# How to integrate Codereadr MCP with Mastra AI ```json { "title": "How to integrate Codereadr MCP with Mastra AI", "toolkit": "Codereadr", "toolkit_slug": "codereadr", "framework": "Mastra AI", "framework_slug": "mastra-ai", "url": "https://composio.dev/toolkits/codereadr/framework/mastra-ai", "markdown_url": "https://composio.dev/toolkits/codereadr/framework/mastra-ai.md", "updated_at": "2026-05-12T10:07:02.660Z" } ``` ## Introduction This guide walks you through connecting Codereadr to Mastra AI 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 Mastra AI 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) - [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: - Set up your environment so Mastra, OpenAI, and Composio work together - Create a Tool Router session in Composio that exposes Codereadr tools - Connect Mastra's MCP client to the Composio generated MCP URL - Fetch Codereadr tool definitions and attach them as a toolset - Build a Mastra agent that can reason, call tools, and return structured results - Run an interactive CLI where you can chat with your Codereadr agent ## What is Mastra AI? Mastra AI is a TypeScript framework for building AI agents with tool support. It provides a clean API for creating agents that can use external services through MCP. Key features include: - MCP Client: Built-in support for Model Context Protocol servers - Toolsets: Organize tools into logical groups - Step Callbacks: Monitor and debug agent execution - OpenAI Integration: Works with OpenAI models via @ai-sdk/openai ## 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 agent to Codereadr. It provides structured and secure access so your agent can perform Codereadr operations on your behalf through a secure, permission-based interface. 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 Before starting, make sure you have: - Node.js 18 or higher - A Composio account with an active API key - An OpenAI API key - Basic familiarity with TypeScript ### 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 need credits or a connected billing setup to use the models. - Store the key somewhere safe. Composio API Key - Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs). - Go to Settings and copy your API key. - This key lets your Mastra agent talk to Composio and reach Codereadr through MCP. ### 2. Install dependencies Install the required packages. What's happening: - @composio/core is the Composio SDK for creating MCP sessions - @mastra/core provides the Agent class - @mastra/mcp is Mastra's MCP client - @ai-sdk/openai is the model wrapper for OpenAI - dotenv loads environment variables from .env ```bash npm install @composio/core @mastra/core @mastra/mcp @ai-sdk/openai dotenv ``` ### 3. Set up environment variables Create a .env file in your project root. What's happening: - COMPOSIO_API_KEY authenticates your requests to Composio - COMPOSIO_USER_ID tells Composio which user this session belongs to - OPENAI_API_KEY lets the Mastra agent call OpenAI models ```bash COMPOSIO_API_KEY=your_composio_api_key_here COMPOSIO_USER_ID=your_user_id_here OPENAI_API_KEY=your_openai_api_key_here ``` ### 4. Import libraries and validate environment What's happening: - dotenv/config auto loads your .env so process.env.* is available - openai gives you a Mastra compatible model wrapper - Agent is the Mastra agent that will call tools and produce answers - MCPClient connects Mastra to your Composio MCP server - Composio is used to create a Tool Router session ```typescript import "dotenv/config"; import { openai } from "@ai-sdk/openai"; import { Agent } from "@mastra/core/agent"; import { MCPClient } from "@mastra/mcp"; import { Composio } from "@composio/core"; import * as readline from "readline"; import type { AiMessageType } from "@mastra/core/agent"; const openaiAPIKey = process.env.OPENAI_API_KEY; const composioAPIKey = process.env.COMPOSIO_API_KEY; const composioUserID = process.env.COMPOSIO_USER_ID; if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set"); if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set"); if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set"); const composio = new Composio({ apiKey: composioAPIKey as string, }); ``` ### 5. Create a Tool Router session for Codereadr What's happening: - create spins up a short-lived MCP HTTP endpoint for this user - The toolkits array contains "codereadr" for Codereadr access - session.mcp.url is the MCP URL that Mastra's MCPClient will connect to ```typescript async function main() { const session = await composio.create( composioUserID as string, { toolkits: ["codereadr"], }, ); const composioMCPUrl = session.mcp.url; console.log("Codereadr MCP URL:", composioMCPUrl); ``` ### 6. Configure Mastra MCP client and fetch tools What's happening: - MCPClient takes an id for this client and a list of MCP servers - The headers property includes the x-api-key for authentication - getTools fetches the tool definitions exposed by the Codereadr toolkit ```typescript const mcpClient = new MCPClient({ id: composioUserID as string, servers: { nasdaq: { url: new URL(composioMCPUrl), requestInit: { headers: session.mcp.headers, }, }, }, timeout: 30_000, }); console.log("Fetching MCP tools from Composio..."); const composioTools = await mcpClient.getTools(); console.log("Number of tools:", Object.keys(composioTools).length); ``` ### 7. Create the Mastra agent What's happening: - Agent is the core Mastra agent - name is just an identifier for logging and debugging - instructions guide the agent to use tools instead of only answering in natural language - model uses openai("gpt-5") to configure the underlying LLM ```typescript const agent = new Agent({ name: "codereadr-mastra-agent", instructions: "You are an AI agent with Codereadr tools via Composio.", model: "openai/gpt-5", }); ``` ### 8. Set up interactive chat interface What's happening: - messages keeps the full conversation history in Mastra's expected format - agent.generate runs the agent with conversation history and Codereadr toolsets - maxSteps limits how many tool calls the agent can take in a single run - onStepFinish is a hook that prints intermediate steps for debugging ```typescript let messages: AiMessageType[] = []; console.log("Chat started! Type 'exit' or 'quit' to end.