# How to integrate Plain MCP with Autogen ```json { "title": "How to integrate Plain MCP with Autogen", "toolkit": "Plain", "toolkit_slug": "plain", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/plain/framework/autogen", "markdown_url": "https://composio.dev/toolkits/plain/framework/autogen.md", "updated_at": "2026-05-12T10:22:13.990Z" } ``` ## Introduction This guide walks you through connecting Plain to AutoGen 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 AutoGen 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: - Get and set up your OpenAI and Composio API keys - Install the required dependencies for Autogen and Composio - Initialize Composio and create a Tool Router session for Plain - Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams - Configure an Autogen AssistantAgent that can call Plain tools - Run a live chat loop where you ask the agent to perform Plain operations ## What is AutoGen? Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows. Key features include: - Multi-Agent Systems: Build collaborative agent workflows - MCP Workbench: Native support for Model Context Protocol tools - Streaming HTTP: Connect to external services through streamable HTTP - AssistantAgent: Pre-built agent class for tool-using assistants ## 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 agents and assistants directly to Plain. Instead of manually wiring Plain APIs, OAuth, and scopes yourself, you get a structured, tool-based interface that an LLM can call safely. 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 You will need: - A Composio API key - An OpenAI API key (used by Autogen's OpenAIChatCompletionClient) - A Plain account you can connect to Composio - Some basic familiarity with Autogen and Python async ### 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 Composio, Autogen extensions, and dotenv. What's happening: - composio connects your agent to Plain via MCP - autogen-agentchat provides the AssistantAgent class - autogen-ext-openai provides the OpenAI model client - autogen-ext-tools provides MCP workbench support ```bash pip install composio python-dotenv pip install autogen-agentchat autogen-ext-openai autogen-ext-tools ``` ### 3. Set up environment variables Create a .env file in your project folder. What's happening: - COMPOSIO_API_KEY is required to talk to Composio - OPENAI_API_KEY is used by Autogen's OpenAI client - USER_ID is how Composio identifies which user's Plain connections to use ```bash COMPOSIO_API_KEY=your-composio-api-key OPENAI_API_KEY=your-openai-api-key USER_ID=your-user-identifier@example.com ``` ### 4. Import dependencies and create Tool Router session What's happening: - load_dotenv() reads your .env file - Composio(api_key=...) initializes the SDK - create(...) creates a Tool Router session that exposes Plain tools - session.mcp.url is the MCP endpoint that Autogen will connect to ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from autogen_agentchat.agents import AssistantAgent from autogen_ext.models.openai import OpenAIChatCompletionClient from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams load_dotenv() async def main(): # Initialize Composio and create a Plain session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["plain"] ) url = session.mcp.url ``` ### 5. Configure MCP parameters for Autogen Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for. What's happening: - url points to the Tool Router MCP endpoint from Composio - timeout is the HTTP timeout for requests - sse_read_timeout controls how long to wait when streaming responses - terminate_on_close=True cleans up the MCP server process when the workbench is closed ```python # Configure MCP server parameters for Streamable HTTP server_params = StreamableHttpServerParams( url=url, timeout=30.0, sse_read_timeout=300.0, terminate_on_close=True, headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")} ) ``` ### 6. Create the model client and agent What's happening: - OpenAIChatCompletionClient wraps the OpenAI model for Autogen - McpWorkbench connects the agent to the MCP tools - AssistantAgent is configured with the Plain tools from the workbench ```python # Create model client model_client = OpenAIChatCompletionClient( model="gpt-5", api_key=os.getenv("OPENAI_API_KEY") ) # Use McpWorkbench as context manager async with McpWorkbench(server_params) as workbench: # Create Plain assistant agent with MCP tools agent = AssistantAgent( name="plain_assistant", description="An AI assistant that helps with Plain operations.", model_client=model_client, workbench=workbench, model_client_stream=True, max_tool_iterations=10 ) ``` ### 7. Run the interactive chat loop What's happening: - The script prompts you in a loop with You: - Autogen passes your input to the model, which decides which Plain tools to call via MCP - agent.run_stream(...) yields streaming messages as the agent thinks and calls tools - Typing exit, quit, or bye ends the loop ```python print("Chat started! Type 'exit' or 'quit' to end the conversation.\n") print("Ask any Plain related question or task to the agent.\n") # Conversation loop 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") # Run the agent with streaming try: response_text = "" async for message in agent.run_stream(task=user_input): if hasattr(message, "content") and message.content: response_text = message.content # Print the final response if response_text: print(f"Agent: {response_text}\n") else: print("Agent: I encountered an issue processing your request.\n") except Exception as e: print(f"Agent: Sorry, I encountered an error: {str(e)}\n") ``` ## Complete Code ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from autogen_agentchat.agents import AssistantAgent from autogen_ext.models.openai import OpenAIChatCompletionClient from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams load_dotenv() async def main(): # Initialize Composio and create a Plain session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["plain"] ) url = session.mcp.url # Configure MCP server parameters for Streamable HTTP server_params = StreamableHttpServerParams( url=url, timeout=30.0, sse_read_timeout=300.0, terminate_on_close=True, headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")} ) # Create model client model_client = OpenAIChatCompletionClient( model="gpt-5", api_key=os.getenv("OPENAI_API_KEY") ) # Use McpWorkbench as context manager async with McpWorkbench(server_params) as workbench: # Create Plain assistant agent with MCP tools agent = AssistantAgent( name="plain_assistant", description="An AI assistant that helps with Plain operations.", model_client=model_client, workbench=workbench, model_client_stream=True, max_tool_iterations=10 ) print("Chat started! Type 'exit' or 'quit' to end the conversation.\n") print("Ask any Plain related question or task to the agent.\n") # Conversation loop 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") # Run the agent with streaming try: response_text = "" async for message in agent.run_stream(task=user_input): if hasattr(message, 'content') and message.content: response_text = message.content # Print the final response if response_text: print(f"Agent: {response_text}\n") else: print("Agent: I encountered an issue processing your request.\n") except Exception as e: print(f"Agent: Sorry, I encountered an error: {str(e)}\n") if __name__ == "__main__": asyncio.run(main()) ``` ## Conclusion You now have an Autogen assistant wired into Plain through Composio's Tool Router and MCP. From here you can: - Add more toolkits to the toolkits list, for example notion or hubspot - Refine the agent description to point it at specific workflows - Wrap this script behind a UI, Slack bot, or internal tool Once the pattern is clear for Plain, you can reuse the same structure for other MCP-enabled apps with minimal code changes. ## 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 Autogen? Yes, you can. Autogen 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)