# How to integrate Codereadr MCP with Autogen ```json { "title": "How to integrate Codereadr MCP with Autogen", "toolkit": "Codereadr", "toolkit_slug": "codereadr", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/codereadr/framework/autogen", "markdown_url": "https://composio.dev/toolkits/codereadr/framework/autogen.md", "updated_at": "2026-05-12T10:07:02.660Z" } ``` ## Introduction This guide walks you through connecting Codereadr to AutoGen using the Composio tool router. By the end, you'll have a working Codereadr agent that can create a new barcode scanning service, configure survey questions after each scan, enable kiosk mode for unattended device through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Codereadr account through Composio's Codereadr MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Codereadr with - [OpenAI Agents SDK](https://composio.dev/toolkits/codereadr/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/codereadr/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/codereadr/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/codereadr/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/codereadr/framework/codex) - [OpenClaw](https://composio.dev/toolkits/codereadr/framework/openclaw) - [Hermes](https://composio.dev/toolkits/codereadr/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/codereadr/framework/cli) - [Google ADK](https://composio.dev/toolkits/codereadr/framework/google-adk) - [LangChain](https://composio.dev/toolkits/codereadr/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/codereadr/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/codereadr/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/codereadr/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/codereadr/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 Codereadr - Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams - Configure an Autogen AssistantAgent that can call Codereadr tools - Run a live chat loop where you ask the agent to perform Codereadr 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 Codereadr MCP server, and what's possible with it? The Codereadr MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Codereadr account. It provides structured and secure access to your data collection and barcode scanning workflows, so your agent can create services, configure scan workflows, manage databases, and automate data collection processes for you. - Automated service and workflow setup: Let your agent create new CodeREADr services and configure custom workflows for scanning, picking, delivery, and receiving tasks. - Custom data collection form creation: Easily set up or modify data capture forms by adding or deleting custom questions after each scan. - Real-time scan integration: Configure Direct Scan URLs, postback endpoints, or Google Sheets connectors to forward scan results instantly to your desired platforms. - Device and database management: Direct your agent to delete devices or entire databases when they are no longer needed, streamlining your data environment. - Kiosk and unattended scanning configuration: Enable and fine-tune Kiosk Mode for unattended or dedicated scanning stations to support high-volume operations. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `CODEREADR_COLLECT_DATA_WITH_QUESTIONS` | Collect Data With Questions | Create and attach custom questions to a CodeREADr service for data collection after scans. Use this to configure forms that collect additional information from users after each barcode scan. Requires a valid service ID from CODEREADR_RETRIEVE_SERVICES or CODEREADR_CREATE_SERVICE. | | `CODEREADR_CONFIGURE_CONNECTOR` | Configure CodeREADr Connector | Helper to guide configuring the CodeREADr Connector for Google Sheets. There is no public API to programmatically create connector configurations. This tool validates your API connectivity (optional) and returns clear steps to proceed via the Google Sheets Add-on UI: https://www.codereadr.com/knowledgebase/codereadr-connector-add-on/ | | `CODEREADR_CREATE_SERVICE` | Create CodeREADr Service | Creates a new CodeREADr service (barcode scanning workflow configuration). A service defines how barcode scans are processed - whether they're simply recorded, validated against a database, forwarded to an external URL, or display web content. Each validation_method type has different required parameters: 'database'/'ondevicedatabase' require database_id, 'postback' requires postback_url, 'webview' requires description (URL/HTML). | | `CODEREADR_DELETE_DATABASE` | Delete CodeREADr Database | Delete a CodeREADr validation database by its ID. This permanently removes the database and all its barcode values. Use with caution. Note: A database cannot be deleted if it is currently linked to one or more services. You must unlink those services from the database first. Example: "Delete database with ID 1340798" | | `CODEREADR_DELETE_DEVICE` | Delete Device | Tool to delete a device from CodeREADr. Uses the CodeREADr legacy API with section=devices and action=delete parameters. Note: Device deletion may have limited support in the CodeREADr API - only 'retrieve' and 'update' actions are officially documented for devices. | | `CODEREADR_DELETE_QUESTION` | Delete Custom Question | Permanently deletes one or more custom questions from your CodeREADr account. Questions are used to collect additional data after scans. Once deleted, the question and all associated answer options are removed. This action cannot be undone. | | `CODEREADR_DELETE_SERVICE` | Delete CodeREADr Service | Delete a CodeREADr service by its numeric ID. Use this to permanently remove a service/workflow configuration from your account. Note: This is a destructive action and cannot be undone. You can delete a single service, multiple services (comma-separated IDs), or all services. Example: "Delete service with ID 12345" | | `CODEREADR_DELETE_USER` | Delete CodeREADr User | Deletes an existing user account from CodeREADr. Uses the CodeREADr legacy API endpoint (POST /api/ with section=users, action=delete). The user_id parameter can be a single ID, comma-separated list of IDs, or 'all'. Note: You cannot delete the account owner's app-user. The API will return an error if an invalid user_id is