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 LangChain 10 tools — connect in under 2 minutes

Name: Medium
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Medium through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

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 langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "medium": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Medium, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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.

LangChain's ecosystem of 500+ components combines seamlessly with Medium through native MCP adapters. Connect 10 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

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 LangChain 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 LangChain via MCP

Follow these steps to integrate the Medium MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 10 tools from Medium via MCP

Why Use LangChain with the Medium MCP Server

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

The largest ecosystem of integrations, chains, and agents. combine Medium MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Medium queries for multi-turn workflows

Medium + LangChain Use Cases

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

RAG with live data: combine Medium tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Medium, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Medium tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Medium tool call, measure latency, and optimize your agent's performance

Medium MCP Tools for LangChain (10)

These 10 tools become available when you connect Medium to LangChain 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 LangChain

Ready-to-use prompts you can give your LangChain 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 LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Medium + LangChain FAQ

Common questions about integrating Medium MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.