What can you do with this server?

This server connects LLMs like Claude to your ActivityWatch time tracking data, allowing you to interact with your personal activity history. Capabilities: * List Buckets: View all available ActivityWatch buckets with optional type filtering. * Run Queries: Execute ActivityWatch Query Language (AQL) queries with parameters for time periods. * Get Raw Events: Retrieve raw events from specific buckets with options for date range and limits. * Get Settings: Access ActivityWatch configuration settings, either all or for a specific key. * Query Examples: Access examples of properly formatted queries for reference.

How do I use ActivityWatch MCP Server?

1. Click on "Deploy Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@ActivityWatch MCP Server what applications have I used the most today?" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

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ActivityWatch MCP Server

by 8bitgentleman

Overview Schema Source Related Servers Discussions Admin

TypeScript

Local

ActivityWatch MCP Server

A Model Context Protocol (MCP) server that connects to ActivityWatch, allowing LLMs like Claude to interact with your time tracking data.

Features

List Buckets: View all available ActivityWatch buckets
Run Queries: Execute powerful AQL (ActivityWatch Query Language) queries
Get Raw Events: Retrieve events directly from any bucket
Get Settings: Access ActivityWatch configuration settings

Related MCP server: Paprika SQL MCP Server

Installation

You can install the ActivityWatch MCP server either from npm or by building it yourself.

Installing from npm (coming soon)

# Global installation
npm install -g activitywatch-mcp-server

# Or install locally
npm install activitywatch-mcp-server

Building from Source

Clone this repository:

git clone https://github.com/8bitgentleman/activitywatch-mcp-server.git
cd activitywatch-mcp-server

Install dependencies:
```
npm install
```
Build the project:
```
npm run build
```

Prerequisites

ActivityWatch installed and running
Node.js (v14 or higher)
Claude for Desktop (or any other MCP client)

Usage

Using with Claude for Desktop

Open your Claude for Desktop configuration file:
- Windows: %APPDATA%\Claude\claude_desktop_config.json
- macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

Add the MCP server configuration:

{
"mcpServers": {
    "activitywatch": {
    "command": "activitywatch-mcp-server",
    "args": []
    }
}
}

If you built from source, use:

{
"mcpServers": {
    "activitywatch": {
    "command": "node",
    "args": ["/path/to/activitywatch-mcp-server/dist/index.js"]
    }
}
}

Restart Claude for Desktop
Look for the MCP icon in Claude's interface to confirm it's working

Using a rootless podman container on Linux with Gemini CLI

Make sure to build the image first with:

version=$(npm pkg get version | tr -d '"')
podman build . -t activitywatch-mcp-server:${version}

This example uses the override for Activity Watch not being available on 127.0.0.1 (see next section). If not required, you may omit the AW_API_BASE environment variable.

{
  "mcpServers": {
    "activitywatch-mcp-server": {
      "command": "/usr/bin/podman",
      "args": [
        "run",
        "--rm",
        "--interactive",
        "--userns=keep-id",
        "-e",
        "AW_API_BASE",
        "localhost/activitywatch-mcp-server:1.2.1"
      ],
      "env": {
        "AW_API_BASE": "http://mydesktop.local:5600/api/0"
      }
    }
  }
}

Override ActivityWatch server host/port

If you want to run this MCP server from inside Windows Subsystem for Linux, for instance within a container, the AW server running in Windows will not be available at 127.0.0.1. To override the standard localhost connection, use the environment variable AW_API_BASE or the --aw-api-base flag, as below:

# Using environment variable
export AW_API_BASE=http://mydesktop.local:5600/api/0
node dist/index.js

# Or using command-line flag
node dist/index.js --aw-api-base=http://mydesktop.local:5600/api/0

NOTE: The AW server may be fussy about the name used to connect to it, but it will accept a name that matches the computer name where it is running with a .local suffix.

Example Queries

Here are some example queries you can try in Claude:

List all your buckets: "What ActivityWatch buckets do I have?"
Get application usage summary: "Can you show me which applications I've used the most today?"
View browsing history: "What websites have I spent the most time on today?"
Check productivity: "How much time have I spent in productivity apps today?"
View settings: "What are my ActivityWatch settings?" or "Can you check a specific setting in ActivityWatch?"

Available Tools

list-buckets

Lists all available ActivityWatch buckets with optional type filtering.

Parameters:

type (optional): Filter buckets by type (e.g., "window", "web", "afk")
includeData (optional): Include bucket data in response

run-query

Run a query in ActivityWatch's query language (AQL).

