# How to integrate Ip2location MCP with Autogen ```json { "title": "How to integrate Ip2location MCP with Autogen", "toolkit": "Ip2location", "toolkit_slug": "ip2location", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/ip2location/framework/autogen", "markdown_url": "https://composio.dev/toolkits/ip2location/framework/autogen.md", "updated_at": "2026-05-12T10:16:10.653Z" } ``` ## Introduction This guide walks you through connecting Ip2location to AutoGen using the Composio tool router. By the end, you'll have a working Ip2location agent that can get geolocation for these ip addresses, check if this ip is using a vpn, find domains hosted on this ip through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Ip2location account through Composio's Ip2location MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Ip2location with - [OpenAI Agents SDK](https://composio.dev/toolkits/ip2location/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/ip2location/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/ip2location/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/ip2location/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/ip2location/framework/codex) - [OpenClaw](https://composio.dev/toolkits/ip2location/framework/openclaw) - [Hermes](https://composio.dev/toolkits/ip2location/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/ip2location/framework/cli) - [Google ADK](https://composio.dev/toolkits/ip2location/framework/google-adk) - [LangChain](https://composio.dev/toolkits/ip2location/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/ip2location/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/ip2location/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/ip2location/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/ip2location/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 Ip2location - Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams - Configure an Autogen AssistantAgent that can call Ip2location tools - Run a live chat loop where you ask the agent to perform Ip2location 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 Ip2location MCP server, and what's possible with it? The Ip2location MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Ip2location account. It provides structured and secure access to advanced IP geolocation data, so your agent can perform actions like looking up IP locations, detecting proxies, running bulk lookups, and retrieving WHOIS information on your behalf. - Precise IP geolocation lookup: Instantly retrieve country, city, ISP, latitude, longitude, and more for any IPv4 or IPv6 address. - Bulk IP address processing: Run batch geolocation queries for up to 1000 IPs at once, making large-scale analysis quick and easy. - Proxy, VPN, and TOR detection: Determine whether an IP address is using anonymizing services to help with fraud prevention or security checks. - Domain and WHOIS data retrieval: Fetch WHOIS details for domains and list all hosted domains on a given IP to enrich investigations or audits. - Geographic distance calculation: Calculate the physical distance between two IP addresses to support analytics, compliance, or security use cases. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `IP2LOCATION_BULK_IP_GEOLOCATION` | Bulk IP Geolocation | Retrieve geolocation information for multiple IP addresses in a single request. Supports batch processing of 1-1000 IPv4 or IPv6 addresses with flexible output formats (JSON or CSV) and customizable field selection. Returns comprehensive data including country, region, city, coordinates, timezone, ASN, and proxy detection. Note: Automatically falls back to individual lookups if bulk endpoint is unavailable. | | `IP2LOCATION_CHECK_CREDITS` | Check IP2Location API Credits | Tool to check remaining IP2Location API credits. Use after setting up authentication to monitor usage. | | `IP2LOCATION_DISTANCE` | IP2Location Distance Calculator | Calculate the great-circle distance between two IP addresses based on their geographic locations. This tool looks up the geolocation (latitude/longitude) for each IP address and calculates the shortest distance between them over the Earth's surface using the Haversine formula. Supports both IPv4 and IPv6 addresses. Returns the distance in kilometers along with the coordinates of both IPs. Use when you need to determine geographic separation between two IP addresses, such as for latency estimation, geographic analysis, or network optimization. | | `IP2LOCATION_GET_HOSTED_DOMAINS` | IP2WHOIS Hosted Domains Lookup | Retrieves a list of domain names hosted on a specific IP address (IPv4 or IPv6). Use this tool when you need to: - Discover which domains are hosted on a particular IP - Investigate shared hosting environments - Analyze domain-to-IP relationships The API supports pagination for IPs with many hosted domains. | | `IP2LOCATION_GET_IP_GEOLOCATION` | IP2Location Get IP Geolocation | Tool to retrieve geolocation data for an IP address. Use when detailed IP location info is needed. | | `IP2LOCATION_GET_PROXY_DETECTION` | IP2Proxy: Get Proxy Detection | Tool to detect if an IP is a proxy, VPN, or TOR exit node. Use when verifying anonymizing services. | | `IP2LOCATION_IP2_WHOIS_DOMAIN_WHOIS` | IP2WHOIS Domain WHOIS Lookup | Tool to retrieve WHOIS information for a domain. Use when you need domain registration details. | | `IP2LOCATION_LIST_IPS` | IP2Location List IPs | Tool to list a curated set of test IPv4 and IPv6 addresses. Use when sample IPs are needed for IP2Location or IP2Proxy lookups during development or testing. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Ip2location MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Ip2location. Instead of manually wiring Ip2location 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 Ip2location 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 Ip2location 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 Ip2location 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 Ip2location 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 Ip2location session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["ip2location"] ) 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 Ip2location 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 Ip2location assistant agent with MCP tools agent = AssistantAgent( name="ip2location_assistant", description="An AI assistant that helps with Ip2location 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 Ip2location 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 Ip2location 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 Ip2location session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["ip2location"] ) 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 Ip2location assistant agent with MCP tools agent = AssistantAgent( name="ip2location_assistant", description="An AI assistant that helps with Ip2location 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 Ip2location 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 Ip2location 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 Ip2location, you can reuse the same structure for other MCP-enabled apps with minimal code changes. ## How to build Ip2location MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/ip2location/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/ip2location/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/ip2location/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/ip2location/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/ip2location/framework/codex) - [OpenClaw](https://composio.dev/toolkits/ip2location/framework/openclaw) - [Hermes](https://composio.dev/toolkits/ip2location/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/ip2location/framework/cli) - [Google ADK](https://composio.dev/toolkits/ip2location/framework/google-adk) - [LangChain](https://composio.dev/toolkits/ip2location/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/ip2location/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/ip2location/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/ip2location/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/ip2location/framework/crew-ai) ## Related Toolkits - [Excel](https://composio.dev/toolkits/excel) - Microsoft Excel is a robust spreadsheet application for organizing, analyzing, and visualizing data. 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It helps streamline how you gather, organize, and analyze responses. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Ip2location MCP? With a standalone Ip2location MCP server, the agents and LLMs can only access a fixed set of Ip2location tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Ip2location 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 Ip2location tools. ### Can I manage the permissions and scopes for Ip2location while using Tool Router? Yes, absolutely. You can configure which Ip2location 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 Ip2location data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)