How to integrate Hashnode MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting Hashnode to the OpenAI Agents SDK 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 OpenAI Agents SDK 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 necessary dependencies
  • Initialize Composio and create a Tool Router session for Hashnode
  • Configure an AI agent that can use Hashnode as a tool
  • Run a live chat session where you can ask the agent to perform Hashnode operations

What is open-ai-agents-sdk?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.

Key features include:

  • Hosted MCP Tools: Connect to external services through hosted MCP endpoints
  • SQLite Sessions: Persist conversation history across interactions
  • Simple API: Clean interface with Agent, Runner, and tool configuration
  • Streaming Support: Real-time response streaming for interactive applications

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

Before starting, make sure you have:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Hashnode project
  • Some knowledge of Python or Typescript

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

Install dependencies

pip install composio_openai_agents openai-agents python-dotenv

Install the Composio SDK and the OpenAI Agents SDK.

Set up environment variables

bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com

Create a .env file and add your OpenAI and Composio API keys.

Import dependencies

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
What's happening:
  • You're importing all necessary libraries.
  • The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Hashnode.

Set up the Composio instance

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
What's happening:
  • load_dotenv() loads your .env file so OPENAI_API_KEY and COMPOSIO_API_KEY are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.

Create a Tool Router session

# Create a Hashnode Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["hashnode"]
)

mcp_url = session.mcp.url

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only hashnode.
  • The router checks the user's Hashnode connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Hashnode.
  • This approach keeps things lightweight and lets the agent request Hashnode tools only when needed during the conversation.

Configure the agent

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Hashnode. "
        "Help users perform Hashnode operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
What's happening:
  • We're creating an Agent instance with a name, model (gpt-5), and clear instructions about its purpose.
  • The agent's instructions tell it that it can access Hashnode and help with queries, inserts, updates, authentication, and fetching database information.
  • The tools array includes a HostedMCPTool that connects to the MCP server URL we created earlier.
  • The headers dict includes the Composio API key for secure authentication with the MCP server.
  • require_approval: 'never' means the agent can execute Hashnode operations without asking for permission each time, making interactions smoother.

Start chat loop and handle conversation

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
What's happening:
  • The program prints a session URL that you visit to authorize Hashnode.
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using Runner.run().
  • The responses are printed to the console, and conversations are saved locally using SQLite.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with Hashnode and open-ai-agents-sdk:

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["hashnode"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Hashnode. "
        "Help users perform Hashnode operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())

Conclusion

This was a starter code for integrating Hashnode MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Hashnode.

Key features:

  • Hosted MCP tool integration through Composio's Tool Router
  • SQLite session persistence for conversation history
  • Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

How to build Hashnode MCP Agent with another framework

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 OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK 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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