autogen-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@autogen-mcpRegister a cheap sub-agent 'code_reviewer' for reviewing pull requests."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
autogen-mcp
AutoGen multi-agent conversations as an MCP server for Claude Code. Two surfaces:
Swarm hierarchy — persistent sub-agents, each owning one task's context, with tiered conversation permissions (heavy agents converse freely; cheap agents route requests through the manager).
Group debates — ad-hoc autonomous round-robin conversations between fresh agents.
Transcripts and per-agent logs are stored per project: in
.autogen-swarm/ inside whatever directory the Claude Code session runs in
(override with the AUTOGEN_MCP_DATA_DIR env var; falls back to this
project's directory if the cwd isn't writable).
The hierarchy model
The manager is your
claude-manager(heavy / GLM-5.2) Claude Code session — it drives the MCP tools and follows~/agent-swarm/manager_prompt.md.Sub-agents are persistent AutoGen agents in this server. Each is registered with a
role(the task it owns) and keeps its conversation memory for the whole server session; every exchange is appended to.autogen-swarm/agents/<name>.jsonlin the session's project.Tiers:
heavyagents get a server-sideconversetool and can talk to any other agent directly.cheapagents get no such tool — the server instructs them to emitNEED_INFO(<task-or-agent>): <question>lines, whichsend_messagesurfaces asinfo_requestsfor the manager to relay. Circular conversations and deep relay chains are blocked server-side. Iftieris omitted at registration, thecheapmodel alias defaults to the cheap tier and everything else to heavy.
Setup
cd ~/Documents/projects/claude_code+autogen
uv syncRequired environment variables (in the shell that launches Claude Code):
ANTHROPIC_API_KEY— foranthropic:*/opusparticipantsDEEPINFRA_API_KEY— fordeepinfra:*/heavy/cheapparticipants
Registration
The project-scoped .mcp.json is already in place — any claude session
started in this directory picks up the autogen-chat server automatically
(you'll be asked to approve it once).
It is also registered user-scope (global) in all three Claude Code profiles, so it's available from any directory. User-scope config lives in the profile's config dir, so each profile needs its own registration:
MCPDIR=~/Documents/projects/claude_code+autogen
# default profile
claude mcp add --scope user autogen-chat -- \
uv run --project "$MCPDIR" python "$MCPDIR/server.py"
# manager / worker profiles (separate CLAUDE_CONFIG_DIR)
CLAUDE_CONFIG_DIR=~/.claude-manager claude mcp add --scope user autogen-chat -- \
uv run --project "$MCPDIR" python "$MCPDIR/server.py"
CLAUDE_CONFIG_DIR=~/.claude-worker claude mcp add --scope user autogen-chat -- \
uv run --project "$MCPDIR" python "$MCPDIR/server.py"Note: --project (not --directory) matters — it selects this project's
Python environment while preserving the working directory Claude Code
launches the server with, which is what makes per-project log storage work.
Usage from Claude Code
Just ask in natural language.
Swarm workflow (the manager session does this per its prompt):
Register a cheap sub-agent
api_taskowning the REST endpoints and a cheap sub-agentdb_taskowning the schema. Brief each with its scope and acceptance test, then relay any NEED_INFO requests between them.
Group debate:
Start a conversation between opus and heavy about whether we should migrate this repo to a monorepo. 8 rounds. Check on it and summarize when done.
Claude Code will call the tools:
Swarm hierarchy (persistent sub-agents):
Tool | Purpose |
| Create a persistent sub-agent owning one task ( |
| Converse with a sub-agent; result includes |
| Read an agent's exchange history ( |
| Roster with tiers, roles, exchange counts |
| Retire an agent (log file survives) |
Group debates (ad-hoc conversations):
Tool | Purpose |
| Kick off a background group chat, returns an ID |
| Poll new turns ( |
| Queue a steering message, delivered at the next round boundary |
| Cancel a running chat |
| Show all chats in this session |
MCP resources: conversation://<id> and agent://<name> expose full
transcripts as readable text.
Model specs
Participants take "model" as <provider>:<model> or a shorthand alias:
Alias | Resolves to |
|
|
|
|
|
|
Any DeepInfra model works via deepinfra:<org>/<model> (uses their
OpenAI-compatible endpoint at api.deepinfra.com/v1/openai).
Notes and caveats
Which shell you launch from decides which providers work. The
claude-cheap/claude-heavy/claude-manageraliases blankANTHROPIC_API_KEY, so from those sessions only DeepInfra participants (heavy,cheap,deepinfra:*) work — which is all the swarm hierarchy needs.opus/anthropic:*participants require a shell withANTHROPIC_API_KEYset (your plainclaude). Note the debate default pair includesopus, so from an alias shell pass explicit agents tostart_conversation. The server pins its base URLs (api.anthropic.com/ DeepInfra), so the aliases'ANTHROPIC_BASE_URLoverride can't misroute requests either way. The server is registered user-scope in all three profiles, so any session in any directory gets the tools — and its swarm data lands in that session's own.autogen-swarm/.Conversations and agent memory die with the session. stdio servers live as long as the Claude Code session that spawned them. Transcripts (
.autogen-swarm/transcripts/*.jsonl) and agent logs (.autogen-swarm/agents/*.jsonl) survive on disk in the session's project, but in-flight chats and sub-agent conversation memory don't — after a restart, re-register agents and re-brief them (e.g. paste the relevant log back as the first message). If you want a long-lived daemon, switchmcp.run()to the streamable-HTTP transport and register the URL instead.Sub-agents are chat-only. They think and produce code as text; they don't touch files. Execution stays with the manager or headless
claude-cheap-yoloworkers — report outcomes back into the owning agent's context so it remains the source of truth.Steering granularity is one round.
inject_messageis delivered at the next round-robin boundary, not mid-turn.Cost:
max_roundsis the guardrail. Two eager models can burn tokens fast — keep rounds modest and usecheapparticipants for experiments.
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