# How to integrate Process street MCP with Autogen ```json { "title": "How to integrate Process street MCP with Autogen", "toolkit": "Process street", "toolkit_slug": "process_street", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/process_street/framework/autogen", "markdown_url": "https://composio.dev/toolkits/process_street/framework/autogen.md", "updated_at": "2026-05-06T08:24:34.913Z" } ``` ## Introduction This guide walks you through connecting Process street to AutoGen using the Composio tool router. By the end, you'll have a working Process street agent that can start a new onboarding checklist for a new hire, find all workflow runs due this week, list all available sop templates in your account through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Process street account through Composio's Process street MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Process street with - [OpenAI Agents SDK](https://composio.dev/toolkits/process_street/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/process_street/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/process_street/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/process_street/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/process_street/framework/codex) - [OpenClaw](https://composio.dev/toolkits/process_street/framework/openclaw) - [Hermes](https://composio.dev/toolkits/process_street/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/process_street/framework/cli) - [Google ADK](https://composio.dev/toolkits/process_street/framework/google-adk) - [LangChain](https://composio.dev/toolkits/process_street/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/process_street/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/process_street/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/process_street/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/process_street/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 Process street - Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams - Configure an Autogen AssistantAgent that can call Process street tools - Run a live chat loop where you ask the agent to perform Process street 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 Process street MCP server, and what's possible with it? The Process street MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Process Street account. It provides structured and secure access to your workflows, so your agent can perform actions like listing workflows, launching new workflow runs, searching data sets, completing processes, and recovering deleted runs on your behalf. - Automated workflow management: Let your agent retrieve all available workflows and help you navigate or select the right process for any task. - Instant workflow run creation: Have your AI assistant spin up new workflow runs from templates, name them, set due dates, and generate share links as needed. - Targeted data set search: Ask your agent to search and filter rows within Process Street data sets to quickly find matching entries based on your criteria. - Workflow run completion: Direct your agent to mark entire workflow runs as completed, ensuring processes are finished and statuses are up to date. - One-click workflow run recovery: Quickly restore accidentally deleted workflow runs, letting your agent correct mistakes and recover lost progress with ease. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `PROCESS_STREET_COMPLETE_WORKFLOW_RUN` | Complete a workflow run | This tool marks an entire workflow run as completed in process street. it updates the workflow run's status to 'completed', distinguishing it from process street complete task which completes individual tasks. | | `PROCESS_STREET_CREATE_WORKFLOW_RUN` | Create Workflow Run | This tool creates a new workflow run from a specified workflow template. it is one of the most fundamental operations in process street, allowing users to initiate a new instance of a workflow. the tool requires a workflow template id and optionally allows setting a custom name, due date, and whether to enable a share link. | | `PROCESS_STREET_FIND_DATA_SET_ROWS` | Find Data Set Rows | This tool allows you to search for records within a data set based on form fields. it's useful for retrieving specific records from a data set when you need to find matching entries based on certain criteria. | | `PROCESS_STREET_LIST_WORKFLOWS` | List Workflows | This tool retrieves a list of all workflows available in the process street account. it is a fundamental action that allows users to view and access all their workflows, which is essential for other operations that require workflow ids. this action is important because it provides the foundation for other actions that require workflow ids as input parameters, such as creating workflow runs or managing workflow-specific tasks, thereby enabling better workflow management and automation. | | `PROCESS_STREET_UNDELETE_WORKFLOW_RUN` | Undelete Workflow Run | This tool allows you to restore a previously deleted workflow run in process street. it uses the put /v1.1/workflow-runs/{workflowrunid}/undelete endpoint to recover a workflow run within a valid recovery period. it complements the existing process street delete workflow run action by providing a data recovery option to correct deletion mistakes. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Process street MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Process street. Instead of manually wiring Process street 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 Process street 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 Process street 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 Process street 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 Process street 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 Process street session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["process_street"] ) 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 Process street 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 Process street assistant agent with MCP tools agent = AssistantAgent( name="process_street_assistant", description="An AI assistant that helps with Process street 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 Process street 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 Process street 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 Process street session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["process_street"] ) 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 Process street assistant agent with MCP tools agent = AssistantAgent( name="process_street_assistant", description="An AI assistant that helps with Process street 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 Process street 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 Process street 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 Process street, you can reuse the same structure for other MCP-enabled apps with minimal code changes. ## How to build Process street MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/process_street/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/process_street/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/process_street/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/process_street/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/process_street/framework/codex) - [OpenClaw](https://composio.dev/toolkits/process_street/framework/openclaw) - [Hermes](https://composio.dev/toolkits/process_street/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/process_street/framework/cli) - [Google ADK](https://composio.dev/toolkits/process_street/framework/google-adk) - [LangChain](https://composio.dev/toolkits/process_street/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/process_street/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/process_street/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/process_street/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/process_street/framework/crew-ai) ## Related Toolkits - [Apilio](https://composio.dev/toolkits/apilio) - Apilio is a home automation platform that lets you connect and control smart devices from different brands. It helps you build flexible automations with complex conditions, schedules, and integrations. - [Basin](https://composio.dev/toolkits/basin) - Basin is a no-code form backend for quickly setting up reliable contact forms. It lets you collect and manage form submissions without writing any server-side code. - [Bouncer](https://composio.dev/toolkits/bouncer) - Bouncer is an email validation platform that verifies the authenticity of email addresses in real-time and batch. It helps boost deliverability and reduce bounce rates for your communications. - [Conveyor](https://composio.dev/toolkits/conveyor) - Conveyor is a platform that automates security reviews with a Trust Center and AI-driven questionnaire automation. It streamlines compliance and vendor security processes for faster, hassle-free reviews. - [Crowdin](https://composio.dev/toolkits/crowdin) - Crowdin is a localization management platform that streamlines translation workflows and collaboration. 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It streamlines repetitive processes so your business runs smoother, faster, and with fewer manual steps. - [Maintainx](https://composio.dev/toolkits/maintainx) - Maintainx is a cloud-based CMMS for centralizing maintenance data, communication, and workflows. It helps organizations streamline maintenance operations and improve team coordination. - [Make](https://composio.dev/toolkits/make) - Make is an automation platform that connects your favorite apps and services. Build powerful, custom workflows without writing code. - [Ntfy](https://composio.dev/toolkits/ntfy) - Ntfy is a notification service to send push messages to phones or desktops. Instantly deliver alerts and updates to users, devices, or teams. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Process street MCP? With a standalone Process street MCP server, the agents and LLMs can only access a fixed set of Process street tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Process street 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 Process street tools. ### Can I manage the permissions and scopes for Process street while using Tool Router? Yes, absolutely. You can configure which Process street 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 Process street data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) ยท [Composio docs](https://docs.composio.dev/llms.txt)