xtrace-mcp-server

xtrace-mcp-server

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This project is an official Model Context Protocol server designed to store and retrieve memories using XTrace's encrypted vector database. It serves as a semantic memory layer for LLMs, utilizing partially homomorphic encryption.

xtrace-mcp-server

The Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools. Whether you're building an AI-powered IDE, enhancing a chat interface, or creating custom AI workflows, MCP provides a standardized way to connect LLMs with the context they need.

This repository is an example of how to create a MCP server for XTrace vector database which uses partially homomorphic encryption for privacy preserving semantic search.

Overview

An official Model Context Protocol server for keeping and retrieving memories in the XTrace encrypted vector db. It acts as a encrypted semantic memory layer for LLMs.

Components

Tools

  1. xtrace-store
    • Store some data in Xtrace's encrypted vector db for later retrieval
    • Input:
      • data (string): textual data to store
      • meta_data (JSON): Optional metadata tp store
    • Returns: success msg
  2. xtrace-search
    • Retrieve relevant data from XTrace with encrypted query.
    • Input:
      • query (string): Query to use for searching
    • Returns: list of most relevant data

Environment Variables

The configuration of the server is done using environment variables:

NameDescriptionDefault Value
XTrace_API_KEYAPI key for the XTrace servviceNone
KNOWLEDGE_BASE_IDID of the Knowledge base to useNone
ORGANIZATION_IDID of the Organization registered at XTraceNone
HOMOMORPHIC_KEY_PATHPath to the locally stored secret key for homomorphic encryptionNone
AES_KEYAES Key used for encrypting/decrypting plain textNone

Installation

Make sure xtrace-sdk is installed. TODO.

Testing

TODO