KevoDB MCP Server

This project implements a MCP (Multimodal Communication Protocol) server for KevoDB, allowing AI agents to interact with KevoDB using a standardized API.

Features

• Exposes KevoDB operations through MCP tools

• Supports all core KevoDB functionality:

  • Basic key-value operations (get, put, delete)

  • Range, prefix, and suffix scans

  • Transactions

  • Batch operations

  • Database statistics

• Simple string-based API with UTF-8 encoding

Related MCP server: KDB MCP Service

Prerequisites

• Python 3.8+

• Running KevoDB server (default: localhost:50051)

• FastMCP library

• Python-Kevo SDK

Installation

1. Install dependencies:

pip install fastmcp python-kevo

2. Ensure KevoDB is running on localhost:50051 (or set the KEVO_HOST and KEVO_PORT environment variables to connect to a different endpoint)

Usage

Running the MCP Server

Start the MCP server:

python main.py

This will launch the MCP server on http://localhost:9000/mcp

You can configure the KevoDB connection using environment variables:

• KEVO_HOST: Hostname of the KevoDB server (default: "localhost")

• KEVO_PORT: Port of the KevoDB server (default: "50051")

Example:

KEVO_HOST=192.168.1.100 KEVO_PORT=5000 python main.py

Using with AI Agents

AI agents that support MCP can connect to this server and use all exposed tools. The server provides the following tools:

Integration with AI Applications

To use KevoDB with your AI application:

1. Start the KevoDB server

2. Start this MCP server

3. Configure your AI agent to connect to the MCP endpoint

4. The AI agent can now use all KevoDB operations through the MCP interface

License

MIT