enVector-MCP-Server

Description

We provide MCP Server of enVector, CryptoLab, Inc.'s HE (Homomorphic Encryption)-Based vector search engine.

Related MCP server: AXYS MCP Lite

What is MCP?

MCP, which stands for Model Context Protocol, is a protocol used by AI application for access to the following services:

1. External data

2. Tools

3. Workflow

It is kind of pre-defined JSON format protocol.

Participant in MCP

There are 3 participant in MCP communication.

• Host

  • AI application

  • ex. VS Code, Claude, and so on

• Client

  • Connection module of Host

  • Form of expansion or add-on module (1:1 for each server)

• Server

  • Supplier of Data/Tools

  • In our case, enVector

How enVector-MCP-Server can be implemented to services?

As enVector is vector search engine based on HE, this enVector MCP Server can be used in some cases like below.

Use Scenario

• AI chat-bot emplaced in private network (IntraNet / Air-Gapped Net)

  • This chat-bot need to use secured dataset.

  In this case,

  1. To get data, AI send query to enVector via enVector MCP Server.

  2. enVector do vector search and returns encryptred scoreboard.

  3. Then AI decrypt scoreboard and require most appropriate vector's metadata to secured DB.

  4. After get response, AI decrypt dataset and show it to user.

• SW Developer, who is affiliated at some SW Dev Team, is running new project.

  • They wanna refer to their previous project to reuse some codes.

  • They are using code assistant module

  • Their previous project is under protection with private repository.

  In this case,

  1. Code assistant generate new skeleton codes first and then, try to search similar codes in DB.

  2. As codes are protected as encrypted form, code assistant AI call enVector MCP Server to search code candidates via enVector.

  3. Then, enVector returns scoreboard of codes stored in secured DB.

  4. Code Assistant AI now can require top-k code blocks stored in specific index in DB.

  5. After decrypting returned code blocks, code assistant AI can improve skeleton codes with them.

• Assumption

  • enVector can run on anywhere

  • Each terminal(devices) user just need to add enVector MCP Server on their AI assistant (or else).

• Expectation

  With pre-defined protocol that enVector MCP Server uses, all 'secured-data search' will be processed automatically.

Languages Support

• Python3