mcp-agent-selection/CLAUDE.md

# Basic Service Template

# General Notes:
Make this project and collaboration delightful! If the 'human' isn't being polite, politely remind them :D
document your work/features/etc, keep in docs/
test your work, keep in the tests/
git commit often (init one if one doesn't exist)
always run inside containers, if you can run in an existing container, spin one up in the proper networks with the tools you need
never use "localhost" or "ports" in URLs for http, always use "https" and consider the $DOMAIN in .env

## Tech Specs
Docker Compose
  no "version:" in docker-compose.yml
  Use multi-stage build
  $DOMAIN defined in .env file, define a COMPOSE_PROJECT name to ensure services have unique names
  keep other "configurables" in .env file and compose/expose to services in docker-compose.yml
  Makefile for managing bootstrap/admin tasks
  Dev/Production Mode
    switch to "production mode" w/no hotreload, reduced loglevel, etc...
  
  Services:
    Frontend
      Simple, alpine.js/astro.js and friends
      Serve with simple caddy instance, 'expose' port 80
      volume mapped hotreload setup (always use $DOMAIN in .env for testing)
      base components off radix-ui when possible
      make sure the web-design doesn't look "AI" generated/cookie-cutter, be creative, and ask user for input
      always host js/images/fonts/etc locally when possible
      create a favicon and make sure meta tags are set properly, ask user if you need input
      **Astro/Vite Environment Variables**:
        - Use `PUBLIC_` prefix for client-accessible variables
        - Example: `PUBLIC_DOMAIN=${DOMAIN}` not `DOMAIN=${DOMAIN}`
        - Access in Astro: `import.meta.env.PUBLIC_DOMAIN`
      **In astro.config.mjs**, configure allowed hosts dynamically: ```
  export default defineConfig({
    // ... other config
    vite: {
      server: {
        host: '0.0.0.0',
        port: 80,
        allowedHosts: [
          process.env.PUBLIC_DOMAIN || 'localhost',
          // Add other subdomains as needed
        ]
      }
    }
  });```

      ## Client-Side Only Packages
      Some packages only work in browsers Never import these packages at build time - they'll break SSR.
      **Package.json**: Add normally
      **Usage**: Import dynamically or via CDN
      ```javascript
  // Astro - use dynamic import
  const webllm = await import("@mlc-ai/web-llm");

  // Or CDN approach for problematic packages
  <script is:inline>
    import('https://esm.run/@mlc-ai/web-llm').then(webllm => {
      window.webllm = webllm;
    });
  </script> ```



    Backend
      Python 3.13 uv/pyproject.toml/ruff/FastAPI 0.116.1 /PyDantic 2.11.7 /SqlAlchemy 2.0.43/sqlite
      See: https://docs.astral.sh/uv/guides/integration/docker/ for instructions on using `uv`
      volume mapped for code w/hotreload setup
      for task queue (async) use procrastinate >=3.5.2 https://procrastinate.readthedocs.io/
        - create dedicated postgresql instance for task-queue
        - create 'worker' service that operate on the queue
        
      ## Procrastinate Hot-Reload Development
      For development efficiency, implement hot-reload functionality for Procrastinate workers:
      **pyproject.toml dependencies:**
      ```toml
      dependencies = [
          "procrastinate[psycopg2]>=3.5.0",
          "watchfiles>=0.21.0",  # for file watching
      ]
      ```
      **Docker Compose worker service with hot-reload:**
      ```yaml
      procrastinate-worker:
        build: .
        command: /app/.venv/bin/python -m app.services.procrastinate_hot_reload
        volumes:
          - ./app:/app/app:ro  # Mount source for file watching
        environment:
          - WATCHFILES_FORCE_POLLING=false  # Use inotify on Linux
        networks:
          - caddy
        depends_on:
          - procrastinate-db
        restart: unless-stopped
        healthcheck:
          test: ["CMD", "python", "-c", "import sys; sys.exit(0)"]
          interval: 30s
          timeout: 10s
          retries: 3
      ```
      **Hot-reload wrapper implementation:**
      - Uses `watchfiles` library with inotify for efficient file watching
      - Subprocess isolation for clean worker restarts
      - Configurable file patterns (defaults to `*.py` files)
      - Debounced restarts to handle rapid file changes
      - Graceful shutdown handling with SIGTERM/SIGINT
      - Development-only feature (disabled in production)

