How do I get a Medium Integration Token?

Go to Medium Settings > Security and apps > Integration tokens to generate your token.

Can I publish in Markdown?

Yes! The `create_post` and `create_draft` tools support Markdown format natively.

Absolutely. Your token is encrypted at rest and injected securely at runtime.

Medium MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Medium
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Medium through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Medium "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Medium?"
    )
    print(result.data)

asyncio.run(main())

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Medium MCP Server

Connect your Medium account to any AI agent and automate your publishing workflow through natural conversation.

Pydantic AI validates every Medium tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Post Creation — Quickly publish public articles or save drafts directly to your Medium account
Publication Management — List publications you belong to and publish content directly under their brand
Profile Inspection — Retrieve your unique User ID and profile details for seamless integration
Contributor Lists — View authorized contributors for publications you manage

The Medium MCP Server exposes 10 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Medium to Pydantic AI via MCP

Follow these steps to integrate the Medium MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 10 tools from Medium with type-safe schemas

Why Use Pydantic AI with the Medium MCP Server

Pydantic AI provides unique advantages when paired with Medium through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Medium integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Medium connection logic from agent behavior for testable, maintainable code

Medium + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Medium MCP Server delivers measurable value.

Type-safe data pipelines: query Medium with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Medium tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Medium and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Medium responses and write comprehensive agent tests

Medium MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Medium to Pydantic AI via MCP:

create_draft

Create a new draft

create_post

Create a new post for a user

create_public_post

Create a public post

create_publication_post

Create a post under a publication

get_authenticated_user

Get details for the authenticated user

get_my_profile

Get your own profile

get_my_user_id

Get your User ID

list_contributors

List contributors for a publication

list_my_publications

List your own publications

list_publications

List publications for a user

Example Prompts for Medium in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Medium immediately.

"Show my Medium profile and user ID."

"Create a draft titled 'My AI Journey' with content 'This is my first post...'"

"List my publications."

Troubleshooting Medium MCP Server with Pydantic AI

Common issues when connecting Medium to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Medium + Pydantic AI FAQ

Common questions about integrating Medium MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Medium MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.