# How to integrate Wakatime MCP with Pydantic AI

```json
{
  "title": "How to integrate Wakatime MCP with Pydantic AI",
  "toolkit": "Wakatime",
  "toolkit_slug": "wakatime",
  "framework": "Pydantic AI",
  "framework_slug": "pydantic-ai",
  "url": "https://composio.dev/toolkits/wakatime/framework/pydantic-ai",
  "markdown_url": "https://composio.dev/toolkits/wakatime/framework/pydantic-ai.md",
  "updated_at": "2026-05-12T10:29:59.474Z"
}
```

## Introduction

This guide walks you through connecting Wakatime to Pydantic AI 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 Pydantic AI 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)
- [CrewAI](https://composio.dev/toolkits/wakatime/framework/crew-ai)

## TL;DR

Here's what you'll learn:
- How to set up your Composio API key and User ID
- How to create a Composio Tool Router session for Wakatime
- How to attach an MCP Server to a Pydantic AI agent
- How to stream responses and maintain chat history
- How to build a simple REPL-style chat interface to test your Wakatime workflows

## What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.
Key features include:
- Type Safety: Built on Pydantic for automatic data validation
- MCP Support: Native support for Model Context Protocol servers
- Streaming: Built-in support for streaming responses
- Async First: Designed for async/await patterns

## 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 with an active API key
- Basic familiarity with Python and async programming

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) and create an API key. You'll need credits to use the models, or you can connect to another model provider.
- Keep the API key safe.
Composio API Key
- Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Navigate to your API settings and generate a new API key.
- Store this key securely as you'll need it for authentication.

### 2. Install dependencies

Install the required libraries.
What's happening:
- composio connects your agent to external SaaS tools like Wakatime
- pydantic-ai lets you create structured AI agents with tool support
- python-dotenv loads your environment variables securely from a .env file
```bash
pip install composio pydantic-ai python-dotenv
```

### 3. Set up environment variables

Create a .env file in your project root.
What's happening:
- COMPOSIO_API_KEY authenticates your agent to Composio's API
- USER_ID associates your session with your account for secure tool access
- OPENAI_API_KEY to access OpenAI LLMs
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key
```

### 4. Import dependencies

What's happening:
- We load environment variables and import required modules
- Composio manages connections to Wakatime
- MCPServerStreamableHTTP connects to the Wakatime MCP server endpoint
- Agent from Pydantic AI lets you define and run the AI assistant
```python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()
```

### 5. Create a Tool Router Session

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 session.mcp.url is the MCP server URL that your agent will use
```python
async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Wakatime
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["wakatime"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")
```

### 6. Initialize the Pydantic AI Agent

What's happening:
- The MCP client connects to the Wakatime endpoint
- The agent uses GPT-5 to interpret user commands and perform Wakatime operations
- The instructions field defines the agent's role and behavior
```python
# Attach the MCP server to a Pydantic AI Agent
wakatime_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[wakatime_mcp],
    instructions=(
        "You are a Wakatime assistant. Use Wakatime tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
```

### 7. Build the chat interface

What's happening:
- The agent reads input from the terminal and streams its response
- Wakatime API calls happen automatically under the hood
- The model keeps conversation history to maintain context across turns
```python
# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with Wakatime.\n")

while True:
    user_input = input("You: ").strip()
    if user_input.lower() in {"exit", "quit", "bye"}:
        print("\nGoodbye!")
        break
    if not user_input:
        continue

    print("\nAgent is thinking...\n", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()
```

### 8. Run the application

What's happening:
- The asyncio loop launches the agent and keeps it running until you exit
```python
if __name__ == "__main__":
    asyncio.run(main())
```

## Complete Code

```python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Wakatime
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["wakatime"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    wakatime_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[wakatime_mcp],
        instructions=(
            "You are a Wakatime assistant. Use Wakatime tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with Wakatime.\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "bye"}:
            print("\nGoodbye!")
            break
        if not user_input:
            continue

        print("\nAgent is thinking...\n", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

if __name__ == "__main__":
    asyncio.run(main())
```

## Conclusion

You've built a Pydantic AI agent that can interact with Wakatime through Composio's Tool Router. With this setup, your agent can perform real Wakatime actions through natural language.
You can extend this further by:
- Adding other toolkits like Gmail, HubSpot, or Salesforce
- Building a web-based chat interface around this agent
- Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Wakatime for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.

## 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)
- [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 Pydantic AI?

Yes, you can. Pydantic 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 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.

---
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