# How to integrate Jotform MCP with Autogen ```json { "title": "How to integrate Jotform MCP with Autogen", "toolkit": "Jotform", "toolkit_slug": "jotform", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/jotform/framework/autogen", "markdown_url": "https://composio.dev/toolkits/jotform/framework/autogen.md", "updated_at": "2026-05-12T10:16:31.933Z" } ``` ## Introduction This guide walks you through connecting Jotform to AutoGen using the Composio tool router. By the end, you'll have a working Jotform agent that can list all your active jotform forms, show recent changes to your account, get details of your current subscription plan through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Jotform account through Composio's Jotform MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Jotform with - [OpenAI Agents SDK](https://composio.dev/toolkits/jotform/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/jotform/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/jotform/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/jotform/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/jotform/framework/codex) - [OpenClaw](https://composio.dev/toolkits/jotform/framework/openclaw) - [Hermes](https://composio.dev/toolkits/jotform/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/jotform/framework/cli) - [Google ADK](https://composio.dev/toolkits/jotform/framework/google-adk) - [LangChain](https://composio.dev/toolkits/jotform/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/jotform/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/jotform/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/jotform/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/jotform/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 Jotform - Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams - Configure an Autogen AssistantAgent that can call Jotform tools - Run a live chat loop where you ask the agent to perform Jotform 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 Jotform MCP server, and what's possible with it? The Jotform MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Jotform account. It provides structured and secure access to your forms, folders, and user data, so your agent can perform actions like retrieving form lists, checking account usage, accessing folders, and auditing user activity on your behalf. - Form discovery and listing: Instantly have your agent fetch and enumerate all forms you've created in your Jotform account. - User account insights: Retrieve up-to-date details about your Jotform user profile, account type, and current usage limits automatically. - Folder management and organization: Let your agent pull a list of your user folders, making it easy to reference, organize, or navigate different form projects. - Audit and activity history retrieval: Fetch a comprehensive log of your account activity to review recent actions, filter by activity type, or monitor changes. - Account settings access: Seamlessly access and review your Jotform user settings for troubleshooting or configuration checks via your AI agent. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `JOTFORM_CLONE_FORM` | Clone Form | Tool to clone a single form in Jotform. Creates a complete copy of the form with all its questions and settings. Use when you need to duplicate an existing form. | | `JOTFORM_CREATE_LABEL` | Create Label | Tool to create a new label for organizing forms in Jotform. Use when you need to categorize or group forms with a named label. | | `JOTFORM_DELETE_LABEL` | Delete Label | Tool to delete a label along with all its sublabels. Use when you need to remove a label from the account. | | `JOTFORM_GET_LABEL` | Get Label | Tool to retrieve details of a label by its ID, including name and color. Use when you need to fetch information about a specific label. | | `JOTFORM_GET_LABEL_RESOURCES` | Get Label Resources | Tool to get a list of assets (forms) in a label and their associated information. Use when you need to retrieve forms organized under a specific label. | | `JOTFORM_GET_SYSTEM_PLAN` | Get System Plan | Tool to retrieve details of a specific system plan. Use when you need to check limits and pricing of a plan. | | `JOTFORM_GET_USER_DETAILS` | Get User Details | Tool to retrieve details of the authenticated user, including account and usage info. Use after confirming valid API key. | | `JOTFORM_GET_USER_FOLDERS` | Get User Folders | Tool to retrieve a list of labels (folders replacement) for the authenticated user. Uses the GET /user/labels endpoint per Jotform's migration from folders to labels. | | `JOTFORM_GET_USER_FORMS` | Get User Forms | Tool to retrieve a list of forms created by the authenticated user. Use after setting up API key authentication. | | `JOTFORM_GET_USER_HISTORY` | Get User History | Tool to fetch user activity history records. Use when auditing or filtering user actions by type or date. | | `JOTFORM_GET_USER_REPORTS` | Get User Reports | Tool to retrieve list of report URLs for all forms in the account. Includes Excel, CSV, printable charts, and embeddable HTML tables. | | `JOTFORM_GET_USER_SETTINGS` | Get User Settings | Tool to retrieve the settings of the authenticated user. Use after confirming a valid API key. | | `JOTFORM_GET_USER_SETTINGS_BY_KEY` | Get User Setting By Key | Tool to retrieve a specific user setting by key. Use when you need a single setting value like email, timezone, language, or website. | | `JOTFORM_GET_USER_SUBMISSIONS` | Get User Submissions | Tool to retrieve all submissions for all forms on the account. The answers dictionary contains submission data with question IDs as keys. Use when you need to access submission data across multiple forms. | | `JOTFORM_GET_USER_USAGE` | Get User Usage | Tool to retrieve monthly usage statistics for the authenticated user. Use to check form submissions, payment forms, SSL submissions, and storage used. | | `JOTFORM_REMOVE_LABEL_RESOURCES` | Remove Resources from Label | Tool to remove specified resources (forms) from a label by their IDs and types. Use when you need to unassign forms from a specific label. | | `JOTFORM_UPDATE_LABEL` | Update Label | Tool to update an existing label with new name or color settings. Use when you need to modify label properties. | | `JOTFORM_UPDATE_USER_SETTINGS` | Update User Settings | Tool to update user's settings like time zone, language, email, and website. Use when you need to modify user account settings. