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KevoDB

KevoDB MCP Server

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by KevoDB
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Python
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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: Simple MCP Server

Prerequisites

  • Python 3.8+

  • Running KevoDB server (default: localhost:50051)

  • FastMCP library

  • Python-Kevo SDK

Installation

  1. Install dependencies:

pip install fastmcp python-kevo

  1. 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:

Tool

Description

connect

Connect to the KevoDB server

get

Get a value by key from KevoDB

put

Store a key-value pair in KevoDB

delete

Delete a key-value pair from KevoDB

scan

Scan keys in KevoDB with options

batch_write

Perform multiple operations in a batch

get_stats

Get database statistics

begin_transaction

Begin a new transaction and return transaction ID

commit_transaction

Commit a transaction by ID

rollback_transaction

Roll back a transaction by ID

tx_put

Store a key-value pair within a transaction

tx_get

Get a value by key within a transaction

tx_delete

Delete a key-value pair within a transaction

cleanup

Close the KevoDB connection

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

This server cannot be deployed

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

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