XTraceAI/xtrace-mcp-server
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The xtrace-mcp-server is an example of creating a Model Context Protocol server for the XTrace vector database, which uses partially homomorphic encryption for privacy-preserving semantic search.
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
xtrace-store- Store some data in Xtrace's encrypted vector db for later retrieval
- Input:
data(string): textual data to storemeta_data(JSON): Optional metadata tp store
- Returns: success msg
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:
| Name | Description | Default Value |
|---|---|---|
XTrace_API_KEY | API key for the XTrace servvice | None |
KNOWLEDGE_BASE_ID | ID of the Knowledge base to use | None |
ORGANIZATION_ID | ID of the Organization registered at XTrace | None |
HOMOMORPHIC_KEY_PATH | Path to the locally stored secret key for homomorphic encryption | None |
AES_KEY | AES Key used for encrypting/decrypting plain text | None |
Installation
Make sure xtrace-sdk is installed. TODO.
Testing
TODO
