Workhours Calendar

Track worked hours by client → project → task. At the end of the month, see how many hours went into each project or client, how long a task took, and what was worked on any given day — via REST API, Swagger UI, or by just asking Claude (MCP server + Claude Code plugin included).

Install

The only requirement is Docker.

Linux / macOS / Raspberry Pi:

curl -fsSL https://raw.githubusercontent.com/gifflet/workhours-calendar/main/install.sh | sh

Windows (PowerShell):

irm https://raw.githubusercontent.com/gifflet/workhours-calendar/main/install.ps1 | iex

The script pulls the prebuilt multi-arch images (amd64, arm64, arm/v7), starts MongoDB and the API, and waits until everything is healthy:

• API: http://localhost:8001 — Swagger UI: http://localhost:8001/docs

• Data persists in the workhours_mongo volume; containers restart with Docker on boot

• Re-run the script anytime to update (data is kept)

• WORKHOURS_PORT changes the API port; MONGO_URL points to an external MongoDB (required on 32-bit ARM). Raspberry Pi 3/4 automatically get mongo:4.4, since MongoDB 5+ needs ARMv8.2-A.

Uninstall: docker rm -f workhours-api workhours-mongo && docker volume rm workhours_mongo

Related MCP server: Time Tracking MCP

Use with Claude Code

Install the plugin once (user scope — available in every project):

/plugin marketplace add gifflet/workhours-calendar
/plugin install workhours@workhours-calendar

Then just ask in natural language:

"Log 2.5 hours today on the CI pipeline task of ACME's ERP project"

"How many hours did I work for ACME in August?"

"Which tasks did I work on yesterday?"

The plugin bundles the MCP server (prebuilt Docker image — nothing to clone or build) and a skill that teaches the model the workflows: resolve names to ids, create missing clients/projects/tasks on demand, and answer report questions with a single tool call. Source: plugins/workhours.

API

Interactive docs at /docs (Swagger UI) and /redoc.

• Dates use YYYY-MM-DD; hours are decimal (1.5 = 1h30).

• A time entry needs a task_id or a project_id; client and project are denormalized into the entry automatically for fast reporting.

• Deletes are guarded: a client/project/task with children or time entries can't be deleted (HTTP 409).

# Hours in August 2026, broken down by client, project, task and day
curl "http://localhost:8001/reports/monthly?year=2026&month=8"

# What was worked on a specific day
curl "http://localhost:8001/reports/daily?date=2026-08-12"

# Total effort spent on a task
curl "http://localhost:8001/reports/task/<task_id>"

Other MCP clients

The MCP server exposes 14 tools over stdio (create_client, log_hours, monthly_report, daily_report, task_report, ...). To register it outside the Claude Code plugin, run the published image with -i:

claude mcp add workhours \
  -- docker run -i --rm \
     --add-host host.docker.internal:host-gateway \
     -e WORKHOURS_API_URL=http://host.docker.internal:8001 \
     ghcr.io/gifflet/workhours-calendar-mcp:latest

The WORKHOURS_API_URL environment variable points the server at the API.

Development

# Everything in containers (builds locally)
docker compose up --build

# Or API on the host (needs MongoDB on localhost:27017 — uncomment the
# ports mapping in docker-compose.yaml to publish the mongodb service)
python3 -m venv .venv
.venv/bin/pip install -r requirements.txt
.venv/bin/uvicorn app.main:app --reload --port 8001

The API reads MONGO_URL (default mongodb://localhost:27017) and MONGO_DB (default workhours). The repo ships a project-scoped .mcp.json that runs the MCP server from the local venv. Test it standalone with:

npx @modelcontextprotocol/inspector .venv/bin/python mcp_server/server.py

CI (.github/workflows/docker-build.yml) builds and publishes ghcr.io/gifflet/workhours-calendar-api and ...-mcp for linux/amd64, linux/arm64 and linux/arm/v7 on every push to main and on v* tags; pull requests build without publishing.

app/                 # FastAPI app (routers, schemas, Mongo access)
mcp_server/          # MCP stdio server calling the API
plugins/workhours/   # Claude Code plugin (skill + MCP via Docker image)
.claude-plugin/      # Plugin marketplace manifest
install.sh install.ps1              # One-command installers
Dockerfile Dockerfile.mcp           # API and MCP server images
docker-compose.yaml
.github/workflows/docker-build.yml  # Multi-arch build + publish to GHCR