# How to integrate Optimoroute MCP with Vercel AI SDK v6 ```json { "title": "How to integrate Optimoroute MCP with Vercel AI SDK v6", "toolkit": "Optimoroute", "toolkit_slug": "optimoroute", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/optimoroute/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/optimoroute/framework/ai-sdk.md", "updated_at": "2026-05-12T10:21:00.158Z" } ``` ## Introduction This guide walks you through connecting Optimoroute to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Optimoroute agent that can list all active drivers on duty today, show planned delivery routes for tomorrow, find unassigned orders for this week through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Optimoroute account through Composio's Optimoroute MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Optimoroute with - [OpenAI Agents SDK](https://composio.dev/toolkits/optimoroute/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/optimoroute/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/optimoroute/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/optimoroute/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/optimoroute/framework/codex) - [OpenClaw](https://composio.dev/toolkits/optimoroute/framework/openclaw) - [Hermes](https://composio.dev/toolkits/optimoroute/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/optimoroute/framework/cli) - [Google ADK](https://composio.dev/toolkits/optimoroute/framework/google-adk) - [LangChain](https://composio.dev/toolkits/optimoroute/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/optimoroute/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/optimoroute/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/optimoroute/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up and configure a Vercel AI SDK agent with Optimoroute integration - Using Composio's Tool Router to dynamically load and access Optimoroute tools - Creating an MCP client connection using HTTP transport - Building an interactive CLI chat interface with conversation history management - Handling tool calls and results within the Vercel AI SDK framework ## What is Vercel AI SDK? The Vercel AI SDK is a TypeScript library for building AI-powered applications. It provides tools for creating agents that can use external services and maintain conversation state. Key features include: - streamText: Core function for streaming responses with real-time tool support - MCP Client: Built-in support for Model Context Protocol via @ai-sdk/mcp - Step Counting: Control multi-step tool execution with stopWhen: stepCountIs() - OpenAI Provider: Native integration with OpenAI models ## What is the Optimoroute MCP server, and what's possible with it? The Optimoroute MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Optimoroute account. It provides structured and secure access to your logistics and planning data, so your agent can perform actions like retrieving driver details, viewing planned delivery routes, checking route assignments, and monitoring driver status on your behalf. - Live driver roster and status retrieval: Instantly fetch up-to-date information about all drivers, including their current availability and contact details. - Planned route overview for any date: Have your agent pull a detailed list of all planned routes for a specific date, including stop information and route parameters. - Monitor unassigned orders and route gaps: Easily identify orders that haven’t been assigned to a route, helping you spot scheduling bottlenecks. - Centralized route and driver reporting: Aggregate route and driver data to power dashboards or daily logistics summaries, all via your AI agent. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `OPTIMOROUTE_CREATE_ORDER` | Create Order | Tool to create a new order or update an existing order in OptimoRoute. Use when you need to add delivery, pickup, or task orders to the system with location, time windows, and other constraints. | | `OPTIMOROUTE_CREATE_OR_UPDATE_ORDERS` | Create or Update Orders | Tool to bulk create, update, or replace multiple orders at once without geocoding. Use when you need to add new orders or modify existing ones efficiently. Supports up to 500 orders per request. | | `OPTIMOROUTE_DELETE_ALL_ORDERS` | Delete All Orders | Tool to remove all orders and planned routes for a specified date. Use when you need to clear orders for a specific date or delete all orders system-wide if no date is provided. | | `OPTIMOROUTE_DELETE_ORDER` | Delete Order | Tool to remove a single order from the OptimoRoute system. Use when you need to delete a specific order by its orderNo. | | `OPTIMOROUTE_DELETE_ORDERS` | Delete Orders | Tool to delete one or more orders from the system in bulk (max 500 per request). Use when you need to remove orders, either individually or in batch operations. | | `OPTIMOROUTE_GET_COMPLETION_DETAILS` | Get Order Completion Details | Tool to retrieve completion details for one or more orders including proof of delivery data. Use when you need to check order completion status, timing details, and form data. | | `OPTIMOROUTE_GET_DRIVERS` | Get Drivers | Tool to retrieve all drivers in the system. Use when you need up-to-date driver data including status and contact information. | | `OPTIMOROUTE_GET_EVENTS` | Get Mobile Events | Tool to retrieve mobile events from drivers' field operations. Use when you need to track order completions, status changes (success, failed, on_duty, off_duty), and other field events for the currently active plan. | | `OPTIMOROUTE_GET_ORDERS` | Get Orders | Tool to retrieve one or more orders