How to Use the Medium MCP in Pydantic AI

Q: Can I use Pydantic AI to automate my Medium drafts?

You can. The createdraft tool is fully compatible with your agent's type-checking, ensuring your drafts are formatted correctly every time.

Validate your Medium publishing actions with Pydantic AI to ensure type-safe content management and error-free posts.

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Connect Medium MCP to Pydantic AI

Create your Vinkius account to connect Medium 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 Medium with Pydantic AI

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Type-safe Medium posts with Pydantic AI

Every response from `create_post` is validated against your Pydantic models. If the API returns unexpected data, your agent catches the issue immediately. Use `create_publication_post` to send content to your publications. Your agent confirms the structure matches your requirements before the post goes live.

Manage drafts securely via Pydantic AI

Your agent uses `create_draft` to stage your content. Because you use Pydantic AI, you know the draft creation parameters are correct before the agent proceeds. This workflow prevents corrupted content from reaching your account. Your agent validates every field against your schema before calling the API.

Inspect Medium records with Pydantic AI

Use `list_publications` to pull your publication list into a validated model. Your agent can then reason about your account structure with total confidence. Call `get_my_profile` to verify your account data. Your agent ensures your profile state is consistent with your application logic, preventing runtime surprises.

Setup guide

Set up Medium 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": {
        "medium-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about Medium MCP in Pydantic AI

It validates every API response against your predefined Pydantic models. If the server returns bad data, the agent triggers a validation error instead of failing silently.

You can. The `create_draft` tool is fully compatible with your agent's type-checking, ensuring your drafts are formatted correctly every time.

It is. The connection uses standard authentication and runs in a sandbox. Your agent only interacts with the API through your validated tool definitions.

You just need to pass the server URL to the toolset. Pydantic AI handles the transport and ensures all tool calls are type-safe.

It accesses your Medium post content, draft status, and user profile information. The server only touches the data points required to complete your requested publishing actions.

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