# How to integrate Context7 MCP MCP with Pydantic AI ```json { "title": "How to integrate Context7 MCP MCP with Pydantic AI", "toolkit": "Context7 MCP", "toolkit_slug": "context7_mcp", "framework": "Pydantic AI", "framework_slug": "pydantic-ai", "url": "https://composio.dev/toolkits/context7_mcp/framework/pydantic-ai", "markdown_url": "https://composio.dev/toolkits/context7_mcp/framework/pydantic-ai.md", "updated_at": "2026-03-29T06:28:43.217Z" } ``` ## Introduction This guide walks you through connecting Context7 MCP to Pydantic AI using the Composio tool router. By the end, you'll have a working Context7 MCP agent that can get documentation for requests.get in python 3.11, show code example for async file read in node.js, explain the difference between map and filter in javascript through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Context7 MCP account through Composio's Context7 MCP MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Context7 MCP with - [ChatGPT](https://composio.dev/toolkits/context7_mcp/framework/chatgpt) - [OpenAI Agents SDK](https://composio.dev/toolkits/context7_mcp/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/context7_mcp/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/context7_mcp/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/context7_mcp/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/context7_mcp/framework/codex) - [Cursor](https://composio.dev/toolkits/context7_mcp/framework/cursor) - [VS Code](https://composio.dev/toolkits/context7_mcp/framework/vscode) - [OpenCode](https://composio.dev/toolkits/context7_mcp/framework/opencode) - [OpenClaw](https://composio.dev/toolkits/context7_mcp/framework/openclaw) - [Hermes](https://composio.dev/toolkits/context7_mcp/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/context7_mcp/framework/cli) - [Google ADK](https://composio.dev/toolkits/context7_mcp/framework/google-adk) - [LangChain](https://composio.dev/toolkits/context7_mcp/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/context7_mcp/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/context7_mcp/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/context7_mcp/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/context7_mcp/framework/crew-ai) ## 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 Context7 MCP - 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 Context7 MCP 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 Context7 MCP MCP server, and what's possible with it? The Context7 MCP MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Context7 MCP account. It provides structured and secure access so your agent can perform Context7 MCP operations on your behalf. ## Supported Tools None listed. ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Context7 MCP MCP server is an implementation of the Model Context Protocol that connects your AI agent to Context7 MCP. It provides structured and secure access so your agent can perform Context7 MCP operations on your behalf through a secure, permission-based interface. With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster. ## Step-by-step Guide ### 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 ### 1. Getting API Keys for OpenAI and Composio OpenAI API Key - Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) 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](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs). - Navigate to your API settings and generate a new API key. - Store this key securely as you'll need it for authentication. ### 2. Install dependencies Install the required libraries. What's happening: - composio connects your agent to external SaaS tools like Context7 MCP - pydantic-ai lets you create structured AI agents with tool support - python-dotenv loads your environment variables securely from a .env file ```bash pip install composio pydantic-ai python-dotenv ``` ### 3. Set up environment variables 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 ```bash COMPOSIO_API_KEY=your_composio_api_key_here USER_ID=your_user_id_here OPENAI_API_KEY=your_openai_api_key ``` ### 4. Import dependencies What's happening: - We load environment variables and import required modules - Composio manages connections to Context7 MCP - MCPServerStreamableHTTP connects to the Context7 MCP MCP server endpoint - Agent from Pydantic AI lets you define and run the AI assistant ```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() ``` ### 5. Create a Tool Router Session What's happening: - We're creating a Tool Router session that gives your agent access to Context7 MCP 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 ```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 Context7 MCP composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["context7_mcp"], ) url = session.mcp.url if not url: raise ValueError("Composio session did not return an MCP URL") ``` ### 6. Initialize the Pydantic AI Agent What's happening: - The MCP client connects to the Context7 MCP endpoint - The agent uses GPT-5 to interpret user commands and perform Context7 MCP operations - The instructions field defines the agent's role and behavior ```python # Attach the MCP server to a Pydantic AI Agent context7_mcp_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[context7_mcp_mcp], instructions=( "You are a Context7 MCP assistant. Use Context7 MCP tools to help users " "with their requests. Ask clarifying questions when needed." ), ) ``` ### 7. Build the chat interface What's happening: - The agent reads input from the terminal and streams its response - Context7 MCP API calls happen automatically under the hood - The model keeps conversation history to maintain context across turns ```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 Context7 MCP.\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() ``` ### 8. Run the application What's happening: - The asyncio loop launches the agent and keeps it running until you exit ```python if __name__ == "__main__": asyncio.run(main()) ``` ## Complete Code ```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 Context7 MCP composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["context7_mcp"], ) 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 context7_mcp_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[context7_mcp_mcp], instructions=( "You are a Context7 MCP assistant. Use Context7 MCP 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 Context7 MCP.