How to Use the AutoGen MCP in Pydantic AI

Ensure type-safe agent responses with AutoGen and Pydantic AI.

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Connect AutoGen MCP to Pydantic AI

Create your Vinkius account to connect AutoGen to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup AutoGen with Pydantic AI

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Validate AutoGen responses in Pydantic AI

Every tool call like `list_skills` returns data that gets checked against your models. If the schema doesn't match, the agent stops immediately. This prevents your agent from hallucinating fields or breaking your downstream code. You get reliability that standard frameworks miss.

Query AutoGen skills with Pydantic AI

Call `list_skills` to see exactly what Python functions are exposed to your agents. The framework validates every function signature for you. This makes building robust agents simpler because you catch errors at runtime. You won't deal with silent failures.

Manage AutoGen session state in Pydantic AI

Use `create_session` to initialize your agent context. It creates a validated container for all your future message exchanges. Keep your state clean by using `delete_session` periodically. It ensures your memory doesn't get cluttered with old, invalid data.

Setup guide

Set up AutoGen MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "autogen-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to AutoGen tools.",
)

result = await agent.run("List recent AutoGen transactions")
print(result.output)

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Common questions about AutoGen MCP in Pydantic AI

Install the slim package, define your MCP toolset, and pass it to your Agent object. It handles the rest.

It does. If an MCP tool returns unexpected data, the framework raises a validation error instantly.

Yes. The framework is model-agnostic, so you can point it at local endpoints or cloud APIs.

The agent halts execution and reports the validation error. This prevents the system from proceeding with bad data.

All your session objects are encrypted at rest. We protect your Pydantic model definitions and message logs inside a zero-trust environment.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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