WakaTime (Coding Stats) MCP. Know exactly how long you spent on every line of code.
WakaTime (Coding Stats) MCP connects your coding data to your agent. Get detailed stats showing total time spent across specific date ranges, track progress against custom goals, and list every project your IDE has recorded activity for.
Give Claude and any AI agent real-world access
Retrieve total coding hours logged since your WakaTime account was created.
Fetch summarized coding statistics for custom date ranges like the last 7 or 30 days.
See a list of your defined coding targets and review your current percentage completion for any goal.
Get a comprehensive list of every detected project, along with daily time summaries for each one.
Inspect raw coding pings and duration blocks to understand exact start times and gaps in your work sessions.
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What AI agents can do with WakaTime (Coding Stats): 14 Tools
These tools allow your agent to access every facet of your coding history—from raw heartbeats to high-level goal tracking.
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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 WakaTime (Coding Stats) MCPCreate External Duration
Records activity time that came from outside your IDE, like a calendar entry.
Create Heartbeat
Sends a raw ping to record immediate coding activity when you start working.
Get All Time Since Today
Retrieves the total amount of time logged across all projects since your account was...
Get Goal
Pulls specific details about a user-defined coding goal you set up.
Get Stats
Gathers summarized coding statistics for any given date range.
List Commits
Lists project commits and shows exactly how much time you spent on each one.
List Custom Rules
Shows you the rules currently set up to modify or remove coding activity records.
List Durations
Retrieves blocks of coding time that were joined together after a pause in typing.
List External Durations
Gets activity time that was imported from external applications, such as Google...
List Goals
Displays a list of all coding goals you have set and how close you are to hitting...
List Heartbeats
Retrieves the raw, ping-level data showing every instance you started coding in your...
List Projects
Lists every unique project that has generated activity on your system.
List Summaries
Provides daily summaries of all recorded coding activity.
Update Custom Rules
Allows you to change the rules that modify or delete your coding activity data based...
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Tracking developer time used to feel like cross-referencing spreadsheets.
Right now, if a manager wants to know where the team spent their last month, someone has to manually go through dashboards, export CSVs for each project, and then spend hours compiling those into one readable report. It's tedious work that introduces human error every single time.
With this MCP, you tell your agent what you need—for example, 'Show me the total effort on Project X versus Project Y last quarter.' The agent accesses all the underlying data streams and delivers a clean, summarized comparison instantly. You get actionable insight without touching a spreadsheet.
Get WakaTime (Coding Stats) MCP to list project time & goals
The need to manually compile daily activity logs and reconcile external meeting times with core coding hours disappears. You don't have to correlate data between your IDE plugins, calendar apps, and task trackers anymore.
Your agent reads the complexity out of the process. It turns scattered raw keystrokes into structured, reportable intelligence at a single prompt.
What WakaTime (Coding Stats) MCP does for your AI
Need to know where you actually spend your development hours? This MCP analyzes the raw data from your IDE, giving you a clear picture of your coding habits without manual effort. You can ask your agent for summarized statistics—say, total time logged over the last 30 days—or track how far along you are with specific personal goals.
It also lists every project your plugins detect, providing daily activity totals per workspace. If your work involves external apps like Google Calendar, it even pulls that data in so nothing slips through the cracks. Connecting WakaTime to Vinkius lets your agent use this MCP and synthesize all that complex time logging into a simple conversation.
It’s pure insight: you get an objective view of who's working on what, right when you need to know.
019e3908-2156-728b-85e9-d1f72c6a6dc6 How to set up WakaTime (Coding Stats) MCP
The bottom line is you talk to your agent about your code time, and it pulls all the detailed data for you.
Subscribe to this MCP and provide your unique WakaTime API key.
Your agent connects the credentials and prepares access to your coding history.
You ask a natural language question—like 'How long did I work on the backend last month?'—and get an immediate, summarized answer.
Who uses WakaTime (Coding Stats) MCP
This MCP is essential for developers who need objective proof of their effort or team leads tired of chasing manual progress reports. It cuts through guesswork and gives hard numbers on where time actually goes.
Uses this to track personal productivity, identifying which specific projects consume the bulk of their coding time.
Monitors high-level project activity and goal progress across multiple team members without having to collect reports manually.
