mirrorsecai/mirror-vectax-mcp-server
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The Secure Embedding MCP Server is a Model Context Protocol implementation designed for secure text embeddings with privacy-preserving features using the Mirror SDK.
The Secure Embedding MCP Server provides a robust interface for processing text data with various security levels while generating embeddings for semantic search and analysis. It leverages the Mirror SDK to provide advanced security features including format-preserving encryption (FPE) for sensitive entities, vector encryption for secure embeddings, role-based access control (RBAC) for fine-grained security policies, and entity detection for PII and sensitive information. The server is designed to handle multiple text operations through a unified interface, offering configurable security levels and a natural language interface for ease of use. It supports batch processing for efficient handling of multiple texts and enables semantic search across documents using embeddings.
Features
- Unified Text Processing: Single entry point for various text operations with appropriate security measures.
- Multiple Operation Modes: Supports 'embed', 'secure', 'analyze', 'mask', and 'auto' modes for text processing.
- Configurable Security Levels: Offers 'none', 'low', 'medium', 'high', and 'auto' security levels based on content.
- Natural Language Interface: Allows processing requests in natural language.
- Batch Processing: Efficiently handles multiple texts for processing.
Usages
usage with Claude Desktop
{ "mcpServers": { "secure-embedding": { "command": "uv", "args": [ "--directory", "/ABSOLUTE/PATH/TO/YOUR/PROJECT/mirror-vectax-mcp-server", "run", "mirror_vectax_server.py" ] } } }
usage with VS Code
{ "mcp": { "servers": { "secure-embedding": { "command": "uv", "args": [ "--directory", "/ABSOLUTE/PATH/TO/YOUR/PROJECT/mirror-vectax-mcp-server", "run", "mirror_vectax_server.py" ] } } } }
Tools
process
Handles text processing with various security measures.
batch-process
Processes multiple texts efficiently.
generate-user-key
Generates user keys for role-based access control.
search
Performs semantic search across documents using embeddings.