Bring Multi Agent Systems
to Cline

Connect your AutoGen Studio instance to any AI agent and take full control of your multi-agent topologies and execution memory spaces through natural conversation.

What you can do

• Sessions — Create and manage blank, isolated memory spaces for your multi-agent workflows to run cleanly
• Messages — Dispatch human prompts and retrieve deep agent-to-agent conversational traces inside Microsoft's logging structures
• Agents — Map out and dynamically define customized LLM roles (User_Proxy, Coder, Critic) using Python-based parameters
• Workflows & Skills — Visualize routing topographies, available graph deployments, and injected native Python capabilities
• Models — Audit existing constrained fallback OpenAI configurations natively stored in the engine

How it works

1. Subscribe to this server
2. Provide your AutoGen Studio instance Base URL
3. Start dispatching nested groups of AI agents directly from Claude, Cursor, or any MCP-compatible client

Your primary agent can now command and debug secondary swarms of specialized agents dynamically.

Who is this for?

• AI Engineers — audit running agent topologies, trace deep execution logs, and iterate on Python skills without swapping contexts
• Product Managers — verify the health and steps of automated backend swarm operations
• Researchers — easily extract deep LLM-to-LLM conversational histories across experimental boundaries for grading