Kevo Mcp
What is Kevo Mcp
Kevo-MCP is a server that implements the Multimodal Communication Protocol (MCP) for accessing and interacting with KevoDB, allowing AI agents to utilize a standardized API for data operations.
Use cases
Use cases for Kevo-MCP include AI-driven applications that need to retrieve, store, or manipulate data in KevoDB, such as chatbots accessing user data, automated reporting tools, and systems requiring batch processing of database transactions.
How to use
To use Kevo-MCP, first install the required dependencies using pip. Ensure that KevoDB is running, then start the MCP server by executing ‘python main.py’. Configure the KevoDB connection with environment variables if needed. AI agents can connect to the server and use various tools for data operations.
Key features
Key features of Kevo-MCP include: exposing KevoDB operations through MCP tools, supporting core functionalities like basic key-value operations, range scans, transactions, batch operations, and providing database statistics. It uses a simple string-based API with UTF-8 encoding.
Where to use
Kevo-MCP can be used in fields that require data management and interaction through AI agents, such as data analytics, machine learning applications, and any system that benefits from a structured database interface.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Kevo Mcp
Kevo-MCP is a server that implements the Multimodal Communication Protocol (MCP) for accessing and interacting with KevoDB, allowing AI agents to utilize a standardized API for data operations.
Use cases
Use cases for Kevo-MCP include AI-driven applications that need to retrieve, store, or manipulate data in KevoDB, such as chatbots accessing user data, automated reporting tools, and systems requiring batch processing of database transactions.
How to use
To use Kevo-MCP, first install the required dependencies using pip. Ensure that KevoDB is running, then start the MCP server by executing ‘python main.py’. Configure the KevoDB connection with environment variables if needed. AI agents can connect to the server and use various tools for data operations.
Key features
Key features of Kevo-MCP include: exposing KevoDB operations through MCP tools, supporting core functionalities like basic key-value operations, range scans, transactions, batch operations, and providing database statistics. It uses a simple string-based API with UTF-8 encoding.
Where to use
Kevo-MCP can be used in fields that require data management and interaction through AI agents, such as data analytics, machine learning applications, and any system that benefits from a structured database interface.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
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
Prerequisites
- Python 3.8+
- Running KevoDB server (default: localhost:50051)
- FastMCP library
- Python-Kevo SDK
Installation
- Install dependencies:
pip install fastmcp python-kevo
- Ensure KevoDB is running on localhost:50051 (or set the
KEVO_HOSTandKEVO_PORTenvironment 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:
- Start the KevoDB server
- Start this MCP server
- Configure your AI agent to connect to the MCP endpoint
- The AI agent can now use all KevoDB operations through the MCP interface
License
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.