Parameters:

timeperiods: Time period(s) to query formatted as array of strings. For date ranges, use format: ["2024-10-28/2024-10-29"]
query: Array of query statements in ActivityWatch Query Language, where each item is a complete query with statements separated by semicolons
name (optional): Name for the query (used for caching)

IMPORTANT: Each query string should contain a complete query with multiple statements separated by semicolons.

Example request format:

{
  "timeperiods": ["2024-10-28/2024-10-29"],
  "query": ["events = query_bucket('aw-watcher-window_UNI-qUxy6XHnLkk'); RETURN = events;"]
}

Note that:

timeperiods should have pre-formatted date ranges with slashes
Each item in the query array is a complete query with all statements

get-events

Get raw events from an ActivityWatch bucket.

Parameters:

bucketId: ID of the bucket to fetch events from
start (optional): Start date/time in ISO format
end (optional): End date/time in ISO format
limit (optional): Maximum number of events to return

get-settings

Get ActivityWatch settings from the server.

Parameters:

key (optional): Get a specific settings key instead of all settings

Query Language Examples

ActivityWatch uses a simple query language. Here are some common patterns:

// Get window events
window_events = query_bucket(find_bucket("aw-watcher-window_"));
RETURN = window_events;

// Get only when not AFK
afk_events = query_bucket(find_bucket("aw-watcher-afk_"));
not_afk = filter_keyvals(afk_events, "status", ["not-afk"]);
window_events = filter_period_intersect(window_events, not_afk);
RETURN = window_events;

// Group by app
window_events = query_bucket(find_bucket("aw-watcher-window_"));
events_by_app = merge_events_by_keys(window_events, ["app"]);
RETURN = sort_by_duration(events_by_app);

// Filter by app name
window_events = query_bucket(find_bucket("aw-watcher-window_"));
code_events = filter_keyvals(window_events, "app", ["Code"]);
RETURN = code_events;

Configuration

The server connects to the ActivityWatch API at http://localhost:5600 by default. If your ActivityWatch instance is running on a different host or port, you can override it as described in the Override ActivityWatch server host/port section above.

Troubleshooting

ActivityWatch Not Running

If ActivityWatch isn't running, the server will show connection errors. Make sure ActivityWatch is running and accessible at the specified host/port address (http://localhost:5600 unless you have overridden it).

Query Errors

If you're encountering query errors:

Check your query syntax
Make sure the bucket IDs are correct
Verify that the timeperiods contain data
Check ActivityWatch logs for more details

Claude/MCP Query Formatting Issues

If Claude reports errors when running queries through this MCP server, it's likely due to formatting issues. Make sure your query follows this exact format in your prompts:

{
  "timeperiods": ["2024-10-28/2024-10-29"],
  "query": ["events = query_bucket('aw-watcher-window_UNI-qUxy6XHnLkk'); RETURN = events;"]
}

Common issues:

Time periods not formatted correctly (should be "start/end" in a single string within an array)
Query statements split into separate array elements instead of being combined in one string

The Most Common Formatting Issue

The most frequent error is when Claude splits each query statement into its own array element like this:

{
  "query": [
    "browser_events = query_bucket('aw-watcher-web');",
    "afk_events = query_bucket('aw-watcher-afk');",
    "RETURN = events;"
  ],
  "timeperiods": ["2024-10-28/2024-10-29"]
}

This is INCORRECT. Instead, all statements should be in a single string within the array:

{
  "timeperiods": ["2024-10-28/2024-10-29"],
  "query": ["browser_events = query_bucket('aw-watcher-web'); afk_events = query_bucket('aw-watcher-afk'); RETURN = events;"]
}

When Prompting Claude

When prompting Claude, be very explicit about the format and use examples. For instance, say:

"Run a query with timeperiods as ["2024-10-28/2024-10-29"] and query as ["statement1; statement2; RETURN = result;"]. Important: Make sure ALL query statements are in a single string within the array, not split into separate array elements."

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT

Available Tools

5 tools

activitywatch_get_eventsC

Get raw events from an ActivityWatch bucket

ParametersJSON Schema

Name	Required	Description
`bucketId`	Yes	ID of the bucket to fetch events from
`limit`	No	Maximum number of events to return (default: 100)
`start`	No	Start date/time in ISO format (e.g. '2024-02-01T00:00:00Z')
`end`	No	End date/time in ISO format (e.g. '2024-02-28T23:59:59Z')

