How to integrate Hashnode MCP with CrewAI

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Introduction

This guide walks you through connecting Hashnode to CrewAI 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 CrewAI 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 a Composio API key and configure your Hashnode connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Hashnode
  • Build a conversational loop where your agent can execute Hashnode operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

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:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Hashnode connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python

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 crewai crewai-tools[mcp] python-dotenv
What's happening:
  • composio connects your agent to Hashnode via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools[mcp] includes MCP helpers
  • python-dotenv loads environment variables from .env

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model

Import dependencies

python
import os
from composio import Composio
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
import dotenv

dotenv.load_dotenv()

COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Hashnode MCP URL

Create a Composio Tool Router session for Hashnode

python
composio_client = Composio(api_key=COMPOSIO_API_KEY)
session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["hashnode"])

url = session.mcp.url
What's happening:
  • You create a Hashnode only session through Composio
  • Composio returns an MCP HTTP URL that exposes Hashnode tools

Initialize the MCP Server

python
server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users search the internet effectively",
        backstory="You are a helpful assistant with access to search tools.",
        tools=tools,
        verbose=False,
        max_iter=10,
    )
What's Happening:
  • Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication.
  • MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format.
  • Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools.
  • Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops.
  • Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries.

Create a CLI Chatloop and define the Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")

conversation_context = ""

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

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

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Conversation history:\n{conversation_context}\n\n"
            f"Current request: {user_input}"
        ),
        expected_output="A helpful response addressing the user's request",
        agent=agent,
    )

    crew = Crew(agents=[agent], tasks=[task], verbose=False)
    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's Happening:
  • Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable.
  • Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean.
  • Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses.
  • Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context.
  • Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response.
  • Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity.

Complete Code

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

from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter
from composio import Composio
from dotenv import load_dotenv
import os

load_dotenv()

GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_API_KEY is not set in the environment.")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment.")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment.")

# Initialize Composio and create a session
composio = Composio(api_key=COMPOSIO_API_KEY)
session = composio.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["hashnode"],
)
url = session.mcp.url

# Configure LLM
llm = LLM(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY"),
)

server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users with internet searches",
        backstory="You are an expert assistant with access to Composio Search tools.",
        tools=tools,
        llm=llm,
        verbose=False,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end.\n")

    conversation_context = ""

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

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

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Conversation history:\n{conversation_context}\n\n"
                f"Current request: {user_input}"
            ),
            expected_output="A helpful response addressing the user's request",
            agent=agent,
        )

        crew = Crew(agents=[agent], tasks=[task], verbose=False)
        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

Conclusion

You now have a CrewAI agent connected to Hashnode through Composio's Tool Router. The agent can perform Hashnode operations through natural language commands.

Next steps:

  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations

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

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 CrewAI?

Yes, you can. CrewAI 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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