Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@daylens-mcp show me my focus score for yesterday"
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.
An MCP server that lets Cursor and Claude answer "what was I working on?" from your local Daylens timeline — no cloud, no API keys.
You ask your AI assistant what you did this morning. It guesses.
It doesn't know you spent three hours in Cursor on the auth refactor, or that you context-switched 200 times before lunch. It wasn't there. Daylens was — it logged every session, labeled every work block, scored your focus — but your AI tools can't see any of it.
You shouldn't have to reconstruct your own day from memory just to fill a timesheet or pick up where you left off.
Related MCP server: ProjectMind MCP
Ask in plain language. Get answers grounded in your actual machine:
You › what was I working on this morning?
• 06:40–09:30 (2h 50m) — Tax Filing, Email & Planning
• 09:30–12:57 (3h 26m) — Mixed Development & Research
Top app: Codex | 219 context switches
• 12:57–13:12 (15m) — X.com, YouTube, EmailWorks in Claude Code, Cursor, Claude Desktop, and Windsurf.
Requires Daylens on macOS and Node.js 22+.
Claude Code — one command:
claude mcp add daylens -- npx -y daylens-mcpCursor — add to ~/.cursor/mcp.json:
{
"mcpServers": {
"daylens": {
"command": "npx",
"args": ["-y", "daylens-mcp"]
}
}
}All clients — auto-detects Claude Code, Cursor, Desktop, and Windsurf:
git clone https://github.com/irachrist1/daylens-mcp.git && cd daylens-mcp && bash install.shRestart your client after install.
Read-only bridge. Opens your Daylens SQLite database in read-only mode. Nothing is written, nothing leaves your Mac.
Labeled blocks, not raw logs. Queries AI-labeled work sessions like "Mixed Development & Research" — not "Chrome: 6 hours".
Five tools, natural questions. Timeline, focus stats, app usage, keyword search, and recent activity. Your assistant picks the tool; you just ask.
On demand, no daemon. Starts when your AI client needs it, exits when the session closes. No background process, no network calls.
Pre-computed summaries. Pulls focus scores, streaks, and daily summaries Daylens already computed — fast answers without re-analyzing raw sessions.
MIT License · Built by Christian Tonny
Get a breakdown of which apps you used and for how long. Defaults to today.
| Name | Required | Description | Default |
|---|---|---|---|
| date | No | YYYY-MM-DD. Defaults to today. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the burden of behavioral disclosure. It does add the 'Defaults to today' behavior and specifies that the output is a breakdown of app usage and durations, but it does not explain timezone handling, formatting, permissions, or any potential limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, information-dense sentence with no filler. Every word contributes: it names the verb, the resource, the output, and the default behavior.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one optional parameter and no output schema, this is nearly complete: purpose and default behavior are clear. Minor gaps remain in that it does not describe the exact return format or explicitly differentiate from sibling activity tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already fully documents the single optional 'date' parameter at 100% coverage, including the default value. The description merely repeats 'Defaults to today' and adds no additional semantic detail beyond what the schema states.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb ('Get') and resource ('a breakdown of which apps you used and for how long'). This distinguishes it from siblings like get_timeline or get_recent_activity, which focus on different types of data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The only usage context is 'Defaults to today', which is a time behavior rather than a comparative guideline. It does not state when to prefer this over sibling tools or list any exclusions, though the intended purpose is strongly implied by the tool name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get focus score, active time, and productivity metrics from Daylens. Defaults to today.
| Name | Required | Description | Default |
|---|---|---|---|
| date | No | YYYY-MM-DD. Defaults to today. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden for behavioral disclosure. It states that the tool defaults to today, which is also in the schema, but does not mention read-only behavior, timezone handling, data granularity, or any side effects. For a simple read tool, this is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, direct sentence that front-loads the verb and resource. It avoids redundancy and is appropriately sized for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one optional parameter and no output schema, the description adequately lists the returned metrics (focus score, active time, productivity metrics) and the default behavior. It is not as complete as it could be regarding usage differentiation, but the tool's simplicity lowers the bar.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides 100% coverage for the 'date' parameter with format and default. The description restates the default but adds no new semantics beyond what the schema specifies. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves focus-related metrics ('focus score, active time, productivity metrics') from a specific source ('Daylens'). This distinguishes it from sibling tools like get_timeline (timeline events) and get_app_usage (app usage).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus siblings. The description only mentions a default date, but does not explain when to choose focus stats over timeline, app usage, search, or activity tools. Given multiple sibling tools, this lack of differentiation leaves the agent to guess.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
See what you've been doing in the last N minutes according to Daylens.