TDQS

C2.9/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure but offers minimal information. It doesn't mention whether this is a read-only operation, if it requires authentication, potential rate limits, error conditions, or what format the 'raw events' are returned in. The description is functionally adequate but lacks important operational context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise - a single sentence that communicates the essential purpose without any wasted words. It's front-loaded with the core functionality and doesn't include unnecessary elaboration, making it efficient for quick understanding.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 4 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what 'raw events' means in terms of data structure, doesn't mention any limitations or constraints, and provides no context about the ActivityWatch system. The agent would need to guess about the return format and operational characteristics.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 100% schema description coverage, the input schema already documents all 4 parameters thoroughly. The description adds no additional parameter information beyond what's in the schema, so it meets the baseline expectation but doesn't provide extra value regarding parameter usage or semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Get raw events') and resource ('from an ActivityWatch bucket'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'activitywatch_query_examples' or 'activitywatch_run_query', which might also retrieve event data but with different approaches or formats.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With sibling tools like 'activitywatch_query_examples' and 'activitywatch_run_query' that might serve similar purposes, there's no indication of when this raw event retrieval is preferred over those query-based approaches, leaving the agent without context for selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

activitywatch_get_settingsB

Get ActivityWatch settings. Can retrieve all settings or a specific key if provided.

ParametersJSON Schema

Name	Required	Description	Default
`key`	No	Optional: Get a specific settings key instead of all settings

TDQS

B3.2/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It states the tool retrieves settings but doesn't disclose behavioral traits such as whether it's read-only (implied by 'Get'), authentication needs, rate limits, error handling, or response format. The description is minimal and lacks necessary context for safe and effective use.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized with two concise sentences that are front-loaded and waste-free. It efficiently communicates the core functionality and parameter usage without unnecessary details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations, no output schema, and a simple input schema, the description is incomplete. It doesn't explain what settings are returned, their structure, or any behavioral aspects like permissions or errors. For a tool with zero annotation coverage, more context is needed for adequate agent understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents the optional 'key' parameter. The description adds marginal value by mentioning 'a specific key if provided,' but doesn't provide additional semantics like key examples, format, or constraints beyond what the schema states.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('Get') and resource ('ActivityWatch settings'), and distinguishes between retrieving all settings or a specific key. However, it doesn't explicitly differentiate from sibling tools like 'activitywatch_get_events' or 'activitywatch_list_buckets' beyond the resource name.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage by mentioning 'all settings or a specific key if provided,' which suggests when to use the optional parameter. However, it lacks explicit guidance on when to choose this tool over siblings (e.g., vs. 'activitywatch_get_events') or any prerequisites or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

activitywatch_list_bucketsB

List all ActivityWatch buckets with optional type filtering

ParametersJSON Schema

Name	Required	Description	Default
`type`	No	Filter buckets by type
`includeData`	No	Include bucket data in response

TDQS

B3.1/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states it's a list operation with optional filtering, implying it's likely read-only and non-destructive, but doesn't confirm this or address other behavioral aspects like permissions needed, rate limits, pagination, error handling, or what 'includeData' entails. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose ('List all ActivityWatch buckets') and adds a concise modifier ('with optional type filtering'). There is no wasted verbiage, repetition, or unnecessary elaboration, making it easy to parse and understand quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is adequate but incomplete. It covers the basic action and hints at filtering, but lacks details on behavioral traits, usage context, or output expectations. Without annotations or output schema, the agent must infer behavior from the description alone, which is insufficient for confident tool selection in varied scenarios.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents both parameters ('type' for filtering and 'includeData' for including bucket data). The description adds minimal value by mentioning 'optional type filtering,' which aligns with the schema but doesn't provide additional context like example types or implications of including data. With high schema coverage, the baseline is 3, and the description doesn't significantly enhance parameter understanding beyond what's structured.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('List all ActivityWatch buckets') and resource ('ActivityWatch buckets'), making the purpose immediately understandable. It distinguishes itself from siblings like 'activitywatch_get_events' by focusing on buckets rather than events, though it doesn't explicitly contrast with other bucket-related tools (none exist in the sibling list). The optional filtering aspect adds specificity beyond a basic list operation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It mentions optional type filtering but doesn't explain scenarios where filtering is beneficial or when to choose this over other tools like 'activitywatch_query_examples' or 'activitywatch_run_query' for bucket-related tasks. There are no prerequisites, exclusions, or contextual recommendations provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

