wardcat-mcp

An MCP server that exposes wardcat's on-prem PII detection and anonymization as tools any agent can call — Claude Desktop, Cursor, a self-hosted bot, a RAG pipeline. Use it as a guardrail: sanitize inputs before they reach an LLM, or gate them with a semantic "is this sensitive?" check.

Runs locally, stays local. The server runs on your machine over stdio; the text, the models, and all detection stay on-prem — nothing is sent anywhere. Publishing this package ships code you run yourself, not a hosted service.

Tools

Tool	Description
scan(text)	Detect PII and return the sanitized text plus a PII-free summary (entity types, actions, confidence — never the raw values).
is_sensitive(text)	Holistic LLM yes/no on whether the text contains sensitive information. Requires the LLM layer (WARDCAT_LLM_MODEL).

Install & run

Not on PyPI yet — run from source (wardcat itself is source-only for now):

uvx --from git+https://github.com/oguzhantopcu0/wardcat-mcp.git wardcat-mcp
# or, cloned locally:
uv run wardcat-mcp

Add it to an MCP client

Claude Desktop (claude_desktop_config.json), Cursor, Cline, Zed, etc.:

{
  "mcpServers": {
    "wardcat": {
      "command": "uvx",
      "args": ["--from", "git+https://github.com/oguzhantopcu0/wardcat-mcp.git", "wardcat-mcp"],
      "env": {
        "WARDCAT_SALT": "your-secret-salt",
        "WARDCAT_ACTION": "redact",
        "WARDCAT_LLM_MODEL": "llama3.2:3b"
      }
    }
  }
}

Configuration (environment variables)

Var	Default	Meaning
WARDCAT_SALT	""	Hashing salt (required for the hash action).
WARDCAT_ENTITIES	broad structural + name set	Comma-separated entity types to enable.
WARDCAT_ACTION	redact	warn | hash | redact | mask.
WARDCAT_SPACY_MODEL	—	Enable SpaCy NER with this model (needs the ner extra).
WARDCAT_LLM_MODEL	—	Enable the on-prem LLM layer via Ollama (e.g. llama3.2:3b).
WARDCAT_LLM_BASE_URL	http://localhost:11434	Ollama endpoint.

Disclaimer

wardcat is a best-effort PII detector — it does not catch everything and is not legal advice or a substitute for compliance review (e.g. GDPR/KVKK). Validate it against your own data. Provided "as is" (MIT).

License

MIT — see LICENSE.