mcp-multiutil

ironystock/mcp-multiutil

3.2

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mcp-multiutil is a Model Context Protocol server offering a suite of utility tools for AI agents and chat applications, utilizing libSQL for persistent storage.

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mcp-multiutil

A Model Context Protocol (MCP) server providing multiple utility tools powered by libSQL for persistent storage.

Overview

mcp-multiutil is a stdio-based MCP server that exposes a collection of useful tools for AI agents and chat applications. It leverages libSQL for efficient, persistent storage with in-memory operation for fast performance.

Features

Tools

  • key-val - Simple key-value storage with CRUD operations
  • vector-store - Store and query vector embeddings with metadata
  • rag - Retrieval-augmented generation using stored documents and vectors
  • embedding - Generate and store text embeddings
  • txt-to-json - Convert text to structured JSON with schema inference
  • txt-to-toon - Convert text to cartoon/ASCII art representation
  • store-md - Store markdown documents with metadata
  • token-count - Count tokens in text
  • tokenize - Split text into tokens
  • store-context - Store conversation context for retrieval

Installation

go install github.com/ironystock/mcp-multiutil@latest

Usage

The server communicates over stdio and is designed to be used with MCP-compatible clients.

mcp-multiutil

Configuration

The server uses a local libSQL database file (multiutil.db by default) that is loaded into memory on startup and persisted to disk on shutdown.

Development

# Clone the repository
git clone https://github.com/ironystock/mcp-multiutil.git
cd mcp-multiutil

# Install dependencies
go mod download

# Build
go build -o mcp-multiutil .

# Run
./mcp-multiutil

Architecture

  • Storage Layer: libSQL with in-memory operation and disk persistence
  • Config Layer: Centralized tool definitions, descriptions, and schemas
  • Tools Layer: Individual tool handlers for each capability
  • MCP Server: stdio transport with graceful shutdown

License

MIT License - see for details.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.