Analyzes coding patterns and historical heartbeats to recommend process optimizations or skill focus areas for a client.
Benefits of connecting WakaTime (Coding Stats) MCP
Pinpoint wasted time. Use 'get_stats' to check specific date ranges and see if your coding hours align with where you thought they did.
Manage expectations. Check progress against custom targets using the 'list_goals' tool so team leads can report on goals, not just effort.
Visualize your work flow. The 'list_projects' function gives an immediate overview of all tracked projects and how much time was spent in each one.
Account for everything. If you track non-coding tasks like meetings in Google Calendar, the 'list_external_durations' tool makes sure that time is included.
Analyze the nitty-gritty. Need to know exactly when your agent saw you stop typing? The 'list_heartbeats' tool gives raw ping data for deep analysis.
WakaTime (Coding Stats) MCP use cases
The Scope Creep Audit
A team lead asks their agent, 'Show me the total time spent on Project Alpha versus Project Beta last quarter.' The agent runs the query using 'get_stats' and delivers a clear comparison, instantly identifying where focus drifted.
The Performance Review Prep
A developer needs to prove they hit their quarterly goals. They ask for their progress against all targets using 'list_goals', getting a comprehensive report that confirms 95% completion on their main objective.
Debugging Time Loss
A consultant suspects the team is losing time between coding sessions. They run the raw activity data via 'list_heartbeats' and review the gaps, pinpointing exactly where the workflow breaks down.
Cross-Functional Reporting
A developer needs to include meeting hours in their productivity report. Instead of manually logging it, they let the agent use 'list_external_durations' to pull verified time from their calendar.
WakaTime (Coding Stats) MCP tradeoffs
What to watch out for, and the recommended way to handle each one.
Assuming activity is constant
Thinking that because you wrote a lot of code last week, your agent will automatically know the hours. You might just ask for 'last week's stats,' which is too vague.
Be specific with date ranges. Use the 'get_stats' tool and tell your agent exactly what dates to cover (e.g., 'from 2024-10-01 to 2024-10-31') for accurate results.
Ignoring non-coding time
Running a simple query that only looks at keystrokes, which completely misses the hours you spent in related tools like Jira or calendar meetings.
Always include external data. Use 'list_external_durations' to pull verified activity from apps outside of your IDE.
Overlooking project boundaries
Asking for a general total time without filtering by specific projects, resulting in one massive number that tells you nothing about focus.
Use 'list_projects' first to see all options, then ask the agent to summarize stats for just the most relevant area.
When to use WakaTime (Coding Stats) MCP
Use this MCP if your primary need is objective, quantitative proof of effort. If you are a developer trying to justify time spent or track granular progress against measurable goals, this is it. You're looking at hard metrics: hours logged per project, total duration in specific date windows, and goal completion percentages.
Don't use this if you need qualitative feedback (e.g., 'Was the code clean?' or 'Is this feature cool?'). This MCP only handles time tracking data. If your problem is coordinating people or brainstorming solutions, a communication tool or a different type of agent will work better. You should use this when you want to measure what was done and for how long, not how good it was.
Frequently asked questions about WakaTime (Coding Stats) MCP
How do I use WakaTime (Coding Stats) MCP to check my total time? +
You ask your agent for the 'get_all_time_since_today' statistic. It provides one single number representing every minute logged since you first connected your account.
Can I track external work hours with WakaTime (Coding Stats) MCP? +
Yes, the 'list_external_durations' tool pulls activity from sources like Google Calendar. This ensures non-coding time is included in your overall picture.
What does list_heartbeats do with WakaTime (Coding Stats) MCP? +
The 'list_heartbeats' tool retrieves the raw, minute-by-minute ping data from your IDE plugins. This is useful for forensic analysis of when work activity truly began and ended.
How do I compare projects using WakaTime (Coding Stats) MCP? +
You can use the 'list_projects' tool to see all options, then ask your agent to run a summary query against those specific project names. This gives you clear time allocations.
Can I update my coding rules with WakaTime (Coding Stats) MCP? +
Yes, the 'update_custom_rules' tool lets you adjust how WakaTime processes your activity data. You can modify patterns to ensure only relevant time is counted.