# How to integrate Cdr platform MCP with Autogen ```json { "title": "How to integrate Cdr platform MCP with Autogen", "toolkit": "Cdr platform", "toolkit_slug": "cdr_platform", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/cdr_platform/framework/autogen", "markdown_url": "https://composio.dev/toolkits/cdr_platform/framework/autogen.md", "updated_at": "2026-05-12T10:05:51.705Z" } ``` ## Introduction This guide walks you through connecting Cdr platform to AutoGen using the Composio tool router. By the end, you'll have a working Cdr platform agent that can estimate cost for removing 10 tons co2, check cdr platform service status now, show current billing thresholds and fees through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Cdr platform account through Composio's Cdr platform MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Cdr platform with - [OpenAI Agents SDK](https://composio.dev/toolkits/cdr_platform/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/cdr_platform/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/cdr_platform/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/cdr_platform/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/cdr_platform/framework/codex) - [OpenClaw](https://composio.dev/toolkits/cdr_platform/framework/openclaw) - [Hermes](https://composio.dev/toolkits/cdr_platform/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/cdr_platform/framework/cli) - [Google ADK](https://composio.dev/toolkits/cdr_platform/framework/google-adk) - [LangChain](https://composio.dev/toolkits/cdr_platform/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/cdr_platform/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/cdr_platform/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/cdr_platform/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/cdr_platform/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 Cdr platform - Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams - Configure an Autogen AssistantAgent that can call Cdr platform tools - Run a live chat loop where you ask the agent to perform Cdr platform 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 Cdr platform MCP server, and what's possible with it? The Cdr platform MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Cdr platform account. It provides structured and secure access to your carbon removal services, so your agent can estimate CDR costs, check platform health, retrieve billing info, and even purchase carbon credits on your behalf. - Instant CDR price estimation: Ask your agent to calculate the cost of carbon dioxide removal based on selected methods and quantities before making a purchase. - Service health monitoring: Let your agent verify the operational status of the Cdr platform, including API and database connectivity, to ensure everything is running smoothly. - Up-to-date billing and pricing info: Retrieve current pricing, fees, and billing thresholds for carbon removal services to inform purchasing decisions and budget planning. - Automated carbon removal purchases: Empower your agent to initiate and complete purchases of carbon dioxide removal credits after confirming costs and selected methods. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `CDR_PLATFORM_GET_CDR_PRICE` | Get CDR Price | Calculate the cost for carbon dioxide removal (CDR) services. Specify one or more removal methods (e.g., 'bio-oil', 'kelp-sinking') with their respective amounts in kilograms to get detailed pricing including removal costs and fees. Returns costs in cents (USD). Use this to estimate pricing before making purchases. | | `CDR_PLATFORM_GET_HEALTH_CHECK` | Get Health Check | Tool to perform a health check of the CDR Platform service. Use when you need to verify API and database connectivity and core service status. | | `CDR_PLATFORM_POST_CDR_PURCHASE` | Post CDR Purchase | Tool to initiate the purchase of carbon dioxide removal credits. Use after confirming cost and methods to finalize the order. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Cdr platform MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Cdr platform. Instead of manually wiring Cdr platform 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 Cdr platform 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 Cdr platform 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 Cdr platform 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 Cdr platform 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 Cdr platform session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["cdr_platform"] ) 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 Cdr platform 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 Cdr platform assistant agent with MCP tools agent = AssistantAgent( name="cdr_platform_assistant", description="An AI assistant that helps with Cdr platform 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 Cdr platform 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 Cdr platform 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 Cdr platform session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["cdr_platform"] ) 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 Cdr platform assistant agent with MCP tools agent = AssistantAgent( name="cdr_platform_assistant", description="An AI assistant that helps with Cdr platform 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 Cdr platform 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 Cdr platform 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 Cdr platform, you can reuse the same structure for other MCP-enabled apps with minimal code changes. ## How to build Cdr platform MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/cdr_platform/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/cdr_platform/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/cdr_platform/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/cdr_platform/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/cdr_platform/framework/codex) - [OpenClaw](https://composio.dev/toolkits/cdr_platform/framework/openclaw) - [Hermes](https://composio.dev/toolkits/cdr_platform/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/cdr_platform/framework/cli) - [Google