How to integrate DEV Community MCP with Pydantic AI

This guide walks you through connecting DEV Community to Pydantic AI using the Composio tool router. By the end, you'll have a working DEV Community agent that can list your published dev articles, draft a tutorial post about docker, find trending javascript posts on dev through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a DEV Community account through Composio's DEV Community MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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DEV Community (dev.to) is a social publishing platform for software developers. Use it to share technical articles, grow a developer audience, and join community discussions.

28 Tools

Introduction

This guide walks you through connecting DEV Community to Pydantic AI using the Composio tool router. By the end, you'll have a working DEV Community agent that can list your published dev articles, draft a tutorial post about docker, find trending javascript posts on dev through natural language commands.

This guide will help you understand how to give your Pydantic AI agent real control over a DEV Community account through Composio's DEV Community MCP server.

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

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TL;DR

Here's what you'll learn:
  • How to set up your Composio API key and User ID
  • How to create a Composio Tool Router session for DEV Community
  • How to attach an MCP Server to a Pydantic AI agent
  • How to stream responses and maintain chat history
  • How to build a simple REPL-style chat interface to test your DEV Community workflows

What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.

Key features include:

  • Type Safety: Built on Pydantic for automatic data validation
  • MCP Support: Native support for Model Context Protocol servers
  • Streaming: Built-in support for streaming responses
  • Async First: Designed for async/await patterns

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

The DEV Community MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your DEV Community account. It provides structured and secure access so your agent can perform DEV Community operations on your behalf.

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

What is Composio SDK?

Composio's Composio SDK 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 Composio SDK

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

How the Composio SDK works

The Composio SDK 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

Step by step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account with an active API key
  • Basic familiarity with Python and async programming
2

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.
3

Install dependencies

bash
pip install composio pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like DEV Community
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file
4

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

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your agent to Composio's API
  • USER_ID associates your session with your account for secure tool access
  • OPENAI_API_KEY to access OpenAI LLMs
5

Import dependencies

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()
What's happening:
  • We load environment variables and import required modules
  • Composio manages connections to DEV Community
  • MCPServerStreamableHTTP connects to the DEV Community MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant
6

Create a Tool Router Session

python
async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for DEV Community
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["devto"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")
What's happening:
  • We're creating a Tool Router session that gives your agent access to DEV Community tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use
7

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
devto_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[devto_mcp],
    instructions=(
        "You are a DEV Community assistant. Use DEV Community tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the DEV Community endpoint
  • The agent uses GPT-5 to interpret user commands and perform DEV Community operations
  • The instructions field defines the agent's role and behavior
8

Build the chat interface

python
# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with DEV Community.\n")

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", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()
What's happening:
  • The agent reads input from the terminal and streams its response
  • DEV Community API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns
9

Run the application

python
if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • The asyncio loop launches the agent and keeps it running until you exit

Complete Code

Here's the complete code to get you started with DEV Community and Pydantic AI:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for DEV Community
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["devto"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    devto_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[devto_mcp],
        instructions=(
            "You are a DEV Community assistant. Use DEV Community tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with DEV Community.\n")

    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", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

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

Conclusion

You've built a Pydantic AI agent that can interact with DEV Community through Composio's Tool Router. With this setup, your agent can perform real DEV Community actions through natural language. You can extend this further by:
  • Adding other toolkits like Gmail, HubSpot, or Salesforce
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + DEV Community for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.
TOOLS

Supported Tools

Every DEV Community action and event your agent gets out of the box.

Create Article

Create a new article on DEV Community.

Get Article By ID

Returns a single published article by its ID, including full body content.

Get Article By Path

Returns a single published article by username and slug path.

Get Comment by ID

Returns a single comment and its descendants (replies) by comment ID.

Get Current User

Tool to get the currently authenticated user's profile information.

Get Listing

Returns a single classified listing by its ID.

Get Organization

Returns a single organization by its username.

Get Profile Image

Returns the profile image URL for a user or organization by username.

Get user

Tool to get a single user by their ID or username.

List Articles

Returns a list of published articles, optionally filtered by tags, username, state, or top articles.

List Comments

Tool to list comments for a specified article or podcast episode on DEV Community.

List Followed Tags

Returns a list of tags followed by the authenticated user.

List Followers

Tool to retrieve a list of users who follow the authenticated user.

List latest DEV Community articles

Tool to retrieve a list of published articles sorted by descending publish date.

List Listings

Returns a list of classified listings for jobs, mentors, products, etc.

List Listings By Category

Returns a list of classified listings filtered by category.

List Organization Articles

Tool to list articles published by a specific organization on DEV.

List organization users on DEV.to

Tool to list users belonging to a specified organization on DEV.

List podcast episodes on DEV.to

Tool to retrieve a list of podcast episodes from DEV.

List DEVTO Reading List

Returns the articles in the authenticated user's reading list.

List Tags

Returns a list of tags with their names, background colors, and text colors.

List User All Articles

Tool to list all articles (both published and unpublished) for the authenticated user.

List User Articles

Tool to list published articles for the authenticated user.

List user's published articles

Returns a list of the authenticated user's published articles only.

List user's unpublished articles

Returns a list of the authenticated user's unpublished (draft) articles.

List Videos

Tool to retrieve a list of articles that contain videos.

Update Article

Update an existing article on DEV Community.

Update Listing

Updates an existing classified listing on DEV Community.

FRAMEWORKS

How to build DEV Community MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use DEV Community MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use DEV Community MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use DEV Community MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use DEV Community MCP with Claude Cowork

Codex logo

Codex

Use DEV Community MCP with Codex

OpenClaw logo

OpenClaw

Use DEV Community MCP with OpenClaw

Hermes logo

Hermes

Use DEV Community MCP with Hermes

CLI logo

CLI

Use DEV Community MCP with CLI

Google ADK logo

Google ADK

Use DEV Community MCP with Google ADK

LangChain logo

LangChain

Use DEV Community MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use DEV Community MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use DEV Community MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use DEV Community MCP with LlamaIndex

CrewAI logo

CrewAI

Use DEV Community MCP with CrewAI

FAQ

Frequently asked questions

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

Yes, you can. Pydantic AI 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 DEV Community tools.

Yes, absolutely. You can configure which DEV Community 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.

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 DEV Community data and credentials are handled as safely as possible.

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