:
postgres:
image: pgvector/pgvector:pg16
volumes: [pgdata:/var/lib/postgresql/data]
Start the database, then run the coordinator:
Terminal window
dockercomposeup-d
npxopenspawnstart
The coordinator detects DATABASE_URL and connects to PostgreSQL instead of SQLite. The asyncio scheduler handles background jobs in both modes — no Redis required.
All other operations (task management, delegation, escalation, status, budgets) are handled via MCP tools at POST /mcp — agents call them directly through the API.