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CloakLLM MCP Server

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

Important: MCP does not protect your initial prompt. MCP tools are called by the LLM — your prompt is sent to the LLM provider first, then the LLM decides to invoke tools. This means the raw prompt (including any PII) reaches the provider before CloakLLM can sanitize it. The MCP server is useful for sanitizing data that the LLM processes during a conversation (documents, files, tool outputs), but it cannot prevent your prompt from reaching the provider.

To protect prompts before they leave your infrastructure, use the SDK middleware instead:

  • Python: enable_openai(client) or cloakllm.enable() (LiteLLM)
  • JavaScript: cloakllm.enable(client)

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 john@acme.com 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 john@acme.com regarding Sarah Johnson's request."
}

Analyze text for PII (no cloaking)

Tool call: analyze

{
  "text": "Contact john@acme.com, SSN 123-45-6789"
}

Response:

{
  "entity_count": 2,
  "entities": [
    {"text": "john@acme.com", "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

License

MIT

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