ADK](https://composio.dev/toolkits/cdr_platform/framework/google-adk) - [LangChain](https://composio.dev/toolkits/cdr_platform/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/cdr_platform/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/cdr_platform/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/cdr_platform/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/cdr_platform/framework/crew-ai) ## Related Toolkits - [Addresszen](https://composio.dev/toolkits/addresszen) - Addresszen is a real-time address autocomplete and verification service. It helps capture accurate, deliverable addresses with instant suggestions and validation. - [Asin data api](https://composio.dev/toolkits/asin_data_api) - Asin data api gives you detailed, real-time product data from Amazon, including price, rank, and reviews. Perfect for e-commerce pros and data-driven marketers who need instant marketplace insights. - [Baselinker](https://composio.dev/toolkits/baselinker) - BaseLinker is an all-in-one e-commerce management platform connecting stores, marketplaces, carriers, and more. It streamlines order processing, inventory control, and automates your sales operations. - [Bestbuy](https://composio.dev/toolkits/bestbuy) - Best Buy is a leading retailer offering APIs for product, store, and recommendation data. Instantly access up-to-date retail insights for smarter shopping and decision-making. - [Btcpay server](https://composio.dev/toolkits/btcpay_server) - BTCPay Server is a free, open-source, self-hosted Bitcoin payment processor. It lets merchants accept Bitcoin payments directly, cutting out middlemen and boosting privacy. - [Cloudcart](https://composio.dev/toolkits/cloudcart) - CloudCart is an e-commerce platform for building and managing online stores. It helps businesses streamline product listings, orders, and customer engagement. - [Countdown api](https://composio.dev/toolkits/countdown_api) - Countdown API gives you real-time, structured eBay product data, reviews, and seller feedback. Perfect for powering price monitoring, product research, or marketplace analytics workflows. - [Dpd2](https://composio.dev/toolkits/dpd2) - Dpd2 is a robust email management platform for handling, sorting, and automating email workflows. Streamline your communications and boost productivity with advanced sorting, labeling, and response tools. - [Finerworks](https://composio.dev/toolkits/finerworks) - FinerWorks is an online platform for fine art and photo printing services. Artists and photographers use it to order custom prints and manage print inventory efficiently. - [Fingertip](https://composio.dev/toolkits/fingertip) - Fingertip is a business management platform for selling, booking, and customer engagement—all from a single link. It helps businesses streamline operations and connect with customers across social channels. - [Fraudlabs pro](https://composio.dev/toolkits/fraudlabs_pro) - FraudLabs Pro is an online payment fraud detection service for e-commerce and merchants. It helps minimize chargebacks and revenue loss by detecting and preventing fraudulent transactions. - [Gift up](https://composio.dev/toolkits/gift_up) - Gift Up! is a digital platform for selling, managing, and redeeming gift cards online. It streamlines promotions and gift card transactions for businesses and their customers. - [Goody](https://composio.dev/toolkits/goody) - Goody is a gifting platform that lets users send gifts and physical products without handling logistics. It streamlines gifting by managing delivery, fulfillment, and recipient experience. - [Gumroad](https://composio.dev/toolkits/gumroad) - Gumroad is a platform for selling digital products, physical goods, and memberships with a simple checkout and marketing tools. It streamlines creator payouts and helps you grow your audience effortlessly. - [Instacart](https://composio.dev/toolkits/instacart) - Instacart is an online grocery delivery and pickup service platform. It lets you discover local retailers and create shoppable lists and recipes with ease. - [Junglescout](https://composio.dev/toolkits/junglescout) - Junglescout is an Amazon product research and analytics platform for sellers. It delivers sales estimates, competitive insights, and optimization tools to boost your Amazon business. - [Ko fi](https://composio.dev/toolkits/ko_fi) - Ko-fi is a platform that lets creators receive donations, memberships, and sales from fans. It helps creators monetize their work and grow their audience with minimal friction. - [Lemon squeezy](https://composio.dev/toolkits/lemon_squeezy) - Lemon Squeezy is a payments and subscription platform built for software companies. It makes managing payments, taxes, and customer subscriptions effortless. - [Loyverse](https://composio.dev/toolkits/loyverse) - Loyverse is a point-of-sale (POS) platform for small businesses, offering tools for sales, inventory, and customer loyalty. It helps streamline retail operations and boost customer engagement. - [Memberstack](https://composio.dev/toolkits/memberstack) - Memberstack lets you add user authentication, payments, and member management to your website—no backend code required. Easily manage your site's members and subscriptions from a single platform. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Cdr platform MCP? With a standalone Cdr platform MCP server, the agents and LLMs can only access a fixed set of Cdr platform tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Cdr platform 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 Cdr platform tools. ### Can I manage the permissions and scopes for Cdr platform while using Tool Router? Yes, absolutely. You can configure which Cdr platform 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 Cdr platform data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)