How to integrate Hashnode MCP with Autogen

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Introduction

This guide walks you through connecting Hashnode to AutoGen using the Composio tool router. By the end, you'll have a working Hashnode agent that can list my most recent hashnode articles, check if 'devjournal.com' domain is available, fetch popular tags for trending topics, get details for the post 'how-to-use-composio' through natural language commands.

This guide will help you understand how to give your AutoGen agent real control over a Hashnode account through Composio's Hashnode MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the required dependencies for Autogen and Composio
  • Initialize Composio and create a Tool Router session for Hashnode
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Hashnode tools
  • Run a live chat loop where you ask the agent to perform Hashnode operations

What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.

Key features include:

  • Multi-Agent Systems: Build collaborative agent workflows
  • MCP Workbench: Native support for Model Context Protocol tools
  • Streaming HTTP: Connect to external services through streamable HTTP
  • AssistantAgent: Pre-built agent class for tool-using assistants

What is the Hashnode MCP server, and what's possible with it?

The Hashnode MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Hashnode account. It provides structured and secure access to your blog and developer publication data, so your agent can fetch articles, manage publication invites, reply to comments, and explore tags or user details on your behalf.

  • Fetch and analyze articles: Let your agent retrieve single articles or lists of posts from your publications, making it easy to summarize, review, or manage your content.
  • Publication invite handling: Effortlessly accept publication invitations or view all your pending invites, streamlining the process of joining new developer teams or publications.
  • Interact with comments and replies: Have your agent add replies to existing comments, enabling automated engagement and conversation management on your posts.
  • Tag discovery and trend tracking: Easily fetch popular tags so your agent can suggest relevant topics, optimize your writing focus, or help you follow industry trends.
  • User and publication insights: Retrieve detailed profile information for any user or publication, giving your agent the context needed for personalized recommendations and content actions.

Supported Tools & Triggers

Tools
Hashnode Accept Publication InviteTool to accept a publication invitation.
Hashnode Add ReplyTool to add a reply to an existing comment.
Hashnode: Check Custom Domain AvailabilityTool to check if a custom domain is available for your Hashnode publication.
Hashnode: Fetch InvitationsTool to fetch pending publication invitations.
Hashnode: Fetch Popular TagsTool to fetch a paginated list of popular tags.
Fetch Publication PostsTool to fetch a paginated list of posts from a publication.
Fetch Series PostsTool to fetch posts from a series within a publication.
Fetch Single ArticleTool to fetch a single article by slug from a publication.
Hashnode: Fetch User DetailsTool to fetch detailed user profile information by username.
Get Publication by HostnameTool to fetch details (id, title, about) of a publication by hostname.
Hashnode Add CommentTool to add a comment to a Hashnode post.
Fetch Stories FeedTool to fetch a paginated home feed of stories.
Hashnode: Get Current UserTool to retrieve details of the currently authenticated user.
Hashnode: Like ReplyTool to like a reply on Hashnode.
Hashnode: List PublicationsTool to list all publications of the authenticated user.
Hashnode Remove ReplyTool to remove a reply from a comment.
Hashnode Update CommentTool to update an existing comment on a Hashnode post.
Hashnode Update ReplyTool to update a reply.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Prerequisites

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Hashnode account you can connect to Composio
  • Some basic familiarity with Autogen and Python async

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.

Install dependencies

bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

  • composio connects your agent to Hashnode via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

Set up environment variables

bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

Create a .env file in your project folder.

What's happening:

  • COMPOSIO_API_KEY is required to talk to Composio
  • OPENAI_API_KEY is used by Autogen's OpenAI client
  • USER_ID is how Composio identifies which user's Hashnode connections to use

Import dependencies and create Tool Router session

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Hashnode session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["hashnode"]
    )
    url = session.mcp.url
What's happening:
  • load_dotenv() reads your .env file
  • Composio(api_key=...) initializes the SDK
  • create(...) creates a Tool Router session that exposes Hashnode tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to

Configure MCP parameters for Autogen

python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.

What's happening:

  • url points to the Tool Router MCP endpoint from Composio
  • timeout is the HTTP timeout for requests
  • sse_read_timeout controls how long to wait when streaming responses
  • terminate_on_close=True cleans up the MCP server process when the workbench is closed

Create the model client and agent

python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Hashnode assistant agent with MCP tools
    agent = AssistantAgent(
        name="hashnode_assistant",
        description="An AI assistant that helps with Hashnode operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

  • OpenAIChatCompletionClient wraps the OpenAI model for Autogen
  • McpWorkbench connects the agent to the MCP tools
  • AssistantAgent is configured with the Hashnode tools from the workbench

Run the interactive chat loop

python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Hashnode related question or task to the agent.\n")

# Conversation loop
while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    print("\nAgent is thinking...\n")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
What's happening:
  • The script prompts you in a loop with You:
  • Autogen passes your input to the model, which decides which Hashnode tools to call via MCP
  • agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
  • Typing exit, quit, or bye ends the loop

Complete Code

Here's the complete code to get you started with Hashnode and AutoGen:

import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Hashnode session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["hashnode"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Hashnode assistant agent with MCP tools
        agent = AssistantAgent(
            name="hashnode_assistant",
            description="An AI assistant that helps with Hashnode operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

        print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
        print("Ask any Hashnode related question or task to the agent.\n")

        # Conversation loop
        while True:
            user_input = input("You: ").strip()

            if user_input.lower() in ['exit', 'quit', 'bye']:
                print("\nGoodbye!")
                break

            if not user_input:
                continue

            print("\nAgent is thinking...\n")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You now have an Autogen assistant wired into Hashnode through Composio's Tool Router and MCP. From here you can:
  • Add more toolkits to the toolkits list, for example notion or hubspot
  • Refine the agent description to point it at specific workflows
  • Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Hashnode, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

How to build Hashnode MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Hashnode MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Hashnode MCP with Claude Agent SDK

Google ADK

Google ADK

Use Hashnode MCP with Google ADK

LangChain

LangChain

Use Hashnode MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Hashnode MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Hashnode MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Hashnode MCP with LlamaIndex

CrewAI

CrewAI

Use Hashnode MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Hashnode MCP?

With a standalone Hashnode MCP server, the agents and LLMs can only access a fixed set of Hashnode tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Hashnode and many other apps based on the task at hand, all through a single MCP endpoint.

Can I use Tool Router MCP with Autogen?

Yes, you can. Autogen fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Hashnode tools.

Can I manage the permissions and scopes for Hashnode while using Tool Router?

Yes, absolutely. You can configure which Hashnode scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Hashnode data and credentials are handled as safely as possible.

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