LLM / Inspector / Claude Desktop → MCP (stdio or HTTP) → tools → answer

src/et_mcp/
├── server.py              # FastMCP entry: --server calc|site|catalog|all, --transport stdio|streamable-http
├── settings.py            # env-only config (pydantic-settings, no hardcoding)
├── retrieval/             # shared hybrid retrieval (Qdrant + BM25, optional)
├── services/
│   ├── calc/              # pure math + knowledge docs + BM25 index
│   ├── catalog/           # DB (psycopg2, read-only, timeout + row cap) + SQL validator (sqlglot)
│   └── site/              # KB chunker + BM25 index
└── tools/                 # thin MCP adapters — no business logic

# 1. install
pip install -e .

# 2. env - copy and fill DB URL (catalog only)
cp .env.example .env
# edit .env: set SUPABASE_DB_URL=postgresql://user:pass@host:5432/db

# 3. run - pick one
python -m et_mcp.server --server all --transport stdio                          # for Claude Desktop / Inspector stdio
python -m et_mcp.server --server catalog --transport streamable-http --port 8001  # HTTP
python -m et_mcp.server --server site    --transport streamable-http --port 8002
python -m et_mcp.server --server calc    --transport streamable-http --port 8003
python -m et_mcp.server --server all     --transport streamable-http --port 8001  # all 17 tools on one port

cp .env.example .env  # set SUPABASE_DB_URL
docker build -f Dockerfile.mcp -t et-mcp .
docker run --env-file .env -p 8001:8001 et-mcp python -m et_mcp.server --server all --transport streamable-http --port 8001 --host 0.0.0.0

{
  "mcpServers": {
    "et-mcp": {
      "command": "python",
      "args": ["-m", "et_mcp.server", "--server", "all"],
      "cwd": "C:\\path\\to\\ETGPT"
    }
  }
}

{
  "mcpServers": {
    "et-mcp-calc":    { "command": "python", "args": ["-m","et_mcp.server","--server","calc"], "cwd": "C:\\path\\to\\ETGPT" },
    "et-mcp-site":    { "command": "python", "args": ["-m","et_mcp.server","--server","site"], "cwd": "C:\\path\\to\\ETGPT" },
    "et-mcp-catalog": { "command": "python", "args": ["-m","et_mcp.server","--server","catalog"], "cwd": "C:\\path\\to\\ETGPT" }
  }
}

npx -y @modelcontextprotocol/inspector -- python -m et_mcp.server --server all
# or HTTP: python -m et_mcp.server --server all --transport streamable-http --port 8001
# then open http://127.0.0.1:6274, connect to http://127.0.0.1:8001/mcp

# 0. import check (no DB needed)
python -c "from et_mcp.tools.registry import TOOLSETS; print({k: len(v) for k,v in TOOLSETS.items()})"
# expect: {'calc': 6, 'site': 2, 'catalog': 9}

# 1. calc — BM25 + math (no DB)
python -c "
from et_mcp.services.calc.retrieval import search
from et_mcp.services.calc.dispatch import DISPATCH
from et_mcp.tools.calc import calculate
print(search('field of view for 12mm lens at 500mm', top_k=3))
# pick a formula_id from above, e.g. fov_using_sensor_size
print(calculate('fov_using_sensor_size', {'sensor_size_mm': 8.8, 'working_distance_mm': 500, 'focal_length_mm': 12}))
"

# 2. site — BM25+grep (no DB)
python -c "
from et_mcp.tools.site import search_knowledge_base, get_document
print(search_knowledge_base('garuda inspection system', top_k=3))
print(get_document('company_overview')['title'])
"

# 3. catalog — needs SUPABASE_DB_URL in .env (read-only)
python -c "
from et_mcp.tools.catalog import list_families, list_tables, describe_table
print(list_families())
print(list_tables('line_scan'))
print(describe_table('line_scan_lens_8k5u'))
"
python -c "
from et_mcp.tools.catalog import search_knowledge, get_table_knowledge
print(search_knowledge('lens for conveyor belt inspection', top_k=3))
print(get_table_knowledge('line_scan_lens_8k5u')['purpose'][:200])
"
python -c "
from et_mcp.tools.catalog import search_products, run_select
print(search_products(table='line_scan_lens_8k5u', filters=[{'column':'focal_length_mm','op':'=','value':12}], limit=2))
print(run_select('SELECT model_name, focal_length_mm FROM line_scan_lens_8k5u LIMIT 2'))
"

# 4. MCP stdio smoke (spawns server, lists tools, exits)
python -c "
import asyncio, sys
from mcp.client.stdio import stdio_client
from mcp import StdioServerParameters
async def main():
    params = StdioServerParameters(command=sys.executable, args=['-m','et_mcp.server','--server','all'])
    async with stdio_client(params) as (read, write):
        from mcp.client.session import ClientSession
        async with ClientSession(read, write) as s:
            await s.initialize()
            tools = await s.list_tools()
            print([t.name for t in tools.tools])
asyncio.run(main())
"
# expect 17 tool names

# 5. HTTP smoke (needs server running in another terminal)
# terminal A: python -m et_mcp.server --server all --transport streamable-http --port 8001
# terminal B:
curl http://127.0.0.1:8001/mcp -H "Accept: text/event-stream"