# How to integrate Zoominfo MCP with Autogen ```json { "title": "How to integrate Zoominfo MCP with Autogen", "toolkit": "Zoominfo", "toolkit_slug": "zoominfo", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/zoominfo/framework/autogen", "markdown_url": "https://composio.dev/toolkits/zoominfo/framework/autogen.md", "updated_at": "2026-05-06T08:35:12.735Z" } ``` ## Introduction This guide walks you through connecting Zoominfo to AutoGen using the Composio tool router. By the end, you'll have a working Zoominfo agent that can find companies in new york with over 500 employees, enrich this contact with latest job title, list recent news about target accounts through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Zoominfo account through Composio's Zoominfo MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Zoominfo with - [OpenAI Agents SDK](https://composio.dev/toolkits/zoominfo/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/zoominfo/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/zoominfo/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/zoominfo/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/zoominfo/framework/codex) - [OpenClaw](https://composio.dev/toolkits/zoominfo/framework/openclaw) - [Hermes](https://composio.dev/toolkits/zoominfo/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/zoominfo/framework/cli) - [Google ADK](https://composio.dev/toolkits/zoominfo/framework/google-adk) - [LangChain](https://composio.dev/toolkits/zoominfo/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/zoominfo/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/zoominfo/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/zoominfo/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/zoominfo/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 Zoominfo - Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams - Configure an Autogen AssistantAgent that can call Zoominfo tools - Run a live chat loop where you ask the agent to perform Zoominfo 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 Zoominfo MCP server, and what's possible with it? The Zoominfo MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Zoominfo account. It provides structured and secure access to rich B2B sales intelligence, so your agent can search companies, enrich contact and company data, analyze intent signals, and surface actionable go-to-market insights for you. - Company and contact data enrichment: Instantly have your agent pull detailed profiles, firmographics, and contact information for any business or person of interest. - Smart company and contact search: Let your agent find the right leads by searching Zoominfo's vast database using criteria like location, industry, and role. - Intent signal analysis: Enable your agent to analyze buying intent signals and help prioritize outreach based on real-time market activity. - Technology and news enrichment: Ask your agent to uncover what technologies a company uses or find the latest news and scoops about prospects and clients. - Location-based prospecting: Have your agent filter and enrich location details to support precise territory planning and targeted campaigns. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `ZOOMINFO_ENRICH_COMPANY` | Company Enrich | Company enrich | | `ZOOMINFO_ENRICH_CONTACT` | Contact Enrich | Contact enrich | | `ZOOMINFO_ENRICH_INTENT` | Intent Enrich | Intent enrich | | `ZOOMINFO_ENRICH_LOCATION` | Location Enrich | Location enrich | | `ZOOMINFO_ENRICH_NEWS` | News Enrich | News enrich | | `ZOOMINFO_ENRICH_SCOOP` | Scoop Enrich | Scoop enrich | | `ZOOMINFO_ENRICH_TECHNOLOGY` | Technology Enrich | Technology enrich | | `ZOOMINFO_SEARCH_COMPANY` | Company Search | Returns a list of companies from zoominfo's data which meet the specified search criteria. | | `ZOOMINFO_SEARCH_COMPANY_INPUT` | Company Search Inputs | Returns a list of fields you can use as input for the company search action. | | `ZOOMINFO_SEARCH_CONTACT` | Contact Search | Returns a list of contacts from zoominfo's data that meet the specified search criteria. | | `ZOOMINFO_SEARCH_CONTACT_INPUT` | Contact Search Inputs | Returns a list of fields you can use as input for the contact search action. | | `ZOOMINFO_SEARCH_INTENT` | Intent Search | Use this endpoint to search for companies and recommended contacts based on intent data. use input values to return the desired output fields in the response. for charging purposes, each intent signal returned is counted as a record. | | `ZOOMINFO_SEARCH_INTENT_INPUT` | Intent Search Inputs | Returns a list of fields you can use as input for the intent action. | | `ZOOMINFO_SEARCH_NEWS` | News Search | Returns a list of news articles from zoominfo's data which meet the specified search criteria. all inputs are optional, but you must use at least one input parameter to generate a successful response. | | `ZOOMINFO_SEARCH_NEWS_INPUT` | News Search Inputs | Returns a list of fields you can use as input for the news search endpoint. | | `ZOOMINFO_SEARCH_SCOOP` | Scoop Search | Returns a list of scoops from zoominfo's data which meet the specified search criteria. | | `ZOOMINFO_SEARCH_SCOOP_INPUT` | Scoop Search Inputs | Returns a list of fields you can use as input for the scoop search action. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Zoominfo MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Zoominfo. Instead of manually wiring Zoominfo 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 Zoominfo 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 Zoominfo 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 Zoominfo 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 Zoominfo 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 Zoominfo session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["zoominfo"] ) 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 Zoominfo 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 Zoominfo assistant agent with MCP tools agent = AssistantAgent( name="zoominfo_assistant", description="An AI assistant that helps with Zoominfo 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 Zoominfo 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 Zoominfo 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 Zoominfo session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["zoominfo"] ) 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 