{"$schema":"https://wellknown.network/schemas/agent-record-v1.json","schemaVersion":"1","id":"ag_gkyzga4f38bw","handle":"timedoctor-mcp","url":"https://wellknown.network/agents/timedoctor-mcp","links":{"self":"https://wellknown.network/agents/timedoctor-mcp/record.json","html":"https://wellknown.network/agents/timedoctor-mcp","markdown":"https://wellknown.network/agents/timedoctor-mcp/record.md","api":"https://wellknown.network/api/v1/agents/timedoctor-mcp","status":"https://wellknown.network/api/v1/agents/timedoctor-mcp/status","claim":"https://wellknown.network/agents/timedoctor-mcp/claim","claimApi":"https://wellknown.network/api/v1/claims","claimDescriptor":"https://wellknown.network/agents/timedoctor-mcp/claim.json","badge":"https://wellknown.network/agents/timedoctor-mcp/badge.svg","openapi":"https://wellknown.network/openapi.json","history":"https://wellknown.network/api/v1/agents/timedoctor-mcp/history","tools":"https://wellknown.network/api/v1/agents/timedoctor-mcp/tools"},"ard":{"identifier":"urn:air::server:timedoctor-mcp","type":"application/mcp-server-card+json"},"kind":"mcp_server","declared":{"name":"timedoctor-mcp","summary":"MCP Server for extracting Time Doctor time tracking data via AI assistants","description":"# Time Doctor MCP\n\n**MCP Server** for extracting Time Doctor time tracking data via AI assistants.\n\n[![Buy Me A Coffee](https://img.shields.io/badge/Buy%20Me%20A%20Coffee-Support-yellow?style=flat-square&logo=buy-me-a-coffee)](https://buymeacoffee.com/frifster)\n\n## What It Does\n\nFetches time tracking reports from Time Doctor and returns them as CSV data. Integrates with AI assistants via the Model Context Protocol (MCP).\n\n**Supports:**\n- 🤖 Claude Desktop & Claude Code\n- 🎯 Cursor IDE\n- ✨ Google Gemini CLI\n- 💻 VS Code with GitHub Copilot\n\n**Features:**\n- 🚀 Single-session scraping (login once, get multiple dates)\n- 📅 Works with any date range (1 day to 365+ days)\n- 📊 Returns CSV data as text (no file system issues)\n- ⏱️ Parses Time Doctor's \"3h 50m\" format\n- 📦 Aggregates duplicate tasks\n- ✅ Includes TOTAL row\n\n## Installation Methods\n\n### Option A: Using uvx (Easiest - No Installation Required)\n\nThe simplest way to use Time Doctor MCP is with `uvx`, which automatically downloads the package from PyPI and runs it locally without manual installation:\n\n**Claude Desktop/Code:**\n```json\n{\n  \"mcpServers\": {\n    \"timedoctor\": {\n      \"command\": \"uvx\",\n      \"args\": [\"timedoctor-mcp\"],\n      \"env\": {\n        \"TD_EMAIL\": \"your-email@example.com\",\n        \"TD_PASSWORD\": \"your-password\",\n        \"TD_BASE_URL\": \"https://2.timedoctor.com\",\n        \"HEADLESS\": \"true\"\n      }\n    }\n  }\n}\n```\n\n**Prerequisites:**\n1. Install uv: `brew install uv` (macOS) or see [uv installation](https://docs.astral.sh/uv/)\n2. Install Playwright browsers (one-time setup):\n   ```bash\n   uvx --with playwright playwright install chromium\n   ```\n\n   This downloads the Chromium browser binaries needed for web scraping (~130MB). You only need to run this once.\n\n**That's it!** No cloning, no virtual environments, no setup scripts. Just add the configuration and restart your AI assistant.\n\n### Option B: Clone & Install (For Development)\n\n```bash\n# Clone the repository\ngit clone https://github.com/frifste…","publisher":null,"homepage":"https://github.com/frifster/timedoctor-mcp","repository":"https://github.com/frifster/timedoctor-mcp","version":"1.3.0","license":"MIT","protocols":["mcp"],"tags":["ai","claude","cursor","gemini","mcp","time-doctor","time-tracking"],"pricing":null,"endpoints":[{"url":"pypi:timedoctor-mcp","type":"package_pypi","auth":null,"probeable":false}],"skills":null,"tools":null,"extra":null,"attribution":{"kind":"pypi","name":"pypi","license":"pypi","repoUrl":"pypi","summary":"pypi","version":"pypi","description":"pypi","homepageUrl":"pypi"}},"derived":{"capabilities":[{"slug":"dev.version-control","name":"Version Control","confidence":1,"provenance":"derived"},{"slug":"infra.browser-automation","name":"Browser Automation","confidence":1,"provenance":"derived"},{"slug":"dev.package-management","name":"Packages & Dependencies","confidence":0.768,"provenance":"derived"}],"categories":["dev","infra"],"language":"en"},"observed":{"status":"unknown","statusReason":"Distributed as a package to run locally; no network endpoint to check.","lastOkAt":null,"lastProbedAt":null,"statusComputedAt":null,"reliability30d":null,"latestObservations":[],"tools":null,"package":{"name":"timedoctor-mcp","registry":"pypi","observedAt":"2026-11-10T04:24:13.817Z","publishedAt":"2025-11-07T00:15:38.170839Z","latestVersion":"1.3.0"},"toolSurface":null,"endpointFacts":[]},"verification":{"claimed":false,"claimedAt":null,"proofs":[]},"provenance":{"sources":[{"source":"pypi","key":"timedoctor-mcp","url":"https://pypi.org/project/timedoctor-mcp/","firstSeenAt":"2026-09-10T14:22:31.883Z","fetchedAt":"2026-11-10T04:23:19.994Z","normalizedAt":"2026-11-10T04:23:19.994Z"}]},"firstSeenAt":"2026-09-10T14:22:31.883Z","updatedAt":"2026-11-10T04:24:13.817Z"}