MCP Data Catalog Server

An MCP server exposing tools over a synthetic enterprise data catalog: asset search with a composable AND/OR filter DSL, lineage, sample data, profiling, history, quality rules, and AI-driven classification (CDE detection, PII tagging, business-term generation).

Independent, from-scratch reimplementation of a system design I built in a professional context — synthetic catalog data, no proprietary business logic, for portfolio/demo purposes. Not affiliated with, and contains no code or data from, any employer or client.

What it demonstrates

• Composable AND/OR filter DSL (src/catalog/filter_dsl.py) — asset search takes a nested {"and": [...]} / {"or": [...]} filter tree instead of a fixed set of query parameters, so callers can express arbitrary boolean combinations of field predicates without the tool schema growing per use case.

• Heuristic-first classification with AI fallback (src/catalog/classification.py) — Critical Data Element (CDE) detection runs cheap heuristics (name/type pattern matching) first and only calls the (stubbed) AI classifier when the heuristics are inconclusive; PII tagging is fully AI-driven from asset metadata.

• Business-term generation validated against governance heuristics (src/catalog/business_terms.py) — candidate terms are matched to catalog assets via cosine similarity over embeddings, then filtered through governance rules (naming convention, domain allowlist) before being surfaced for publishing.

• MCP tool surface (src/tools/) — search, lineage, sample data, profiling, history, quality rules, CDE classification, PII classification, and business term generation, registered on a real mcp SDK server in src/server.py.

Related MCP server: DataHub MCP Server

Running it

python -m venv .venv
source .venv/bin/activate   # or .venv\Scripts\activate on Windows
pip install -r requirements.txt
python -m src.main

The server runs over stdio, ready to be added to an MCP client (e.g. Claude Desktop or Claude Code) config pointing at python -m src.main in this directory. All catalog data is synthetic and generated in-process — no external database required.

pytest

Project layout

src/
  main.py               # entrypoint
  server.py              # MCP server + tool registration
  catalog/
    store.py              # in-memory synthetic catalog
    models.py              # Asset, LineageEdge, QualityRule
    filter_dsl.py            # AND/OR filter tree evaluator
    classification.py         # heuristic-first CDE + AI-driven PII
    business_terms.py          # embedding similarity + governance validation
  tools/
    search.py, lineage.py, sample_data.py, profiling.py,
    history.py, quality_rules.py, classification_tools.py,
    business_term_tool.py
tests/