# How to integrate Wakatime MCP with Vercel AI SDK v6 ```json { "title": "How to integrate Wakatime MCP with Vercel AI SDK v6", "toolkit": "Wakatime", "toolkit_slug": "wakatime", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/wakatime/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/wakatime/framework/ai-sdk.md", "updated_at": "2026-05-12T10:29:59.474Z" } ``` ## Introduction This guide walks you through connecting Wakatime to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Wakatime agent that can show your top coding languages this week, summarize today's coding activity by project, list your most productive coding days last month through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Wakatime account through Composio's Wakatime MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Wakatime with - [OpenAI Agents SDK](https://composio.dev/toolkits/wakatime/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/wakatime/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/wakatime/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/wakatime/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/wakatime/framework/codex) - [OpenClaw](https://composio.dev/toolkits/wakatime/framework/openclaw) - [Hermes](https://composio.dev/toolkits/wakatime/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/wakatime/framework/cli) - [Google ADK](https://composio.dev/toolkits/wakatime/framework/google-adk) - [LangChain](https://composio.dev/toolkits/wakatime/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/wakatime/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/wakatime/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/wakatime/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up and configure a Vercel AI SDK agent with Wakatime integration - Using Composio's Tool Router to dynamically load and access Wakatime 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 Wakatime MCP server, and what's possible with it? The Wakatime MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Wakatime account. It provides structured and secure access to your coding activity and productivity data, so your agent can analyze time spent coding, summarize project progress, generate reports, and surface productivity trends on your behalf. - Code activity summaries and analytics: Your agent can pull detailed breakdowns of your coding hours by language, project, or editor to help you understand where your time goes. - Project progress tracking: Get automatic updates on how much time you've dedicated to individual projects, making it easy to monitor deadlines and progress. - Personal productivity insights: Let your agent surface trends, highlight most productive days or hours, and offer suggestions for improving your workflow based on historical data. - Automated weekly and monthly reports: Have the agent generate and deliver summary reports of your coding habits, helping you spot patterns and areas for improvement. - Goal tracking and notifications: Enable your agent to track coding goals and notify you when milestones are reached or if you're falling behind. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `WAKATIME_GET_AGGREGATE_STATS` | Get Aggregate Stats | Tool to retrieve aggregate coding statistics across all WakaTime users for a given time range. Use when analyzing global trends in programming languages, editors, operating systems, and categories. | | `WAKATIME_GET_CURRENT_USER_STATUS_BAR_TODAY` | Get current user's status bar summary for today | Tool to get current user's coding activity today for displaying in IDE status bars. Use when you need a summary of today's coding time broken down by projects, languages, editors, etc. | | `WAKATIME_GET_EDITORS` | List IDE Plugins | Tool to list WakaTime IDE plugins with metadata. Use when you want to discover available IDE integrations and their latest versions. | | `WAKATIME_GET_GOALS` | List Goals | Tool to list a user's goals with progress series and metadata. Use after authenticating the user with read_goals scope. | | `WAKATIME_GET_INSIGHTS` | Get User Insight | Tool to retrieve an insight for a user over a time range. Use when analyzing user coding metrics after authentication. | | `WAKATIME_GET_LEADERS` | List Leaders | Tool to list public leaders ranked by coding activity. Use when viewing top coders globally or filtering by language, country code, or hireable status. | | `WAKATIME_GET_MACHINE_NAMES` | List Machine Names | Tool to list a user's machines including last seen time. Use when needing machine names for a specific user. | | `WAKATIME_GET_META` | Get API Meta Information | Tool to retrieve WakaTime API meta information, including public IP addresses used by WakaTime servers. Use when you need to know WakaTime's infrastructure details for network configuration or security purposes. | | `WAKATIME_GET_OAUTH_AUTHORIZE` | Generate WakaTime OAuth authorize URL | Tool to generate OAuth 2.0 authorization URL. Use when redirecting users to WakaTime to grant access. | | `WAKATIME_GET_USER` | Get User Details | Tool to get detailed profile information for a WakaTime user by user ID or username. Use 'current' as the user parameter to get the authenticated user's details. Returns comprehensive profile data including display name, email, timezone, plan, and privacy settings. | | `WAKATIME_GET_USERS_ALL_TIME_SINCE_TODAY` | Get User's Total Time Since Creation | Tool to retrieve total coding time since account creation for a user. Use after authenticating to fetch all-time stats. | | `WAKATIME_GET_USER_STATS` | Get User Stats | Tool to retrieve coding statistics for a user over the default time range. Returns comprehensive metrics including languages, editors, projects, and daily averages. Use when analyzing a user's coding patterns and productivity metrics. | | `WAKATIME_GET_USER_STATS_BY_RANGE` | Get User Stats by Range | Tool to retrieve comprehensive coding statistics for a user over a specific time range. Returns breakdowns by language, editor, project, OS, and more, along with daily averages and best day. Use when analyzing productivity patterns or generating coding activity reports for time periods. | | `WAKATIME_GET_USER_SUMMARIES` | Get User Summaries | Get user's coding activity for a time range as daily summaries. Returns detailed breakdowns by projects, languages, editors, and more for each day. Use when you need to analyze coding patterns, track project time, or generate activity reports over a date range. Requires 'read_summaries' scope. | | `WAKATIME_LIST_PROGRAM_LANGUAGES` | List Program Languages | Tool to list all verified program languages supported by WakaTime. Use when you need to discover available programming languages tracked by WakaTime. | | `WAKATIME_LIST_USER_PROJECTS` | List User Projects | List WakaTime projects for a specified user. Returns project names, IDs, creation dates, and last activity times. Use to discover available projects for any user before querying project-specific stats. | | `WAKATIME_LIST_USER_USER_AGENTS` | List User Agents | Tool to list plugins and editors which have sent data for a specified user. Use when needing to discover which development environments and tools a user is actively using. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Wakatime MCP server is an implementation of the Model Context Protocol that connects your AI agent to Wakatime. It provides structured and secure access so your agent can perform Wakatime 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 Wakatime 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 Wakatime-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: ["wakatime"], }); 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 Wakatime 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 wakatime, 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 Wakatime 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: ["wakatime"], }); 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 wakatime, 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 Wakatime 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 Wakatime MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/wakatime/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/wakatime/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/wakatime/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/wakatime/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/wakatime/framework/codex) - [OpenClaw](https://composio.dev/toolkits/wakatime/framework/openclaw) - [Hermes](https://composio.dev/toolkits/wakatime/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/wakatime/framework/cli) - [Google ADK](https://composio.dev/toolkits/wakatime/framework/google-adk) - [LangChain](https://composio.dev/toolkits/wakatime/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/wakatime/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/wakatime/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/wakatime/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 Wakatime MCP? With a standalone Wakatime MCP server, the agents and LLMs can only access a fixed set of Wakatime tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Wakatime 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 Wakatime tools. ### Can I manage the permissions and scopes for Wakatime while using Tool Router? Yes, absolutely. You can configure which Wakatime 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 Wakatime data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)