from OptimoRoute. Use when you need detailed order information including location, time windows, and assignment details. | | `OPTIMOROUTE_GET_PLANNING_STATUS` | Get Planning Status | Tool to retrieve the status of an active planning/optimization process. Use when you need to check the progress of a planning job by providing its ID. | | `OPTIMOROUTE_GET_ROUTES` | Get Planned Routes | Tool to retrieve all planned routes for a given date. Use when you need a detailed view of routes including optional stops, route parameters, and unassigned orders. | | `OPTIMOROUTE_GET_SCHEDULING_INFO` | Get Order Scheduling Info | Tool to retrieve scheduling information for a specific order. Use when you need to check if an order is scheduled and get details like driver assignment, timing, and position. | | `OPTIMOROUTE_SEARCH_ORDERS` | Search Orders | Tool to search for orders in OptimoRoute based on criteria. Use when you need to find orders by date range, order identifiers, or order status. At least one of 'orders' or 'date_range' must be provided. | | `OPTIMOROUTE_START_PLANNING` | Start Planning | Tool to start the planning/optimization process for a specified date or date range. Use when you need to generate optimized routes for orders and drivers. Requires orders to be created before planning can begin. | | `OPTIMOROUTE_STOP_PLANNING` | Stop Planning | Tool to stop an active planning/optimization process. Use when you need to halt a running planning job by providing its ID. | | `OPTIMOROUTE_UPDATE_DRIVER_PARAMETERS` | Update Driver Parameters | Tool to update driver parameters for a specific date including work times, vehicle assignment, and start/end locations. Use when you need to modify driver availability or routing constraints. Note that this unschedules existing routes for the driver on the specified date. | | `OPTIMOROUTE_UPDATE_DRIVERS_PARAMETERS` | Update Drivers Parameters | Tool to update parameters of multiple drivers for specified dates in bulk (max 500 per request). Use when you need to modify driver configuration including work hours, vehicle assignments, and location settings. Note: Existing routes for the specified drivers and dates will be unscheduled. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Optimoroute MCP server is an implementation of the Model Context Protocol that connects your AI agent to Optimoroute. It provides structured and secure access so your agent can perform Optimoroute 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 you begin, make sure you have: - Node.js and npm installed - A Composio account with API key - An OpenAI API key ### 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 required dependencies First, install the necessary packages for your project. What you're installing: - @ai-sdk/openai: Vercel AI SDK's OpenAI provider - @ai-sdk/mcp: MCP client for Vercel AI SDK - @composio/core: Composio SDK for tool integration - ai: Core Vercel AI SDK - dotenv: Environment variable management ```bash npm install @ai-sdk/openai @ai-sdk/mcp @composio/core ai dotenv ``` ### 3. Set up environment variables Create a .env file in your project root. What's needed: - OPENAI_API_KEY: Your OpenAI API key for GPT model access - COMPOSIO_API_KEY: Your Composio API key for tool access - COMPOSIO_USER_ID: A unique identifier for the user session ```bash OPENAI_API_KEY=your_openai_api_key_here COMPOSIO_API_KEY=your_composio_api_key_here COMPOSIO_USER_ID=your_user_id_here ``` ### 4. Import required modules and validate environment What's happening: - We're importing all necessary libraries including Vercel AI SDK's OpenAI provider and Composio - The dotenv/config import automatically loads environment variables - The MCP client import enables connection to Composio's tool server ```typescript import "dotenv/config"; import { openai } from "@ai-sdk/openai"; import { Composio } from "@composio/core"; import * as readline from "readline"; import { streamText, type ModelMessage, stepCountIs } from "ai"; import { createMCPClient } from "@ai-sdk/mcp"; const composioAPIKey = process.env.COMPOSIO_API_KEY; const composioUserID = process.env.COMPOSIO_USER_ID; if (!process.env.OPENAI_API_KEY) 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, }); ``` ### 5. Create Tool Router session and initialize MCP client What's happening: - We're creating a Tool Router session that gives your agent access to Optimoroute tools - The create method takes the user ID and specifies which toolkits should be available - The returned mcp object contains the URL and authentication headers needed to connect to the MCP server - This session provides access to all Optimoroute-related tools through the MCP protocol ```typescript async function main() { // Create a tool router session for the user const session = await composio.create(composioUserID!, { toolkits: ["optimoroute"], }); const mcpUrl = session.mcp.url; ``` ### 6. Connect to MCP server and retrieve tools What's happening: - We're creating an MCP client that connects to our Composio Tool Router session via HTTP - The mcp.url provides the endpoint, and mcp.headers contains authentication credentials - The type: "http" is important - Composio requires HTTP transport - tools() retrieves all available Optimoroute tools that the agent can use ```typescript const mcpClient = await createMCPClient({ transport: { type: "http", url: mcpUrl, headers: session.mcp.headers, // Authentication headers for the Composio MCP server }, }); const tools = await mcpClient.tools(); ``` ### 7. Initialize conversation and CLI interface What's happening: - We initialize an empty messages array