How to Use the Medium Alternative MCP in LangChain

Q: Can LangChain handle draft formatting errors with Medium Alternative?

Yes. When createpost returns a formatting error, LangChain agents inspect the raw error payload via LangSmith. The agent then rewrites the markdown or HTML and submits the post again.

Q: Can I post to specific publications?

Use listpublications to find the correct ID first. Then, pass that ID into the createpublicationpost tool to route your story to the correct publication queue.

Publish stories and manage publications directly from your LangChain chains and ReAct agents.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Medium Alternative MCP to LangChain

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

GDPR Free for Subscribers

Setup Medium Alternative with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Chain publication steps with LangChain

The `create_post` tool lets your LangChain agent publish drafts or live stories directly to your profile. By linking this tool into a sequential chain, the output of your content generation chain feeds directly into the publishing payload without manual copy-pasting. You trace the entire execution in LangSmith to monitor payload delivery and check latency. If a step fails, the agent inspects the error and retries the publish call with corrected formatting.

Audit publication teams using this MCP Server

The `list_contributors` tool retrieves the active writer and editor lists for any publication you manage. Your LangChain agent runs this check before calling `create_publication_post` to verify that the target author has the correct permissions to submit drafts. This multi-step validation prevents API errors during automated runs. The agent checks the contributor list, matches it against your internal database, and only proceeds with the publication workflow if the validation succeeds.

Map user profiles to target publications

The `get_me` tool fetches your authenticated profile details to establish the base user ID for downstream operations. Your agent combines this profile data with `list_publications` to determine which publication queues are available for your current integration token. This mapping ensures your automated pipelines route content to the correct publication without hardcoding IDs. LangChain manages these transitions in memory, passing the verified IDs from one node to the next in your graph.

Setup guide

Set up Medium Alternative MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Medium Alternative tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

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

async with MultiServerMCPClient({
    "medium-alternative-mcp": {
        "transport": "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,
    )
    result = await agent.ainvoke({
        "messages": "List recent Medium Alternative transactions"
    })
    print(result["messages"][-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Medium. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Medium Alternative now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Medium Alternative MCP in LangChain

Install the adapter package and initialize the MultiServerMCPClient with the server URL. Pass the tools retrieved from the client directly into your agent's tool list.

Yes. When create_post returns a formatting error, LangChain agents inspect the raw error payload via LangSmith. The agent then rewrites the markdown or HTML and submits the post again.

The server passes raw rate limit headers back to your agent. You configure standard LangChain retry logic on the tool-calling node to handle backoffs when publishing multiple posts.

Use list_publications to find the correct ID first. Then, pass that ID into the create_publication_post tool to route your story to the correct publication queue.

Your integration tokens and draft content remain isolated within the Vinkius V8 sandbox. The ephemeral MCP server processes these credentials on demand, never writing your tokens or drafts to persistent storage.

Use it with your favorite AI tools

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

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript