# How to integrate Plain MCP with Pydantic AI ```json { "title": "How to integrate Plain MCP with Pydantic AI", "toolkit": "Plain", "toolkit_slug": "plain", "framework": "Pydantic AI", "framework_slug": "pydantic-ai", "url": "https://composio.dev/toolkits/plain/framework/pydantic-ai", "markdown_url": "https://composio.dev/toolkits/plain/framework/pydantic-ai.md", "updated_at": "2026-05-12T10:22:13.990Z" } ``` ## Introduction This guide walks you through connecting Plain to Pydantic AI using the Composio tool router. By the end, you'll have a working Plain agent that can add a customer to the enterprise group, fetch company details for acme corp, list all issues linked to this customer through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Plain account through Composio's Plain MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Plain with - [OpenAI Agents SDK](https://composio.dev/toolkits/plain/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/plain/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/plain/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/plain/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/plain/framework/codex) - [OpenClaw](https://composio.dev/toolkits/plain/framework/openclaw) - [Hermes](https://composio.dev/toolkits/plain/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/plain/framework/cli) - [Google ADK](https://composio.dev/toolkits/plain/framework/google-adk) - [LangChain](https://composio.dev/toolkits/plain/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/plain/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/plain/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/plain/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/plain/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 Plain - 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 Plain 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 Plain MCP server, and what's possible with it? The Plain MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Plain account. It provides structured and secure access to your B2B support workspace, so your agent can perform actions like managing customers, creating support threads, fetching company details, handling issues, and organizing customer groups on your behalf. - Customer management and onboarding: Automatically create new customer records, fetch customer information by email or ID, and add customers to specific support groups for better organization. - Support thread creation: Let your agent create new support threads tied to customers, making it easy to kick off or escalate conversations without manual intervention. - Issue tracking and retrieval: Fetch all external issue links associated with a customer, helping your team stay on top of ongoing problems and resolutions. - Company and tier information access: Retrieve detailed company profiles and tier metadata, including contract value, owner details, and more, to personalize support interactions. - User and customer cleanup: Safely delete customers or users from the system when offboarding or data hygiene is needed, all through agent-driven actions. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `PLAIN_ADD_CUSTOMER_TO_GROUP` | Add Customer To Group | Tool to add a customer to one or more customer groups. Use when you have a customer and groups ready. | | `PLAIN_CREATE_CUSTOMER_GROUP` | Create Customer Group | Creates a new customer group in Plain for organizing and segmenting customers. Customer groups allow you to categorize customers (e.g., by pricing tier, feature access, or support level) and manage them more effectively in your support workflow. Each group has a unique key, display name, and visual color for easy identification. Use this when you need to create a new customer segment for organization or filtering purposes. | | `PLAIN_CREATE_THREAD` | Create Thread | Tool to create a new thread. Use after obtaining valid customer identifier. | | `PLAIN_DELETE_CUSTOMER` | Delete Customer | Tool to delete a customer from the system. Use when you need to remove a customer by their ID. | | `PLAIN_DELETE_USER` | Delete User | Tool to delete a user from the system. Use when you need to remove a user by their ID after confirming existence. | | `PLAIN_FETCH_COMPANY` | Fetch Company | Tool to fetch company details by ID. Use when you need the full profile of a company, including name, domain, contract value, owner info, and timestamps. | | `PLAIN_FETCH_ISSUES` | Fetch Issues | Fetches external issue tracker links (Jira, Linear, GitHub, etc.) associated with a customer's threads. Returns a flattened list of all issue links across the customer's threads, including the thread context for each issue. Useful for getting a complete view of all external issues related to a customer. With defaults, returns up to threadFirst×linkFirst (2,500) total issue links; results are truncated if limits are exceeded, so reduce threadFirst or linkFirst for large datasets. | | `PLAIN_FETCH_TIER` | Fetch Tier | Tool to fetch a tier by its ID. Use when you have a tier ID and need its metadata before proceeding. Example: "Fetch tier with ID tier_123". | | `PLAIN_GET_CUSTOMER_BY_EMAIL` | Get Customer By Email | Fetch customer details by email address. Returns customer information if found, or null if no customer exists with that email. | | `PLAIN_GET_CUSTOMER_BY_ID` | Get Customer By ID | Tool to retrieve details of a specific customer by their unique ID. Use after obtaining the customer's ID to fetch their complete record. | | `PLAIN_GET_CUSTOMERS` | Get Customers | Tool to fetch a list of customers. Use when retrieving multiple customer records with pagination, filtering, or sorting. | | `PLAIN_GET_THREAD_BY_ID` | Get Thread By ID | Fetches comprehensive details of a specific thread by ID, including customer info, status, priority, labels, and assignments. Returns null if thread not found. | | `PLAIN_GET_USER_BY_ID` | Get User By ID | Fetch workspace user/team member by ID. Returns detailed information about a workspace team member including their name, email, status, and avatar. Note: This fetches workspace users (team members), not customers. Use GET_CUSTOMER_BY_ID for customer data. | | `PLAIN_LIST_CUSTOMER_GROUPS` | List Customer Groups | Tool to list all customer groups. Use when you need to retrieve group metadata with optional pagination or filters. | | `PLAIN_LIST_TIERS` | List Tiers | Tool to retrieve a list of tiers with pagination. Use when you need to browse available tiers after determining pagination cursors. Example: 'List tiers with first=25'. | | `PLAIN_QUERY_THREADS` | List Threads | Tool to retrieve a paginated list of threads. Use when you need to list threads with optional status filtering. | | `PLAIN_REMOVE_CUSTOMER_FROM_GROUP` | Remove Customer From Group | Removes a customer from one or more customer groups in Plain. Use this action to revoke customer group memberships. The customer must be a member of the specified group(s) - attempting to remove a customer from a group they're not in will result in an error. Groups can be identified by either their Plain internal ID (customerGroupId) or their unique key (customerGroupKey). Common use cases: - Downgrade customer tier (e.g., remove from premium_tier group) - Remove customer from beta access groups - Clean up group memberships after customer status changes | | `PLAIN_RUN_GRAPHQL_QUERY` | Run GraphQL Query | Execute any GraphQL query or mutation against Plain API. Use when no specific action exists or for complex operations like thread timelines, advanced filtering, and custom data retrieval. Supports queries, mutations, fragments, and variables. | | `PLAIN_SEND_MESSAGE` | Send Message | Tool to send a new message within a thread. Use after identifying the thread and preparing message content. | | `PLAIN_UPDATE_COMPANY` | Update Company | Upserts (creates or updates) a company in Plain. Provide either companyId (for updating an existing company by ID) or companyDomainName (for upserting by domain). Use this to create new companies, update existing company details (name, domain, contract value), or assign account owners. | | `PLAIN_UPDATE_THREAD` | Update Thread | Tool to update a thread's title. Use when renaming a thread after confirming its ID. | | `PLAIN_UPSERT_CUSTOMER` | Upsert Customer | Tool to upsert (create or update) a customer. Use when syncing or ensuring a customer record exists before subsequent actions. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Plain MCP server is an implementation of the Model Context Protocol that connects your AI agent to Plain. It provides structured and secure access so your agent can perform Plain 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 Plain - 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 Plain - MCPServerStreamableHTTP connects to the Plain 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 Plain 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 Plain composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["plain"], ) 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 Plain endpoint - The agent uses GPT-5 to interpret user commands and perform Plain operations - The instructions field defines the agent's role and behavior ```python # Attach the MCP server to a Pydantic AI Agent plain_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[plain_mcp], instructions=( "You are a Plain assistant. Use Plain 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 - Plain 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 Plain.\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 Plain composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["plain"], ) 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 plain_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[plain_mcp], instructions=( "You are a Plain assistant. Use Plain 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 Plain.\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 Plain through Composio's Tool Router. With this setup, your agent can perform real Plain 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 + Plain 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 Plain MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/plain/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/plain/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/plain/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/plain/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/plain/framework/codex) - [OpenClaw](https://composio.dev/toolkits/plain/framework/openclaw) - [Hermes](https://composio.dev/toolkits/plain/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/plain/framework/cli) - [Google