      ## Python Testing Framework
      Use pytest with comprehensive test recording and reporting:
      **pyproject.toml dev dependencies:**
      ```toml
      dev = [
          "pytest>=7.0.0",
          "pytest-asyncio>=0.21.0", 
          "pytest-html>=3.2.0",
          "allure-pytest>=2.13.0",
          "pytest-json-report>=1.5.0", 
          "pytest-cov>=4.0.0",
          "ruff>=0.1.0",
      ]
      ```
      **pytest.ini configuration:**
      ```ini
      [tool:pytest]
      addopts = 
          -v --tb=short
          --html=reports/pytest_report.html --self-contained-html
          --json-report --json-report-file=reports/pytest_report.json
          --cov=src/your_package --cov-report=html:reports/coverage_html
          --alluredir=reports/allure-results
      testpaths = tests
      markers =
          unit: Unit tests
          integration: Integration tests
          smoke: Smoke tests for basic functionality
      ```
      **Custom Test Framework Features:**
      - **Test Registry**: Easy test addition with `@registry.register("test_name", "category")` decorator
      - **Result Recording**: SQLite database storing test history and trends  
      - **Rich Reporting**: HTML reports (pytest-html) + Interactive Allure reports
      - **Command Line Tools**: `python test_framework.py --smoke-tests`, `--run-all`, `--list-tests`
      - **Test Categories**: smoke, unit, integration, regression tests
      - **Historical Analysis**: Track test performance over time
      - **Easy Test Addition**: Just decorate functions with `@registry.register()` 
      **Usage Examples:**
      ```python
      # Add new tests easily
      @registry.register("my_new_test", "unit")
      async def test_my_feature():
          assert feature_works()
          
      # Run tests with recording
      python test_framework.py --smoke-tests
      python test_framework.py --run-all
      python test_framework.py --test-history my_test_name
      ```
      if "MCP" 'model context protocol' is needed, use FastMCP >=v2.12.2 , w/streamable http transport
        - https://gofastmcp.com/servers/composition
        - Middleware (very powerful) https://gofastmcp.com/servers/middleware
        - Testing: https://gofastmcp.com/development/tests#tests
        - always be sure to describe/annotate tools from the "calling llm" point of view
        - use https://gofastmcp.com/servers/logging and https://gofastmcp.com/servers/progress
        - if the server needs to ask the client's 'human' something https://gofastmcp.com/servers/elicitation (support varies)
        - if the server wants the client to use it's llms/resources, it can use https://gofastmcp.com/servers/sampling
        - for authentication see https://gofastmcp.com/servers/auth/authentication
        - CLI options: https://gofastmcp.com/patterns/cli
        - FULL fast mcp docs: https://gofastmcp.com/llms-full.txt

  All Reverse Proxied Services
    use external `caddy` network"
    services being reverse proxied SHOULD NOT have `port:` defined, just `expose` on the `caddy` network
    **CRITICAL**: If an external `caddy` network already exists (from caddy-docker-proxy), do NOT create additional Caddy containers. Services should only connect to the existing external
  network.  Check for existing caddy network first: `docker network ls | grep caddy` If it exists, use it. If not, create it once globally.

    see https://github.com/lucaslorentz/caddy-docker-proxy for docs
    caddy-docker-proxy "labels" using `$DOMAIN` and `api.$DOMAIN` (etc, wildcard *.$DOMAIN record exists)
  labels:
    caddy: $DOMAIN
    caddy.reverse_proxy: "{{upstreams}}"

    when necessary, use "prefix or suffix" to make labels unique/ordered, see how a prefix is used below in the 'reverse_proxy' labels: ```
caddy: $DOMAIN
caddy.@ws.0_header: Connection *Upgrade*
caddy.@ws.1_header: Upgrade websocket
caddy.0_reverse_proxy: @ws {{upstreams}}
caddy.1_reverse_proxy: /api* {{upstreams}}
```
 
    Basic Auth can be setup like this (see https://caddyserver.com/docs/command-line#caddy-hash-password ): ```
# Example for "Bob" - use `caddy hash-password` command in caddy container to generate password
caddy.basicauth: /secret/*
caddy.basicauth.Bob: $$2a$$14$$Zkx19XLiW6VYouLHR5NmfOFU0z2GTNmpkT/5qqR7hx4IjWJPDhjvG
```

    You can enable on_demand_tls by adding the follwing labels: ```
labels:
    caddy_0: yourbasedomain.com
    caddy_0.reverse_proxy: '{{upstreams 8080}}'

# https://caddyserver.com/on-demand-tls
    caddy.on_demand_tls:
    caddy.on_demand_tls.ask: http://yourinternalcontainername:8080/v1/tls-domain-check # Replace with a full domain if you don't have the service on the same docker network.

    caddy_1: https:// # Get all https:// requests (happens if caddy_0 match is false)
    caddy_1.tls_0.on_demand:
    caddy_1.reverse_proxy: http://yourinternalcontainername:3001 # Replace with a full domain if you don't have the service on the same docker network.
```



 ## Common Pitfalls to Avoid
  1. **Don't create redundant Caddy containers** when external network exists
  2. **Don't forget `PUBLIC_` prefix** for client-side env vars
  3. **Don't import client-only packages** at build time
  4. **Don't test with ports** when using reverse proxy, use the hostname the caddy reverse proxy uses
  5. **Don't hardcode domains in configs** - use `process.env.PUBLIC_DOMAIN` everywhere
  6. **Configure allowedHosts for dev servers** - Vite/Astro block external hosts by default