# How to integrate Wakatime MCP with CrewAI ```json { "title": "How to integrate Wakatime MCP with CrewAI", "toolkit": "Wakatime", "toolkit_slug": "wakatime", "framework": "CrewAI", "framework_slug": "crew-ai", "url": "https://composio.dev/toolkits/wakatime/framework/crew-ai", "markdown_url": "https://composio.dev/toolkits/wakatime/framework/crew-ai.md", "updated_at": "2026-05-12T10:29:59.474Z" } ``` ## Introduction This guide walks you through connecting Wakatime to CrewAI 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 CrewAI 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) - [Vercel AI SDK](https://composio.dev/toolkits/wakatime/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/wakatime/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/wakatime/framework/llama-index) ## TL;DR Here's what you'll learn: - Get a Composio API key and configure your Wakatime connection - Set up CrewAI with an MCP enabled agent - Create a Tool Router session or standalone MCP server for Wakatime - Build a conversational loop where your agent can execute Wakatime operations ## What is CrewAI? CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews. Key features include: - Agent Roles: Define specialized agents with specific goals and backstories - Task Management: Create tasks with clear descriptions and expected outputs - Crew Orchestration: Combine agents and tasks into collaborative workflows - MCP Integration: Connect to external tools through Model Context Protocol ## 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 starting, make sure you have: - Python 3.9 or higher - A Composio account and API key - A Wakatime connection authorized in Composio - An OpenAI API key for the CrewAI LLM - Basic familiarity with Python ### 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 **What's happening:** - composio connects your agent to Wakatime via MCP - crewai provides Agent, Task, Crew, and LLM primitives - crewai-tools[mcp] includes MCP helpers - python-dotenv loads environment variables from .env ```bash pip install composio crewai crewai-tools[mcp] python-dotenv ``` ### 3. Set up environment variables Create a .env file in your project root. What's happening: - COMPOSIO_API_KEY authenticates with Composio - USER_ID scopes the session to your account - OPENAI_API_KEY lets CrewAI use your chosen OpenAI model ```bash COMPOSIO_API_KEY=your_composio_api_key_here USER_ID=your_user_id_here OPENAI_API_KEY=your_openai_api_key_here ``` ### 4. Import dependencies **What's happening:** - CrewAI classes define agents and tasks, and run the workflow - MCPServerHTTP connects the agent to an MCP endpoint - Composio will give you a short lived Wakatime MCP URL ```python import os from composio import Composio from crewai import Agent, Task, Crew from crewai_tools import MCPServerAdapter import dotenv dotenv.load_dotenv() COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY") COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID") if not COMPOSIO_API_KEY: raise ValueError("COMPOSIO_API_KEY is not set") if not COMPOSIO_USER_ID: raise ValueError("COMPOSIO_USER_ID is not set") ``` ### 5. Create a Composio Tool Router session for Wakatime **What's happening:** - You create a Wakatime only session through Composio - Composio returns an MCP HTTP URL that exposes Wakatime tools ```python composio_client = Composio(api_key=COMPOSIO_API_KEY) session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["wakatime"]) url = session.mcp.url ``` ### 6. Initialize the MCP Server **What's Happening:** - Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication. - MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format. - Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools. - Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops. - Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries. ```python server_params = { "url": url, "transport": "streamable-http", "headers": {"x-api-key": COMPOSIO_API_KEY}, } with MCPServerAdapter(server_params) as tools: agent = Agent( role="Search Assistant", goal="Help users search the internet effectively", backstory="You are a helpful assistant with access to search tools.", tools=tools, verbose=False, max_iter=10, ) ``` ### 7. Create a CLI Chatloop and define the Crew **What's Happening:** - Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable. - Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean. - Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses. - Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context. - Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response. - Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity. ```python print("Chat started! Type 'exit' or 'quit' to end.\n") conversation_context = "" while True: user_input = input("You: ").strip() if user_input.lower() in ["exit", "quit", "bye"]: print("\nGoodbye!") break if not user_input: continue conversation_context += f"\nUser: {user_input}\n" print("\nAgent is thinking...\n") task = Task( description=( f"Conversation history:\n{conversation_context}\n\n" f"Current request: {user_input}" ), expected_output="A helpful response addressing the user's request", agent=agent, ) crew = Crew(agents=[agent], tasks=[task], verbose=False) result = crew.kickoff() response = str(result) conversation_context += f"Agent: {response}\n" print(f"Agent: {response}\n") ``` ## Complete Code ```python from crewai import Agent, Task, Crew, LLM from crewai_tools import MCPServerAdapter from composio import Composio from dotenv import load_dotenv import os load_dotenv() GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY") COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY") COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID") if not GOOGLE_API_KEY: raise ValueError("GOOGLE_API_KEY is not set in the environment.") if not COMPOSIO_API_KEY: raise ValueError("COMPOSIO_API_KEY is not set in the environment.") if not COMPOSIO_USER_ID: raise ValueError("COMPOSIO_USER_ID is not set in the environment.") # Initialize Composio and create a session composio = Composio(api_key=COMPOSIO_API_KEY) session = composio.create( user_id=COMPOSIO_USER_ID, toolkits=["wakatime"], ) url = session.mcp.url # Configure LLM llm = LLM( model="gpt-5", api_key=os.getenv("OPENAI_API_KEY"), ) server_params = { "url": url, "transport": "streamable-http", "headers": {"x-api-key": COMPOSIO_API_KEY}, } with MCPServerAdapter(server_params) as tools: agent = Agent( role="Search Assistant", goal="Help users with internet searches", backstory="You are an expert assistant with access to Composio Search tools.", tools=tools, llm=llm, verbose=False, max_iter=10, ) print("Chat started! Type 'exit' or 'quit' to end.\n") conversation_context = "" while True: user_input = input("You: ").strip() if user_input.lower() in ["exit", "quit", "bye"]: print("\nGoodbye!") break if not user_input: continue conversation_context += f"\nUser: {user_input}\n" print("\nAgent is thinking...\n") task = Task( description=( f"Conversation history:\n{conversation_context}\n\n" f"Current request: {user_input}" ), expected_output="A helpful response addressing the user's request", agent=agent, ) crew = Crew(agents=[agent], tasks=[task], verbose=False) result = crew.kickoff() response = str(result) conversation_context += f"Agent: {response}\n" print(f"Agent: {response}\n") ``` ## Conclusion You now have a CrewAI agent connected to Wakatime through Composio's Tool Router. The agent can perform Wakatime operations through natural language commands. Next steps: - Add role-specific instructions to customize agent behavior - Plug in more toolkits for multi-app workflows - Chain tasks for complex multi-step operations ## 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) - [Vercel AI SDK](https://composio.dev/toolkits/wakatime/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/wakatime/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/wakatime/framework/llama-index) ## 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 CrewAI? Yes, you can. CrewAI 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)