cloakllm-mcp 0.3.0

MCP server for CloakLLM — PII cloaking tools for Claude Desktop

CloakLLM MCP Server

MCP server that wraps CloakLLM's Python SDK as tools for Claude Desktop and other MCP-compatible clients.

Tools

Tool	Description
sanitize	Detect & cloak PII, return sanitized text + token map ID + entity_details. Pass mode: "redact" for irreversible PII removal (no token_map_id returned).
desanitize	Restore original values using a token map ID
analyze	Detect PII without cloaking (pure analysis)

Install

cd cloakllm-mcp
pip install -e .

Claude Desktop Configuration

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "cloakllm": {
      "command": "python",
      "args": ["/path/to/cloakllm-mcp/server.py"],
      "env": {
        "CLOAKLLM_LOG_DIR": "./cloakllm_audit",
        "CLOAKLLM_LLM_DETECTION": "false"
      }
    }
  }
}

Or using uvx:

{
  "mcpServers": {
    "cloakllm": {
      "command": "uvx",
      "args": ["mcp", "run", "/path/to/cloakllm-mcp/server.py"]
    }
  }
}

Usage Examples

Sanitize text before sending to an LLM

Tool call: sanitize

{
  "text": "Email [e-mail] about the meeting with Sarah Johnson at 742 Evergreen Terrace",
  "model": "claude-sonnet-4-20250514",
  "token_map_id": "optional-id-for-multi-turn"
}

Multi-turn: Pass the token_map_id from a previous sanitize response to reuse the same token map across conversation turns. The same PII will always map to the same token.

Response:

{
  "sanitized": "Email [EMAIL_0] about the meeting with [PERSON_0] at 742 Evergreen Terrace",
  "token_map_id": "a1b2c3d4-...",
  "entity_count": 2,
  "categories": {"EMAIL": 1, "PERSON": 1},
  "entity_details": [
    {"category": "EMAIL", "start": 6, "end": 19, "length": 13, "confidence": 0.95, "source": "regex", "token": "[EMAIL_0]"},
    {"category": "PERSON", "start": 42, "end": 56, "length": 14, "confidence": 0.85, "source": "spacy", "token": "[PERSON_0]"}
  ]
}

Restore original values

Tool call: desanitize

{
  "text": "I've drafted an email to [EMAIL_0] regarding [PERSON_0]'s request.",
  "token_map_id": "a1b2c3d4-..."
}

Response:

{
  "restored": "I've drafted an email to [e-mail] regarding Sarah Johnson's request."
}

Analyze text for PII (no cloaking)

Tool call: analyze

{
  "text": "Contact [e-mail], SSN 123-45-6789"
}

Response:

{
  "entity_count": 2,
  "entities": [
    {"text": "[e-mail]", "category": "EMAIL", "start": 8, "end": 21, "confidence": 0.95, "source": "regex"},
    {"text": "123-45-6789", "category": "SSN", "start": 27, "end": 38, "confidence": 0.95, "source": "regex"}
  ]
}

Environment Variables

Variable	Default	Description
CLOAKLLM_LOG_DIR	./cloakllm_audit	Audit log directory
CLOAKLLM_AUDIT_ENABLED	true	Enable/disable audit logging
CLOAKLLM_SPACY_MODEL	en_core_web_sm	spaCy model for NER
CLOAKLLM_LLM_DETECTION	false	Enable LLM-based detection
CLOAKLLM_LLM_MODEL	llama3.2	Ollama model for LLM detection
CLOAKLLM_OLLAMA_URL	http://localhost:11434	Ollama endpoint

Testing

# Test with MCP inspector
python -m mcp dev server.py

# Or run directly
python server.py

See Also

• CloakLLM Hub — project overview, architecture, and links
• CloakLLM Python SDK — Python library with spaCy NER + OpenAI / LiteLLM middleware
• CloakLLM JS SDK — JavaScript library with OpenAI + Vercel AI middleware

License

MIT