Wakapi MCP for AI. Audit your development time instantly.
Works with every AI agent you already use
…and any MCP-compatible client








Connect to your AI in seconds.
The Wakapi MCP tracks your coding time and productivity across editors, languages, and projects. It gives you detailed stats on exactly where you spend your development hours, helping managers audit team activity or freelancers bill accurately.
What your AI can do
Send heartbeats
Sends manual activity pings to keep the coding timeline current and accurate for reporting.
List projects
Returns an exhaustive list of all projects that have been tracked by the user.
Get stats
Retrieves specific coding metrics, including languages and editors, for a user.
Gets comprehensive metrics on the languages, editors, and operating systems used over a specific period of work.
Creates granular summaries of your coding efforts for defined time windows or individual projects.
Provides a clear inventory of every project you’ve recorded time against, useful for billing organization.
Sends manual heartbeats to ensure your coding timeline remains accurate even if the primary tracking source fails.
Ask an AI about this
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Wakapi (WakaTime Alternative) 4 Tools
These four tools let your agent get precise details on exactly what you coded, when, and where.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Wakapi (WakaTime Alternative) on VinkiusSend Heartbeats
Sends manual activity pings to keep the coding timeline current and accurate for reporting.
List Projects
Returns an exhaustive list of all projects that have been tracked by the user.
Get Stats
Retrieves specific coding metrics, including languages and editors, for a user.
Get Summaries
Pulls a detailed overview of activity within defined date ranges or project scopes.
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Wakapi (WakaTime Alternative), then connect any of our 5,100+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,100+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Wakapi. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This connection provides 4 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.
The biggest waste of time isn't writing code; it's tracking it.
Right now, reporting your hours means clicking into one dashboard for language usage, then opening a spreadsheet to calculate total project time, and finally manually emailing a summary. You spend more time compiling the report than you do doing the work itself.
This MCP changes that. Your agent reads directly from Wakapi, pulling out exactly what you need—whether it's listing every client project or generating detailed summaries for tax purposes. The data flows instantly to your AI workflow.
Getting Project Inventory with list_projects
Without this, you have to rely on memory or scattered notes just to remember the names of every project you touched over two years. It's a painful manual audit.
Now, running `list_projects` gives you a clean, machine-readable list of everything tracked. You don't forget anything.
What your AI can actually do with this
Need to know how much time you actually spent coding? This connector monitors your entire development workflow by pulling data from your Wakapi instance—a self-hosted alternative to WakaTime. You can get deep stats broken down by language and editor, fetch project summaries for specific date ranges, or just list every project you've ever worked on here.
It’s built for developers who need an accurate picture of their time investment.
When your agent runs this MCP through Vinkius, the platform ensures that every data flow is visible in the Vinkius AI Analytics dashboard. This means you always know exactly which tools were called and what specific activity data was pulled—no black boxes here. It’s simply a way to let your agent read out your actual coding history so you can report time accurately for clients or just track personal growth.
019e3907-f203-7295-adbd-13d4e33adcc7 Here's how it actually works
The bottom line is, it lets your AI agent talk directly to your coding history record.
First, you connect your Wakapi API URL and key credentials to this MCP within Vinkius.
Next, you tell your AI agent what data you need—maybe 'Show me my stats for last month' or 'List all projects.'
The MCP executes the necessary tool call, pulls the activity log from Wakapi, and hands the raw data back to your agent.
Who is this actually for?
Developers who are tired of manually compiling time logs from different sources need this. It’s for anyone whose job requires proving exactly how many hours they spent on a specific language or client project.
Uses the MCP to pull detailed summaries and list projects, ensuring every billable hour is tied to a recorded activity period.
Requests high-level stats for team members or specific project groups without having to manually check multiple internal dashboards.
Checks general coding statistics over long periods just to see where their personal productivity strengths lie (e.g., 'I spend 60% of my time in React').
What Changes When You Connect
Get specific breakdowns of where you spent your time. Use get_stats to see exactly what languages and editors dominated a given period, helping you justify skill sets.
Stop guessing about project scope creep. The list_projects tool gives you an immediate inventory of every single repository or client effort tracked in Wakapi.
Avoid manual reporting headaches. Asking for activity summaries via get_summaries pulls compiled data across dates, giving managers a quick pulse on team velocity.
Ensure continuity when systems fail. Use send_heartbeats to manually log an active coding session if your primary tracking mechanism is down for any reason.
