How do I get an Everhour API Key?

Log in to your Everhour account, navigate to your user profile settings (top right), and click on **API**. You can find or generate your unique API Key there.

Can the agent start a new timer?

This integration currently focuses on listing and auditing projects, tasks, and time entries. Starting or stopping live timers should be performed via the Everhour browser extension or mobile app.

Does the integration show real-time budget usage?

Yes, you can use the list_projects_within_budget tool to retrieve current budget utilization rates and identify projects that are approaching their limits.

Everhour Time Tracking MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Everhour Time Tracking
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Everhour Time Tracking through the Vinkius and every tool is automatically validated against Pydantic schemas — catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Everhour Time Tracking "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Everhour Time Tracking?"
    )
    print(result.data)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Everhour Time Tracking MCP Server

Integrate Everhour, the powerful time tracking and project management software, directly into your AI workflow. Manage your projects and tasks, track real-time time entries and team productivity, monitor project budgets and billing status, and oversee your entire team's workload using natural language.

Pydantic AI validates every Everhour Time Tracking tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through the Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code — full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Project Oversight — List and retrieve detailed information, budgets, and status for all your tracked projects.
Time Intelligence — Monitor team time records, resolving task IDs, durations, and active user timers in real-time.
Budget Management — Access and monitor project budgets, identifying utilization rates and identifying projects at risk of exceeding limits.
Productivity Auditing — Retrieve high-level summaries of recent time entries, task completion, and organizational account health instantly.

The Everhour Time Tracking MCP Server exposes 10 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Everhour Time Tracking to Pydantic AI via MCP

Follow these steps to integrate the Everhour Time Tracking MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 10 tools from Everhour Time Tracking with type-safe schemas

Why Use Pydantic AI with the Everhour Time Tracking MCP Server

Pydantic AI provides unique advantages when paired with Everhour Time Tracking through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture — switch between OpenAI, Anthropic, or Gemini without changing your Everhour Time Tracking integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Everhour Time Tracking connection logic from agent behavior for testable, maintainable code

Everhour Time Tracking + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Everhour Time Tracking MCP Server delivers measurable value.

Type-safe data pipelines: query Everhour Time Tracking with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Everhour Time Tracking tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Everhour Time Tracking and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Everhour Time Tracking responses and write comprehensive agent tests

Everhour Time Tracking MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Everhour Time Tracking to Pydantic AI via MCP:

get_currently_running_timer

Retrieve the task and start time for any currently active timer

get_everhour_user_metadata

Retrieve metadata and profile information for the current Everhour user

get_project_detailed_data

Get detailed settings and budget information for a specific project

list_billing_clients

List all clients configured for project billing and invoicing

list_organization_team_members

List all team members and their roles in the organization

list_project_tasks

List all tasks within a specific project

list_projects_within_budget

Identify projects that are currently within their assigned time or monetary budget

list_team_time_records

List time records for the team within a specific date range

list_tracked_projects

List all projects managed in your Everhour account

quick_time_tracking_audit

Retrieve a high-level summary of recent time entries and active projects

Example Prompts for Everhour Time Tracking in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Everhour Time Tracking immediately.

"List all projects currently over budget."

"Show me the tasks for project 'Mobile App'."

"What is the team productivity summary for this week?"

Troubleshooting Everhour Time Tracking MCP Server with Pydantic AI

Common issues when connecting Everhour Time Tracking to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Everhour Time Tracking + Pydantic AI FAQ

Common questions about integrating Everhour Time Tracking MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer — your Everhour Time Tracking MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.