Verbinden Sie Autogen mit ChatGPT, Claude und Gemini

• 01 / 02Code-Reviews automatisieren
• 02 / 02Gespräche debuggen

Schnellster Tag

626ms

Langsamster Tag

934ms

14-Tage-Trend

Stabil+1%

Microsoft AutoGen Connector

Alles bereit. Wählen Sie Ihren MCP-Client und folgen Sie den Einrichtungsschritten.

Connector-Linkhttps://edge.vinkius.com/vk_preview_im6ZUleGV5zCo8b51ydydKQxlYTOsNTFUZKM0ez4/mcpKopieren

Claude Desktop

Folgen Sie den Schritten unten, um sich in Sekunden zu verbinden.

1. 1In Claude Desktop, open Settings → Connectors.
2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
3. 3Click Add and start a new chat — Microsoft AutoGen capabilities are ready to use.

Konfiguration · claude_desktop_config.jsonKopieren

{
  "mcpServers": {
    "autogen-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_im6ZUleGV5zCo8b51ydydKQxlYTOsNTFUZKM0ez4/mcp"
    }
  }
}

• Claude
• ChatGPT
• Cursor
• VS Code
• Windsurf
• Claude Code
• JetBrains
• Cline

Schritt-für-Schritt-Anleitungen für jeden Client finden Sie im Guide. Verbinden

Geführte Einrichtung für Claude? Microsoft AutoGen in Claude und anderen KI-Tools einrichten

Alle KI-Clients ansehen, mit denen dieser Connector funktioniert ↑

• 01

  KI-Ingenieure

  Auditieren Sie laufende Agenten-Topologien, verfolgen Sie tiefe Execution Logs und iterieren Sie an Python Skills, ohne den Kontext wechseln zu müssen.

• 02

  Produktmanager

  Überprüfen Sie den Zustand und die Schritte automatisierter Backend-Swarm-Operationen, um die Produktzuverlässigkeit zu gewährleisten.

• 03

  Forscher

  Extrahieren Sie einfach tiefgehende LLM-zu-LLM Konversationsverläufe über experimentelle Grenzen hinweg, um Ergebnisse zu bewerten.

• 01

  What is the difference between a 'session' and a 'workflow'?

  A session is the isolated memory space where the conversation happens. A workflow is the predefined topology or graph that dictates how the agents interact within that session. You create a session first, then run a workflow inside it.

• 02

  Can I debug the agents' conversations?

  Yes. You can use the message history capabilities to retrieve deep agent-to-agent conversation traces. This lets you see exactly which agent said what and why, which is critical for debugging.

• 03

  Do I need to write code to use this MCP?

  No. You interact with this MCP using natural conversation prompts through your AI client. The underlying complexity, like defining agents or listing skills, is handled by the capabilities you invoke.

• 04

  What if I want to change an agent's role?

  You can redefine agents using the create_agent capability. This lets you change their parameters, giving them new roles or specialized instructions mid-project.

• 05

  Does this MCP support multiple types of agents?

  Yes. You can define and manage multiple, specialized agents, such as a User Proxy, a Coder, and a Critic, allowing them to collaborate on a single task.

• 06

  Can my AI agent debug a looping multi-agent conversation?

  Yes. You can instruct your primary agent to retrieve the message traces for a specific AutoGen session ID. It will instantly unpack the internal LLM-to-LLM conversation, highlighting exactly which secondary agent is looping, throwing errors, or deviating from the constraints without manual log parsing.

• 07

  How do I add a new Python capability or skill dynamicly?

  Your agent can list currently mapped Python skills bound to the studio runtime. If you need a new capability, your primary AI can iterate on the script directly on your CLI/editor and once deployed in your studio, you can map it natively to customized agents via the creation parameters.

• 08

  Can it trigger a Workflow to start executing a new complex task?

  Absolutely. Ask your agent to create a fresh, blank, and completely isolated session, then dispatch a newly constructed 'human message' targeting an existing Multi-Agent workflow topology. It initiates the whole automated logic sequence securely and remotely.

• 

  n8n (AI Workflow Automation) KI-Connector

  Manage workflow automation via n8n — audit active workflows, track execution logs, and monitor credentials.

  Ansehen
• 

  Make (Workflow Automation) KI-Connector

  Manage workflow automation via Make — audit scenarios, track execution logs, and monitor data stores.

  Ansehen
• 

  Langflow (Visual Multi-agent Orchestrator) KI-Connector

  Orchestrate multi-agent AI workflows visually — execute flows, manage projects, and trigger webhooks directly

  Ansehen
• 

  Relay Workflow Automation KI-Connector

  List, run, and manage workflow automations via Relay API.

  Ansehen

Vorschläge

• 

  GitScrum Tasks KI-Connector

  Master task execution via GitScrum — create, filter, assign, and track tasks with subtasks, checklists, and co

  Ansehen
• 

  CrewAI Platform KI-Connector

  Orchestrate multi-agent workflows via CrewAI — list crews and agents, kickoff autonomous runs, and monitor tas

  Ansehen
• 

  UnifyApps KI-Connector

  Automate integration workflows via UnifyApps — monitor execution logs, check active flows, audit connections,

  Ansehen
• 

  Multi-Turn Conversation Compressor KI-Connector

  Deterministic engine for reducing conversation history size while preserving semantic continuity.

  Ansehen