Simplify billing reports. By combining list_projects and get_summaries, you can quickly prove time spent on client-specific deliverables, right from the AI agent.
See it in action
Client Billing Dispute
The client asks for proof of hours worked last month. The developer prompts their agent: 'Get a summary of my activity from October 1st to October 31st.' The agent runs get_summaries and provides the total logged time, breaking it down by project.
Team Performance Review
The engineering manager needs a high-level overview of what languages were most used across the department last quarter. They prompt: 'Show me coding stats for Q3.' The agent calls get_stats and provides a clear, aggregated language breakdown.
Project Scope Definition
The dev team needs to know what projects are active but not currently tracked. They prompt: 'List all my old projects.' The agent runs list_projects, revealing dormant repositories that need re-evaluation.
Debugging Tracking Gaps
The tracking system briefly went offline during a critical coding session. To prevent data loss, the developer manually sends an activity heartbeat using send_heartbeats to mark their continued work period accurately.
The honest tradeoffs
Asking for general productivity tips
Prompting: 'How can I be more productive?' This yields useless, generic advice because the agent doesn't know what data to pull.
You need specific data points. Instead of asking generally, run get_stats and ask: 'What were my top three languages by time last month?' That forces the agent to use the correct tool.
Confusing summary vs. stats
Prompting: 'Give me all my detailed numbers.' The agent might guess and provide a high-level report instead of the deep metrics you need.
If you want specific language breakdowns, use get_stats. If you just need an overall total for a week, use get_summaries.
Assuming all projects are visible
Thinking the agent knows every project name without prompting. The agent will fail to provide a full list.
Always start by running list_projects. This confirms your available data pool before you try to pull stats or summaries for specific jobs.
When It Fits, When It Doesn't
Use this MCP if your primary need is auditing time spent on code, billing clients, or assessing personal development trends. You should use it when you have a specific question about what was coded and when. Don't use it if you just want to know general team morale or high-level strategic goals; for that, talk to a person. If you need a real-time chat transcript analysis (i.e., 'What were the key decisions made in this Slack thread?'), then you need a messaging MCP instead. This tool is purely about development time metrics.
Questions you might have
How do I use get_stats with Wakapi MCP? +
You ask your agent to 'Show my stats for last week.' The agent uses the get_stats tool, which returns a detailed breakdown of languages and editors used during that time.
Can I track multiple projects with get_summaries? +
Yes. You can specify date ranges or even list several project names in your prompt to the agent, letting get_summaries compile a consolidated report for you.
Do I have to run send_heartbeats often? +
No, but it's useful if your main tracking tool goes down temporarily. You use send_heartbeats just to manually log that you were still actively coding and need the time recorded.
What is the difference between get_stats and get_summaries? +
Stats give granular, comparative metrics (like 'X hours in Python vs. Y hours in Rust'). Summaries give a total overview of activity for a given period.
How do I handle permissions or scope when using `list_projects`? +
The MCP requires API credentials that grant read access to all tracked data. If a project isn't visible via list_projects, check your service key permissions first. The tool only shows what the associated Wakapi account has been granted visibility into.
What happens if I run `get_stats` for a time period where no activity was recorded? +
The API returns a clear zero-data response rather than an error. You'll receive confirmation that the user spent 0 hours in the specified range, which is helpful for reporting accurate downtime.
Can I use `send_heartbeats` to correct or modify existing time data? +
No; send_heartbeats only reports new activity and cannot change historical records. It acts as an additive log, ensuring that any gaps in your automated tracking are manually filled in.
What credentials do I need to ensure `get_summaries` works across different time zones? +
You must provide a single API key with global read permissions. The tool handles the time zone conversion internally, so long as your initial query parameters are accurate.
How can I see my coding statistics for the last 7 days? +
You can use the get_stats tool and specify 'last_7_days' as the range. The agent will return a breakdown of your languages, editors, and projects for that period.
Can I get a list of all projects I have ever tracked in Wakapi? +
Yes! Use the list_projects tool. It will retrieve all project names associated with your account, allowing you to see the scope of your tracked work.
Is it possible to track activity for a specific date range? +
Absolutely. Use the get_summaries tool by providing a 'start' and 'end' date in YYYY-MM-DD format. You can even filter this by a specific project name.
We've already built the connector for Wakapi. Just plug in your AI agents and start using Vinkius.
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