\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 Context7 MCP through Composio's Tool Router. With this setup, your agent can perform real Context7 MCP 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 + Context7 MCP for workflow automation) This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations. ## How to build Context7 MCP MCP Agent with another framework - [ChatGPT](https://composio.dev/toolkits/context7_mcp/framework/chatgpt) - [OpenAI Agents SDK](https://composio.dev/toolkits/context7_mcp/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/context7_mcp/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/context7_mcp/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/context7_mcp/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/context7_mcp/framework/codex) - [Cursor](https://composio.dev/toolkits/context7_mcp/framework/cursor) - [VS Code](https://composio.dev/toolkits/context7_mcp/framework/vscode) - [OpenCode](https://composio.dev/toolkits/context7_mcp/framework/opencode) - [OpenClaw](https://composio.dev/toolkits/context7_mcp/framework/openclaw) - [Hermes](https://composio.dev/toolkits/context7_mcp/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/context7_mcp/framework/cli) - [Google ADK](https://composio.dev/toolkits/context7_mcp/framework/google-adk) - [LangChain](https://composio.dev/toolkits/context7_mcp/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/context7_mcp/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/context7_mcp/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/context7_mcp/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/context7_mcp/framework/crew-ai) ## Related Toolkits - [Google Sheets](https://composio.dev/toolkits/googlesheets) - Google Sheets is a cloud-based spreadsheet tool for real-time collaboration and data analysis. It lets teams work together from anywhere, updating information instantly. - [Supabase](https://composio.dev/toolkits/supabase) - Supabase is an open-source backend platform offering scalable Postgres databases, authentication, storage, and real-time APIs. It lets developers build modern apps without managing infrastructure. - [Composio](https://composio.dev/toolkits/composio) - Composio is an integration platform that connects AI agents with hundreds of business tools. It streamlines authentication and lets you trigger actions across services—no custom code needed. - [Notion](https://composio.dev/toolkits/notion) - Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place. - [Airtable](https://composio.dev/toolkits/airtable) - Airtable combines the flexibility of spreadsheets with the power of a database for easy project and data management. Teams use Airtable to organize, track, and collaborate with custom views and automations. - [Codeinterpreter](https://composio.dev/toolkits/codeinterpreter) - Codeinterpreter is a Python-based coding environment with built-in data analysis and visualization. It lets you instantly run scripts, plot results, and prototype solutions inside supported platforms. - [Asana](https://composio.dev/toolkits/asana) - Asana is a collaborative work management platform for teams to organize and track projects. It streamlines teamwork, boosts productivity, and keeps everyone aligned on goals. - [Google Tasks](https://composio.dev/toolkits/googletasks) - Google Tasks is a to-do list and task management tool integrated into Gmail and Google Calendar. It helps you organize, track, and complete tasks across your Google ecosystem. - [Linear](https://composio.dev/toolkits/linear) - Linear is a modern issue tracking and project planning tool for fast-moving teams. It helps streamline workflows, organize projects, and boost productivity. - [GitHub](https://composio.dev/toolkits/github) - GitHub is a code hosting platform for version control and collaborative software development. It streamlines project management, code review, and team workflows in one place. - [Composio search](https://composio.dev/toolkits/composio_search) - Composio search is a unified web search toolkit spanning travel, e-commerce, news, financial markets, images, and more. It lets you and your apps tap into up-to-date web data from a single, easy-to-integrate service. - [Jira](https://composio.dev/toolkits/jira) - Jira is Atlassian’s platform for bug tracking, issue tracking, and agile project management. It helps teams organize work, prioritize tasks, and deliver projects efficiently. - [Clickup](https://composio.dev/toolkits/clickup) - ClickUp is an all-in-one productivity platform for managing tasks, docs, goals, and team collaboration. It streamlines project workflows so teams can work smarter and stay organized in one place. - [Monday](https://composio.dev/toolkits/monday) - Monday.com is a customizable work management platform for project planning and collaboration. It helps teams organize tasks, automate workflows, and track progress in real time. - [Perplexityai](https://composio.dev/toolkits/perplexityai) - Perplexityai delivers natural, conversational AI models for generating human-like text. Instantly get context-aware, high-quality responses for chat, search, or complex workflows. - [Browser tool](https://composio.dev/toolkits/browser_tool) - Browser tool is a virtual browser integration that lets AI agents interact with the web programmatically. It enables automated browsing, scraping, and action-taking from any AI workflow. - [Ably](https://composio.dev/toolkits/ably) - Ably is a real-time messaging platform for live chat and data sync in modern apps. It offers global scale and rock-solid reliability for seamless, instant experiences. - [Abuselpdb](https://composio.dev/toolkits/abuselpdb) - Abuselpdb is a central database for reporting and checking IPs linked to malicious online activity. Use it to quickly identify and report suspicious or abusive IP addresses. - [Addressfinder](https://composio.dev/toolkits/addressfinder) - Addressfinder is a data quality platform for verifying addresses, emails, and phone numbers. It helps you ensure accurate customer and contact data every time. - [Agiled](https://composio.dev/toolkits/agiled) - Agiled is an all-in-one business management platform for CRM, projects, and finance. It helps you streamline workflows, consolidate client data, and manage business processes in one place. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Context7 MCP MCP? With a standalone Context7 MCP MCP server, the agents and LLMs can only access a fixed set of Context7 MCP tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Context7 MCP and many other apps based on the task at hand, all through a single MCP endpoint. ### Can I use Tool Router MCP with Pydantic AI? 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 Context7 MCP tools. ### Can I manage the permissions and scopes for Context7 MCP while using Tool Router? Yes, absolutely. You can configure which Context7 MCP 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 Context7 MCP data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)