\n"); const rl = readline.createInterface({ input: process.stdin, output: process.stdout, prompt: "> ", }); rl.prompt(); rl.on("line", async (userInput: string) => { const trimmedInput = userInput.trim(); if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) { console.log("\nGoodbye!"); rl.close(); process.exit(0); } if (!trimmedInput) { rl.prompt(); return; } messages.push({ id: crypto.randomUUID(), role: "user", content: trimmedInput, }); console.log("\nAgent is thinking...\n"); try { const response = await agent.generate(messages, { toolsets: { codereadr: composioTools, }, maxSteps: 8, }); const { text } = response; if (text && text.trim().length > 0) { console.log(`Agent: ${text}\n`); messages.push({ id: crypto.randomUUID(), role: "assistant", content: text, }); } } catch (error) { console.error("\nError:", error); } rl.prompt(); }); rl.on("close", async () => { console.log("\nSession ended."); await mcpClient.disconnect(); process.exit(0); }); } main().catch((err) => { console.error("Fatal error:", err); process.exit(1); }); ``` ## Complete Code ```typescript import "dotenv/config"; import { openai } from "@ai-sdk/openai"; import { Agent } from "@mastra/core/agent"; import { MCPClient } from "@mastra/mcp"; import { Composio } from "@composio/core"; import * as readline from "readline"; import type { AiMessageType } from "@mastra/core/agent"; const openaiAPIKey = process.env.OPENAI_API_KEY; const composioAPIKey = process.env.COMPOSIO_API_KEY; const composioUserID = process.env.COMPOSIO_USER_ID; if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set"); if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set"); if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set"); const composio = new Composio({ apiKey: composioAPIKey as string }); async function main() { const session = await composio.create(composioUserID as string, { toolkits: ["codereadr"], }); const composioMCPUrl = session.mcp.url; const mcpClient = new MCPClient({ id: composioUserID as string, servers: { codereadr: { url: new URL(composioMCPUrl), requestInit: { headers: session.mcp.headers, }, }, }, timeout: 30_000, }); const composioTools = await mcpClient.getTools(); const agent = new Agent({ name: "codereadr-mastra-agent", instructions: "You are an AI agent with Codereadr tools via Composio.", model: "openai/gpt-5", }); let messages: AiMessageType[] = []; const rl = readline.createInterface({ input: process.stdin, output: process.stdout, prompt: "> ", }); rl.prompt(); rl.on("line", async (input: string) => { const trimmed = input.trim(); if (["exit", "quit"].includes(trimmed.toLowerCase())) { rl.close(); return; } messages.push({ id: crypto.randomUUID(), role: "user", content: trimmed }); const { text } = await agent.generate(messages, { toolsets: { codereadr: composioTools }, maxSteps: 8, }); if (text) { console.log(`Agent: ${text}\n`); messages.push({ id: crypto.randomUUID(), role: "assistant", content: text }); } rl.prompt(); }); rl.on("close", async () => { await mcpClient.disconnect(); process.exit(0); }); } main(); ``` ## Conclusion You've built a Mastra AI agent that can interact with Codereadr through Composio's Tool Router. You can extend this further by: - Adding other toolkits like Gmail, Slack, or GitHub - Building a web-based chat interface around this agent - Using multiple MCP endpoints to enable cross-app workflows ## 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) - [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. It's the go-to tool for calculations, reporting, and flexible data management. - [21risk](https://composio.dev/toolkits/_21risk) - 21RISK is a web app built for easy checklist, audit, and compliance management. It streamlines risk processes so teams can focus on what matters. - [Abstract](https://composio.dev/toolkits/abstract) - Abstract provides a suite of APIs for automating data validation and enrichment tasks. It helps developers streamline workflows and ensure data quality with minimal effort. - [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. - [Agentql](https://composio.dev/toolkits/agentql) - Agentql is a toolkit that connects AI agents to the web using a specialized query language. It enables structured web interaction and data extraction for smarter automations. - [Agenty](https://composio.dev/toolkits/agenty) - Agenty is a web scraping and automation platform for extracting data and automating browser tasks—no coding needed. It streamlines data collection, monitoring, and repetitive online actions. - [Ambee](https://composio.dev/toolkits/ambee) - Ambee is an environmental data platform providing real-time, hyperlocal APIs for air quality, weather, and pollen. Get precise environmental insights to power smarter decisions in your apps and workflows. - [Ambient weather](https://composio.dev/toolkits/ambient_weather) - Ambient Weather is a platform for personal weather stations with a robust API for accessing local, real-time, and historical weather data. 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 Mastra AI? Yes, you can. Mastra AI 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)