to maintain conversation history - A readline interface is created to accept user input from the command line - Instructions are displayed to guide the user on how to interact with the agent ```typescript let messages: ModelMessage[] = []; console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n"); console.log( "Ask any questions related to optimoroute, like summarize my last 5 emails, send an email, etc... :)))\n", ); const rl = readline.createInterface({ input: process.stdin, output: process.stdout, prompt: "> ", }); rl.prompt(); ``` ### 8. Handle user input and stream responses with real-time tool feedback What's happening: - We use streamText instead of generateText to stream responses in real-time - toolChoice: "auto" allows the model to decide when to use Optimoroute tools - stopWhen: stepCountIs(10) allows up to 10 steps for complex multi-tool operations - onStepFinish callback displays which tools are being used in real-time - We iterate through the text stream to create a typewriter effect as the agent responds - The complete response is added to conversation history to maintain context - Errors are caught and displayed with helpful retry suggestions ```typescript 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({ role: "user", content: trimmedInput }); console.log("\nAgent is thinking...\n"); try { const stream = streamText({ model: openai("gpt-5"), messages, tools, toolChoice: "auto", stopWhen: stepCountIs(10), onStepFinish: (step) => { for (const toolCall of step.toolCalls) { console.log(`[Using tool: ${toolCall.toolName}]`); } if (step.toolCalls.length > 0) { console.log(""); // Add space after tool calls } }, }); for await (const chunk of stream.textStream) { process.stdout.write(chunk); } console.log("\n\n---\n"); // Get final result for message history const response = await stream.response; if (response?.messages?.length) { messages.push(...response.messages); } } catch (error) { console.error("\nAn error occurred while talking to the agent:"); console.error(error); console.log( "\nYou can try again or restart the app if it keeps happening.\n", ); } finally { rl.prompt(); } }); rl.on("close", async () => { await mcpClient.close(); console.log("\n👋 Session ended."); 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 { Composio } from "@composio/core"; import * as readline from "readline"; import { streamText, type ModelMessage, stepCountIs } from "ai"; import { createMCPClient } from "@ai-sdk/mcp"; const composioAPIKey = process.env.COMPOSIO_API_KEY; const composioUserID = process.env.COMPOSIO_USER_ID; if (!process.env.OPENAI_API_KEY) 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, }); async function main() { // Create a tool router session for the user const session = await composio.create(composioUserID!, { toolkits: ["optimoroute"], }); const mcpUrl = session.mcp.url; const mcpClient = await createMCPClient({ transport: { type: "http", url: mcpUrl, headers: session.mcp.headers, // Authentication headers for the Composio MCP server }, }); const tools = await mcpClient.tools(); let messages: ModelMessage[] = []; console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n"); console.log( "Ask any questions related to optimoroute, like summarize my last 5 emails, send an email, etc... :)))\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({ role: "user", content: trimmedInput }); console.log("\nAgent is thinking...\n"); try { const stream = streamText({ model: openai("gpt-5"), messages, tools, toolChoice: "auto", stopWhen: stepCountIs(10), onStepFinish: (step) => { for (const toolCall of step.toolCalls) { console.log(`[Using tool: ${toolCall.toolName}]`); } if (step.toolCalls.length > 0) { console.log(""); // Add space after tool calls } }, }); for await (const chunk of stream.textStream) { process.stdout.write(chunk); } console.log("\n\n---\n"); // Get final result for message history const response = await stream.response; if (response?.messages?.length) { messages.push(...response.messages); } } catch (error) { console.error("\nAn error occurred while talking to the agent:"); console.error(error); console.log( "\nYou can try again or restart the app if it keeps happening.\n", ); } finally { rl.prompt(); } }); rl.on("close", async () => { await mcpClient.close(); console.log("\n👋 Session ended."); process.exit(0); }); } main().catch((err) => { console.error("Fatal error:", err); process.exit(1); }); ``` ## Conclusion You've successfully built a Optimoroute agent using the Vercel AI SDK with streaming capabilities! This implementation provides a powerful foundation for building AI applications with natural language interfaces and real-time feedback. Key features of this implementation: - Real-time streaming responses for a better user experience with typewriter effect - Live tool execution feedback showing which tools are being used as the agent works - Dynamic tool loading through Composio's Tool Router with secure authentication - Multi-step tool execution with configurable step limits (up to 10 steps) - Comprehensive error handling for robust agent execution - Conversation history maintenance for context-aware responses You can extend this further by adding custom error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows. ## How to build Optimoroute MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/optimoroute/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/optimoroute/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/optimoroute/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/optimoroute/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/optimoroute/framework/codex) - [OpenClaw](https://composio.dev/toolkits/optimoroute/framework/openclaw) - [Hermes](https://composio.dev/toolkits/optimoroute/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/optimoroute/framework/cli) - [Google