How to Use the WakaTime (Coding Stats) MCP in Pydantic AI

Q: What's the easiest way to check my daily coding effort with Pydantic AI?

Call listsummaries. This function pulls together all activity into clean daily totals. The resulting data structure is guaranteed to be correct.

Q: Can I use WakaTime (Coding Stats) with Pydantic AI for compliance reporting?

Yes. You can list commits using listcommits and get a structured record of who worked on what, which is ideal for generating auditable reports.

Q: Does Pydantic AI support tracking multiple coding goals with WakaTime (Coding Stats)?

Yes. It reads all user-defined goals using listgoals and gives you the current progress against each one, ensuring multi-target visibility.

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Connect WakaTime (Coding Stats) MCP to Pydantic AI

Create your Vinkius account to connect WakaTime (Coding Stats) to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup WakaTime (Coding Stats) with Pydantic AI

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Monitor Daily and Goal Progress

To check immediate progress, call `list_summaries` to get daily totals of coding activity. This provides an instant view of effort. You can also list all defined targets and their current standing using `list_goals`, ensuring your agent always validates against set objectives.

Identify Code Activity Blocks

For granular time tracking, the tool retrieves coding activity joined into blocks via `list_durations`. This is better than simple timestamps for understanding deep focus. You can also read which projects are detected by calling `list_projects`, giving context to those tracked durations.

Manage Rules and System Pings

If the rules governing activity tracking change, you update them using `update_custom_rules`. This keeps your system accurate. To check the underlying health of the connection, retrieve raw pings with `list_heartbeats`.

Setup guide

Set up WakaTime (Coding Stats) MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "wakatime-coding-stats-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to WakaTime (Coding Stats) tools.",
)

result = await agent.run("List recent WakaTime (Coding Stats) transactions")
print(result.output)

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Common questions about WakaTime (Coding Stats) MCP in Pydantic AI

It validates every piece of data—whether it’s a project name or a time total—against strict Python models. If the API sends bad data, your agent fails loudly, which is exactly what you want.

Call `list_summaries`. This function pulls together all activity into clean daily totals. The resulting data structure is guaranteed to be correct.

Yes. You can list commits using `list_commits` and get a structured record of who worked on what, which is ideal for generating auditable reports.

Yes. It reads all user-defined goals using `list_goals` and gives you the current progress against each one, ensuring multi-target visibility.

This MCP Server manages raw coding activity pings, project metadata, and external duration records.

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