Zoominfo assistant agent with MCP tools agent = AssistantAgent( name="zoominfo_assistant", description="An AI assistant that helps with Zoominfo 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 Zoominfo 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 Zoominfo 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 Zoominfo, you can reuse the same structure for other MCP-enabled apps with minimal code changes. ## How to build Zoominfo MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/zoominfo/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/zoominfo/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/zoominfo/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/zoominfo/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/zoominfo/framework/codex) - [OpenClaw](https://composio.dev/toolkits/zoominfo/framework/openclaw) - [Hermes](https://composio.dev/toolkits/zoominfo/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/zoominfo/framework/cli) - [Google ADK](https://composio.dev/toolkits/zoominfo/framework/google-adk) - [LangChain](https://composio.dev/toolkits/zoominfo/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/zoominfo/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/zoominfo/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/zoominfo/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/zoominfo/framework/crew-ai) ## Related Toolkits - [Hubspot](https://composio.dev/toolkits/hubspot) - HubSpot is an all-in-one marketing, sales, and customer service platform. It lets teams nurture leads, automate outreach, and track every customer interaction in one place. - [Pipedrive](https://composio.dev/toolkits/pipedrive) - Pipedrive is a sales management platform offering pipeline visualization, lead tracking, and workflow automation. It helps sales teams keep deals moving forward efficiently and never miss a follow-up. - [Salesforce](https://composio.dev/toolkits/salesforce) - Salesforce is a leading CRM platform that helps businesses manage sales, service, and marketing. It centralizes customer data, enabling teams to drive growth and build strong relationships. - [Apollo](https://composio.dev/toolkits/apollo) - Apollo is a CRM and lead generation platform that helps businesses discover contacts and manage sales pipelines. Use it to streamline customer outreach and track your deals from one place. - [Attio](https://composio.dev/toolkits/attio) - Attio is a customizable CRM and workspace for managing your team's relationships and workflows. It helps teams organize contacts, automate tasks, and collaborate more efficiently. - [Acculynx](https://composio.dev/toolkits/acculynx) - AccuLynx is a cloud-based roofing business management software for contractors. It streamlines project tracking, lead management, and document sharing. - [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. - [Affinity](https://composio.dev/toolkits/affinity) - Affinity is a relationship intelligence CRM that helps private capital investors find, manage, and close more deals. It streamlines deal flow and surfaces key connections to help you win opportunities. - [Agencyzoom](https://composio.dev/toolkits/agencyzoom) - AgencyZoom is a sales and performance platform built for P&C insurance agencies. It helps agents boost sales, retain clients, and analyze producer results in one place. - [Bettercontact](https://composio.dev/toolkits/bettercontact) - Bettercontact is a smart contact enrichment tool for finding emails and phone numbers. It helps boost lead generation with automated, waterfall search across multiple sources. - [Blackbaud](https://composio.dev/toolkits/blackbaud) - Blackbaud provides cloud-based software for nonprofits, schools, and healthcare institutions. It streamlines fundraising, donor management, and mission-driven operations. - [Brilliant directories](https://composio.dev/toolkits/brilliant_directories) - Brilliant Directories is an all-in-one platform for building and managing online membership communities and business directories. It streamlines listings, member management, and engagement tools into a single, easy interface. - [Capsule crm](https://composio.dev/toolkits/capsule_crm) - Capsule CRM is a user-friendly CRM platform for managing contacts and sales pipelines. It helps businesses organize relationships and streamline their sales process efficiently. - [Centralstationcrm](https://composio.dev/toolkits/centralstationcrm) - CentralStationCRM is an easy-to-use CRM software focused on collaboration and long-term customer relationships. It helps teams manage contacts, deals, and communications all in one place. - [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. - [Close](https://composio.dev/toolkits/close) - Close is a CRM platform built for sales teams, combining calling, email automation, and predictive dialers. It streamlines sales workflows and boosts productivity with all-in-one communication tools. - [Dropcontact](https://composio.dev/toolkits/dropcontact) - Dropcontact is a B2B email finder and data enrichment service for professionals. It delivers verified email addresses and enriches contact info with up-to-date data. - [Dynamics365](https://composio.dev/toolkits/dynamics365) - Dynamics 365 is Microsoft's platform combining CRM, ERP, and productivity apps. It streamlines sales, marketing, service, and operations in one place. - [Espocrm](https://composio.dev/toolkits/espocrm) - EspoCRM is an open-source web application for managing customer relationships. It helps businesses organize contacts, track leads, and streamline their sales process. - [Fireberry](https://composio.dev/toolkits/fireberry) - Fireberry is a CRM platform that streamlines customer and sales management. It helps businesses organize contacts, automate sales, and integrate with other business tools. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Zoominfo MCP? With a standalone Zoominfo MCP server, the agents and LLMs can only access a fixed set of Zoominfo tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Zoominfo 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 Zoominfo tools. ### Can I manage the permissions and scopes for Zoominfo while using Tool Router? Yes, absolutely. You can configure which Zoominfo 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 Zoominfo 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)