ADK](https://composio.dev/toolkits/optimoroute/framework/google-adk) - [LangChain](https://composio.dev/toolkits/optimoroute/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/optimoroute/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/optimoroute/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/optimoroute/framework/crew-ai) ## Related Toolkits - [Google Sheets](https://composio.dev/toolkits/googlesheets) - Google Sheets is a cloud-based spreadsheet tool for real-time collaboration and data analysis. It lets teams work together from anywhere, updating information instantly. - [Notion](https://composio.dev/toolkits/notion) - Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place. - [Airtable](https://composio.dev/toolkits/airtable) - Airtable combines the flexibility of spreadsheets with the power of a database for easy project and data management. Teams use Airtable to organize, track, and collaborate with custom views and automations. - [Asana](https://composio.dev/toolkits/asana) - Asana is a collaborative work management platform for teams to organize and track projects. It streamlines teamwork, boosts productivity, and keeps everyone aligned on goals. - [Google Tasks](https://composio.dev/toolkits/googletasks) - Google Tasks is a to-do list and task management tool integrated into Gmail and Google Calendar. It helps you organize, track, and complete tasks across your Google ecosystem. - [Linear](https://composio.dev/toolkits/linear) - Linear is a modern issue tracking and project planning tool for fast-moving teams. It helps streamline workflows, organize projects, and boost productivity. - [Jira](https://composio.dev/toolkits/jira) - Jira is Atlassian’s platform for bug tracking, issue tracking, and agile project management. It helps teams organize work, prioritize tasks, and deliver projects efficiently. - [Clickup](https://composio.dev/toolkits/clickup) - ClickUp is an all-in-one productivity platform for managing tasks, docs, goals, and team collaboration. It streamlines project workflows so teams can work smarter and stay organized in one place. - [Monday](https://composio.dev/toolkits/monday) - Monday.com is a customizable work management platform for project planning and collaboration. It helps teams organize tasks, automate workflows, and track progress in real time. - [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. - [Agiled](https://composio.dev/toolkits/agiled) - Agiled is an all-in-one business management platform for CRM, projects, and finance. It helps you streamline workflows, consolidate client data, and manage business processes in one place. - [Ascora](https://composio.dev/toolkits/ascora) - Ascora is a cloud-based field service management platform for service businesses. It streamlines scheduling, invoicing, and customer operations in one place. - [Basecamp](https://composio.dev/toolkits/basecamp) - Basecamp is a project management and team collaboration tool by 37signals. It helps teams organize tasks, share files, and communicate efficiently in one place. - [Beeminder](https://composio.dev/toolkits/beeminder) - Beeminder is an online goal-tracking platform that uses monetary pledges to keep you motivated. Stay accountable and hit your targets with real financial incentives. - [Boxhero](https://composio.dev/toolkits/boxhero) - Boxhero is a cloud-based inventory management platform for SMBs, offering real-time updates, barcode scanning, and team collaboration. It helps businesses streamline stock tracking and analytics for smarter inventory decisions. - [Breathe HR](https://composio.dev/toolkits/breathehr) - Breathe HR is cloud-based HR software for SMEs to manage employee data, absences, and performance. It simplifies HR admin, making it easy to keep employee records accurate and up to date. - [Breeze](https://composio.dev/toolkits/breeze) - Breeze is a project management platform designed to help teams plan, track, and collaborate on projects. It streamlines workflows and keeps everyone on the same page. - [Bugherd](https://composio.dev/toolkits/bugherd) - Bugherd is a visual feedback and bug tracking tool for websites. It helps teams and clients report website issues directly on live sites for faster fixes. - [Canny](https://composio.dev/toolkits/canny) - Canny is a platform for managing customer feedback and feature requests. It helps teams prioritize product decisions based on real user insights. - [Chmeetings](https://composio.dev/toolkits/chmeetings) - Chmeetings is a church management platform for events, members, donations, and volunteers. It streamlines church operations and improves community engagement. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Optimoroute MCP? With a standalone Optimoroute MCP server, the agents and LLMs can only access a fixed set of Optimoroute tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Optimoroute and many other apps based on the task at hand, all through a single MCP endpoint. ### Can I use Tool Router MCP with Vercel AI SDK v6? Yes, you can. Vercel AI SDK v6 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 Optimoroute tools. ### Can I manage the permissions and scopes for Optimoroute while using Tool Router? Yes, absolutely. You can configure which Optimoroute 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 Optimoroute data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)