| Name | Required | Description | Default |
|---|---|---|---|
| minutes | No | Minutes to look back. Defaults to 60. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must carry the behavioral burden. It implies a read-only operation ('See') but does not disclose return format, data scope, pagination, or any side effects. The description is too thin to inform the agent about the tool's behavior beyond a basic intent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that directly conveys the tool's purpose without redundancy or extraneous detail. It is optimally concise and well-structured for a simple read tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with no output schema, the description gives the essential function and time window. However, it lacks context about what 'activity' includes, the nature of the return value, and differentiation from closely related sibling tools, making it only minimally sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema fully documents the 'minutes' parameter with a description and default value, achieving 100% coverage. The description's phrase 'last N minutes' mirrors the schema without adding new semantic meaning, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves recent user activity over a specified time window ('See what you've been doing in the last N minutes'), using a specific verb and resource. It is concise and understandable, though it does not explicitly distinguish itself from sibling tools like get_timeline or get_app_usage.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidance is provided. The description does not mention when to use this tool versus alternatives, any prerequisites, or scenarios where it would be inappropriate, leaving the agent without direction for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get your Daylens work timeline for a day — labeled work blocks with durations and context. Defaults to today.
| Name | Required | Description | Default |
|---|---|---|---|
| date | No | YYYY-MM-DD. Defaults to today. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the default date behavior and summarizes the output structure, which is useful. However, it does not mention edge cases (e.g., empty timeline), timezone handling, or explicitly state that this is a read-only operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose, and every word adds value. It is concise without sacrificing essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one optional parameter and no output schema, the description adequately explains what the tool returns ('labeled work blocks with durations and context') and its default behavior. It is complete for the agent to select and invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the single parameter 'date' is well-described in the schema. The description adds no additional meaning beyond the schema, merely reinforcing the default. This matches the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') with a clear resource ('Daylens work timeline for a day') and specifies the output ('labeled work blocks with durations and context'). This clearly distinguishes it from sibling tools like get_app_usage or get_recent_activity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description conveys that this tool is for retrieving a daily work timeline and defaults to today, giving clear context for when to use it. It does not explicitly mention when not to use it or name alternatives, but the daily scoping and unique output make the use case evident.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search Daylens work history by app name, label, category, or description.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | Days back to search. Defaults to 7. | |
| query | Yes | Search term. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It adds the specific searchable fields (app name, label, category, description), which is useful context, but it does not disclose any behavioral traits such as read-only nature, result limitations, or pagination. For a simple search tool, this is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no redundancy. Every word contributes to explaining the tool's purpose and scope, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (two params, no output schema) and the existing schema/descriptions, the description is mostly complete. It covers purpose and searchable fields, though it could mention what the return output looks like. Overall, it is sufficient for the complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for both parameters (query and days). The description adds value beyond the schema by specifying the fields the query term matches, which the schema's 'Search term' description does not convey.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific action (Search) on a specific resource (Daylens work history) with the exact fields to search by (app name, label, category, description). This distinguishes it from sibling tools like get_timeline and get_recent_activity, which are not search-based.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage (use when you need to search work history by keywords) but does not explicitly state when to prefer this over alternatives or when not to use it. There are no exclusion scenarios or sibling tool comparisons, so guidance is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v1.0.0get_app_usageget_focus_statsget_recent_activityget_timelinesearch_workScored across 5 tools
Each tool has a distinct purpose: timeline for daily blocks, focus stats for metrics, app usage for breakdown, search for querying history, and recent activity for up-to-the-minute info. No two tools clearly overlap.
Four tools consistently use the get_ prefix (get_timeline, get_focus_stats, get_app_usage, get_recent_activity), but search_work breaks the pattern. While still readable, the inconsistency is mildly noticeable.
Five tools is well-scoped for a personal analytics server, covering the main ways to access Daylens data without being bloated or sparse.
The set covers all the typical read-only needs for a work-tracking service: daily overview, metrics, detailed usage, search, and real-time activity. No obvious gaps for this domain.
Persistent memory for Claude Code and Cursor. Stop re-explaining your project every session.
Let ChatGPT, Claude & Cursor use your Mac: email, calendar, iMessage, Teams, files. Local, free.
Gives your AI assistant persistent memory and intelligence about your work patterns.
Privacy-first work tracking with summaries, reports, coaching, and AI-ready long-term memory.