provided. | | `CODEREADR_GENERATE_SCAN_LINK` | Generate Scan Link | Generates a CodeREADr scan link URI that opens the CodeREADr mobile app with a pre-filled scan value. Use this tool when you need to create clickable links that launch the CodeREADr scanner with a specific barcode, QR code, or identifier already entered. | | `CODEREADR_LIST_SUPPORTED_BARCODE_TYPES` | List Supported Barcode Types | Lists barcode symbologies supported by CodeREADr for scanning. Returns 1D barcodes (Code 39, Code 128, EAN, UPC, Codabar, etc.), 2D barcodes (QR Code, Data Matrix, PDF-417, Aztec, etc.), and specialized formats. Use this to verify if a specific barcode type is supported before scanning. | | `CODEREADR_RETRIEVE_DATABASES` | Retrieve CodeREADr Databases | Retrieves all validation databases configured in your CodeREADr account. Use this to list databases for barcode validation, see their IDs, names, item counts, and which services they're linked to. | | `CODEREADR_RETRIEVE_DEVICES` | Retrieve Devices | Retrieve a list of devices registered to your CodeREADr account. This tool fetches information about devices linked to your account, including device IDs, UDIDs, names, and creation timestamps. Use this to monitor which devices have access to your CodeREADr services. | | `CODEREADR_RETRIEVE_SCANS` | Retrieve Scan Records | Retrieve scan records from your CodeREADr account. Scans are the core data collected by CodeREADr when users scan barcodes using the mobile app. Each scan record includes the barcode value, timestamp, device info, validation status, and any collected responses. Use filters to narrow down results by service, user, device, date range, or status. Returns scan records in batches. Use limit and offset parameters for pagination. | | `CODEREADR_RETRIEVE_SERVICES` | Retrieve CodeREADr Services | Retrieve configured services from your CodeREADr account. Services are the core organizational units in CodeREADr that define how barcode scans are validated and processed. Use this action to list all services or retrieve specific services by ID. | | `CODEREADR_UPDATE_QUESTION` | Update CodeREADr Question | Add answer options to an existing CodeREADr question. Use this to add selectable answers for checkbox, dropdown, or option-type questions. The CodeREADr API does not support updating question text - to change text, delete and recreate the question. | | `CODEREADR_UPDATE_SERVICE` | Update CodeREADr Service | Update an existing CodeREADr service configuration. Use this action to modify settings of a service by its ID. Only specified fields will be updated - omitted fields retain their current values. Common use cases: - Renaming a service - Changing postback/webhook URL - Enabling/disabling GPS tracking - Modifying duplicate scan handling - Setting time restrictions for service availability | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Codereadr MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Codereadr. Instead of manually wiring Codereadr 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 Codereadr 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 Codereadr 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 Codereadr 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 Codereadr 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 Codereadr session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["codereadr"] ) 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 Codereadr 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 Codereadr assistant agent with MCP tools agent = AssistantAgent( name="codereadr_assistant", description="An AI assistant that helps with Codereadr 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 Codereadr 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 Codereadr 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 Codereadr session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["codereadr"] ) 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 Codereadr assistant agent with MCP tools agent = AssistantAgent( name="codereadr_assistant", description="An AI assistant that helps with Codereadr 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 Codereadr 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 Codereadr 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 Codereadr, you can reuse the same structure for other MCP-enabled apps with minimal code changes. ## How to build Codereadr MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/codereadr/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/codereadr/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/codereadr/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/codereadr/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/codereadr/framework/codex) - [OpenClaw](https://composio.dev/toolkits/codereadr/framework/openclaw) - [Hermes](https://composio.dev/toolkits/codereadr/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/codereadr/framework/cli) - [Google ADK](https://composio.dev/toolkits/codereadr/framework/google-adk) - [LangChain](https://composio.dev/toolkits/codereadr/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/codereadr/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/codereadr/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/codereadr/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/codereadr/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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Get detailed environmental insights directly from your own sensors for smarter apps and automations. - [Anonyflow](https://composio.dev/toolkits/anonyflow) - Anonyflow is a service for encryption-based data anonymization and secure data sharing. 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. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Codereadr MCP? With a standalone Codereadr MCP server, the agents and LLMs can only access a fixed set of Codereadr tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Codereadr 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 Codereadr tools. ### Can I manage the permissions and scopes for Codereadr while using Tool Router? Yes, absolutely. You can configure which Codereadr 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 Codereadr data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)