activitywatch_query_examplesB

Get examples of properly formatted queries for the ActivityWatch MCP server

ParametersJSON Schema

Name	Required	Description	Default
No parameters

TDQS

B3.2/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'gets examples,' implying a read-only operation, but doesn't clarify if this requires authentication, has rate limits, returns structured data, or involves any side effects. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior and constraints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence: 'Get examples of properly formatted queries for the ActivityWatch MCP server.' It is front-loaded with the core action ('Get examples') and specifies the context ('for the ActivityWatch MCP server'), with zero wasted words. This makes it highly efficient and easy for an agent to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is adequate but has gaps. It explains what the tool does but lacks behavioral details (e.g., response format, authentication needs) and usage guidelines relative to siblings. Without an output schema, it doesn't describe return values, which could hinder an agent's understanding of how to use the examples provided.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters, and the input schema has 100% description coverage (though empty). The description doesn't need to explain parameters, as there are none. It appropriately focuses on the tool's purpose without redundant parameter details, earning a high baseline score for parameter semantics in this context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Get examples of properly formatted queries for the ActivityWatch MCP server.' It uses a specific verb ('Get') and identifies the resource ('examples of properly formatted queries'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'activitywatch_run_query' or 'activitywatch_get_events,' which prevents a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing to understand query syntax before using 'activitywatch_run_query'), exclusions, or contextual cues. Without such information, an agent might struggle to choose between this and sibling tools like 'activitywatch_run_query' or 'activitywatch_get_events.'

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

activitywatch_run_queryC

Run a query in ActivityWatch's query language

ParametersJSON Schema

Name	Required	Description
`timeperiods`	Yes	Time periods to query. Format: ['2024-10-28/2024-10-29'] where dates are in ISO format and joined with a slash
`query`	Yes	MUST BE A SINGLE STRING containing all query statements separated by semicolons. DO NOT split into multiple strings.
`name`	No	Optional name for the query (used for caching)

TDQS

C2.9/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure but only states the basic action. It doesn't mention whether this is a read-only operation, if it requires specific permissions, potential side effects, rate limits, or what the output looks like (especially critical since there's no output schema). This leaves significant gaps for a query execution tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that states the core purpose without any wasted words. It's appropriately sized for a tool with well-documented parameters and gets straight to the point, making it easy for an agent to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a query execution tool with no annotations and no output schema, the description is insufficient. It doesn't explain what kind of results to expect, error conditions, or behavioral constraints. Given the complexity of running queries and the lack of structured output documentation, more context about the operation's nature and results is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds no parameter information beyond what's already in the schema (which has 100% coverage). While the schema thoroughly documents all three parameters with formats, constraints, and examples, the description doesn't provide additional context about parameter relationships or usage semantics, meeting the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Run a query') and the resource ('in ActivityWatch's query language'), which is specific and unambiguous. However, it doesn't explicitly differentiate this tool from its sibling 'activitywatch_query_examples', which might cause confusion about when to use each.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'activitywatch_get_events' or 'activitywatch_query_examples'. There's no mention of prerequisites, appropriate contexts, or exclusions, leaving the agent to infer usage from the tool name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

5 tool updatesv1.0.0Jan 2, 2026
- Addedactivitywatch_get_events
- Addedactivitywatch_get_settings
- Addedactivitywatch_list_buckets
- Addedactivitywatch_query_examples
- Addedactivitywatch_run_query

Deploy Server

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A3.5/5.0

Scored 2026-04-18 11:35 across 5 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: get_events retrieves raw event data, get_settings accesses configuration, list_buckets enumerates available data containers, query_examples provides documentation, and run_query executes queries. There is no overlap in functionality that would cause agent confusion.

Naming Consistency5/5

All tools follow a consistent 'activitywatch_verb_noun' pattern with snake_case throughout. The verbs (get, list, run) are appropriately descriptive and maintain a uniform naming convention across all five tools.

Tool Count5/5

With 5 tools, this server is well-scoped for interacting with ActivityWatch data. The count is appropriate for the domain, covering core operations like data retrieval, configuration access, and query execution without being overwhelming or insufficient.

Completeness4/5

The toolset provides solid coverage for querying and inspecting ActivityWatch data, including examples for guidance. A minor gap exists in write operations (e.g., creating or modifying buckets/events), but the available tools support most common read and query workflows effectively.

Maintenance

ActivityInactive

ResponsivenessNo issues

Resources

GitHub Repository

Need Help?

Reddit Discussion

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ActivityWatch MCP Server

Features

Installation

Installing from npm (coming soon)

Building from Source

Prerequisites

Usage

Using with Claude for Desktop

Using a rootless podman container on Linux with Gemini CLI

Override ActivityWatch server host/port

Example Queries

Available Tools

list-buckets

run-query

get-events

get-settings

Query Language Examples

Configuration

Troubleshooting

ActivityWatch Not Running

Query Errors

Claude/MCP Query Formatting Issues

The Most Common Formatting Issue

When Prompting Claude

Contributing

License

Available Tools

Tool Schema Changelog

Maintenance

Resources

Related MCP Connectors

Related MCP Servers

TripleWhale MCP Serverofficial

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