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Jotform MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Jotform. Instead of manually wiring Jotform 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 Jotform 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 Jotform 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 Jotform 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 Jotform 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 Jotform session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["jotform"] ) 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 Jotform 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 Jotform assistant agent with MCP tools agent = AssistantAgent( name="jotform_assistant", description="An AI assistant that helps with Jotform 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 Jotform 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 Jotform 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 Jotform session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["jotform"] ) 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 Jotform assistant agent with MCP tools agent = AssistantAgent( name="jotform_assistant", description="An AI assistant that helps with Jotform 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 Jotform 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 Jotform 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 Jotform, you can reuse the same structure for other MCP-enabled apps with minimal code changes. ## How to build Jotform MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/jotform/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/jotform/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/jotform/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/jotform/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/jotform/framework/codex) - [OpenClaw](https://composio.dev/toolkits/jotform/framework/openclaw) - [Hermes](https://composio.dev/toolkits/jotform/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/jotform/framework/cli) - [Google ADK](https://composio.dev/toolkits/jotform/framework/google-adk) - [LangChain](https://composio.dev/toolkits/jotform/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/jotform/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/jotform/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/jotform/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/jotform/framework/crew-ai) ## Related Toolkits - [Excel](https://composio.dev/toolkits/excel) - Microsoft Excel is a robust spreadsheet application for organizing, analyzing, and visualizing data. It's the go-to tool for calculations, reporting, and flexible data management. - [21risk](https://composio.dev/toolkits/_21risk) - 21RISK is a web app built for easy checklist, audit, and compliance management. It streamlines risk processes so teams can focus on what matters. - [Abstract](https://composio.dev/toolkits/abstract) - Abstract provides a suite of APIs for automating data validation and enrichment tasks. It helps developers streamline workflows and ensure data quality with minimal effort. - [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. - [Agenty](https://composio.dev/toolkits/agenty) - Agenty is a web scraping and automation platform for extracting data and automating browser tasks—no coding needed. 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It helps organizations meet GDPR, CCPA, and HIPAA data privacy compliance requirements. - [Api ninjas](https://composio.dev/toolkits/api_ninjas) - Api ninjas offers 120+ public APIs spanning categories like weather, finance, sports, and more. Developers use it to supercharge apps with real-time data and actionable endpoints. - [Api sports](https://composio.dev/toolkits/api_sports) - Api sports is a comprehensive sports data platform covering 2,000+ competitions with live scores and 15+ years of stats. Instantly access up-to-date sports information for analysis, apps, or chatbots. - [Apify](https://composio.dev/toolkits/apify) - Apify is a cloud platform for building, deploying, and managing web scraping and automation tools called Actors. It lets you automate data extraction and workflow tasks at scale—no infrastructure headaches. - [Autom](https://composio.dev/toolkits/autom) - Autom is a lightning-fast search engine results data platform for Google, Bing, and Brave. Developers use it to access fresh, low-latency SERP data on demand. - [Beaconchain](https://composio.dev/toolkits/beaconchain) - Beaconchain is a real-time analytics platform for Ethereum 2.0's Beacon Chain. It provides detailed insights into validators, blocks, and overall network performance. - [Big data cloud](https://composio.dev/toolkits/big_data_cloud) - BigDataCloud provides APIs for geolocation, reverse geocoding, and address validation. Instantly access reliable location intelligence to enhance your applications and workflows. - [Bigpicture io](https://composio.dev/toolkits/bigpicture_io) - BigPicture.io offers APIs for accessing detailed company and profile data. Instantly enrich your applications with up-to-date insights on 20M+ businesses. - [Bitquery](https://composio.dev/toolkits/bitquery) - Bitquery is a blockchain data platform offering indexed, real-time, and historical data from 40+ blockchains via GraphQL APIs. Get unified, reliable access to complex on-chain data for analytics, trading, and research. - [Brightdata](https://composio.dev/toolkits/brightdata) - Brightdata is a leading web data platform offering advanced scraping, SERP APIs, and anti-bot tools. It lets you collect public web data at scale, bypassing blocks and friction. - [Builtwith](https://composio.dev/toolkits/builtwith) - BuiltWith is a web technology profiler that uncovers the technologies powering any website. Gain actionable insights into analytics, hosting, and content management stacks for smarter research and lead generation. - [Byteforms](https://composio.dev/toolkits/byteforms) - Byteforms is an all-in-one platform for creating forms, managing submissions, and integrating data. It streamlines workflows by centralizing form data collection and automation. - [Cabinpanda](https://composio.dev/toolkits/cabinpanda) - Cabinpanda is a data collection platform for building and managing online forms. It helps streamline how you gather, organize, and analyze responses. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Jotform MCP? With a standalone Jotform MCP server, the agents and LLMs can only access a fixed set of Jotform tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Jotform 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 Jotform tools. ### Can I manage the permissions and scopes for Jotform while using Tool Router? Yes, absolutely. You can configure which Jotform 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 Jotform data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)