ADK](https://composio.dev/toolkits/plain/framework/google-adk) - [LangChain](https://composio.dev/toolkits/plain/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/plain/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/plain/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/plain/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/plain/framework/crew-ai) ## Related Toolkits - [Aeroleads](https://composio.dev/toolkits/aeroleads) - Aeroleads is a B2B lead generation platform for finding business emails and phone numbers. Grow your sales pipeline faster with powerful prospecting tools. - [Autobound](https://composio.dev/toolkits/autobound) - Autobound is an AI-powered sales engagement platform that crafts hyper-personalized outreach and insights. It helps sales teams boost response rates and close more deals through tailored content and recommendations. - [Better proposals](https://composio.dev/toolkits/better_proposals) - Better Proposals is a web-based tool for crafting and sending professional proposals. It helps teams impress clients and close deals faster with slick, easy-to-use templates. - [Bidsketch](https://composio.dev/toolkits/bidsketch) - Bidsketch is a proposal software that helps businesses create professional proposals quickly and efficiently. It streamlines the proposal process, saving time while boosting client win rates. - [Bolna](https://composio.dev/toolkits/bolna) - Bolna is an AI platform for building conversational voice agents. It helps businesses automate support and streamline interactions through natural, voice-powered conversations. - [Botsonic](https://composio.dev/toolkits/botsonic) - Botsonic is a no-code AI chatbot builder for easily creating and deploying chatbots to your website. It empowers businesses to offer conversational experiences without writing code. - [Botstar](https://composio.dev/toolkits/botstar) - BotStar is a comprehensive chatbot platform for designing, developing, and training chatbots visually on Messenger and websites. It helps businesses automate conversations and customer interactions without coding. - [Callerapi](https://composio.dev/toolkits/callerapi) - CallerAPI is a white-label caller identification platform for branded caller ID and fraud prevention. It helps businesses boost customer trust while stopping spam, fraud, and robocalls. - [Callingly](https://composio.dev/toolkits/callingly) - Callingly is a lead response management platform that automates immediate call and text follow-ups with new leads. It helps sales teams boost response speed and close more deals by connecting seamlessly with CRMs and lead sources. - [Callpage](https://composio.dev/toolkits/callpage) - Callpage is a lead capture platform that lets businesses instantly connect with website visitors via callback. It boosts lead generation and increases your sales conversion rates. - [Clearout](https://composio.dev/toolkits/clearout) - Clearout is an AI-powered service for verifying, finding, and enriching email addresses. It boosts deliverability and helps you discover high-quality leads effortlessly. - [Clientary](https://composio.dev/toolkits/clientary) - Clientary is a platform for managing clients, invoices, projects, proposals, and more. It streamlines client work and saves you serious admin time. - [Convolo ai](https://composio.dev/toolkits/convolo_ai) - Convolo ai is an AI-powered communications platform for sales teams. It accelerates lead response and improves conversion rates by automating calls and integrating workflows. - [Delighted](https://composio.dev/toolkits/delighted) - Delighted is a customer feedback platform based on the Net Promoter System®. It helps you quickly gather, track, and act on customer sentiment. - [Emelia](https://composio.dev/toolkits/emelia) - Emelia is an all-in-one B2B prospecting platform for cold-email, LinkedIn outreach, and prospect research. It streamlines outbound campaigns so you can find, engage, and warm up leads faster. - [Findymail](https://composio.dev/toolkits/findymail) - Findymail is a B2B data provider offering verified email and phone contacts for sales prospecting. Enhance outreach with automated exports, email verification, and CRM enrichment. - [Freshdesk](https://composio.dev/toolkits/freshdesk) - Freshdesk is customer support software with ticketing and automation tools. It helps teams streamline helpdesk operations for faster, better customer support. - [Fullenrich](https://composio.dev/toolkits/fullenrich) - FullEnrich is a B2B contact enrichment platform that aggregates emails and phone numbers from 15+ data vendors. Instantly find and verify lead contact data to boost your outreach. - [Gatherup](https://composio.dev/toolkits/gatherup) - GatherUp is a customer feedback and online review management platform. It helps businesses boost their reputation by streamlining how they collect and manage customer feedback. - [Getprospect](https://composio.dev/toolkits/getprospect) - Getprospect is a business email discovery tool with LinkedIn integration. Use it to quickly find and verify professional email addresses. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Plain MCP? With a standalone Plain MCP server, the agents and LLMs can only access a fixed set of Plain tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Plain 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 Plain tools. ### Can I manage the permissions and scopes for Plain while using Tool Router? Yes, absolutely. You can configure which Plain 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 Plain data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)