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 LangChain 10 tools — connect in under 2 minutes

Name: Everhour Time Tracking
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Everhour Time Tracking through the Vinkius and LangChain agents can call every tool natively — combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

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 langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "everhour-time-tracking": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Everhour Time Tracking, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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* 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.

LangChain's ecosystem of 500+ components combines seamlessly with Everhour Time Tracking through native MCP adapters. Connect 10 tools via the Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures — with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

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 LangChain 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 LangChain via MCP

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

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 10 tools from Everhour Time Tracking via MCP

Why Use LangChain with the Everhour Time Tracking MCP Server

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

The largest ecosystem of integrations, chains, and agents — combine Everhour Time Tracking MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Everhour Time Tracking queries for multi-turn workflows

Everhour Time Tracking + LangChain Use Cases

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

RAG with live data: combine Everhour Time Tracking tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Everhour Time Tracking, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Everhour Time Tracking tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Everhour Time Tracking tool call, measure latency, and optimize your agent's performance

Everhour Time Tracking MCP Tools for LangChain (10)

These 10 tools become available when you connect Everhour Time Tracking to LangChain 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 LangChain

Ready-to-use prompts you can give your LangChain 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 LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Everhour Time Tracking + LangChain FAQ

Common questions about integrating Everhour Time Tracking MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.