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Meilisearch MCP Server Implementation Plan

Overview

This document outlines the implementation plan for the Meilisearch MCP Server, which integrates with Meilisearch to provide search capabilities to LLMs via the Model Context Protocol (MCP).

Project Structure

meilisearch-ts-mcp/
├── src/
│   ├── index.ts                 # Main entry point
│   ├── config.ts                # Server configuration
│   ├── tools/                   # MCP tools implementation
│   │   ├── index-tools.ts       # Index management tools
│   │   ├── document-tools.ts    # Document management tools
│   │   ├── search-tools.ts      # Search tools
│   │   ├── settings-tools.ts    # Settings management tools
│   │   ├── task-tools.ts        # Task management tools
│   │   ├── vector-tools.ts      # Vector search tools 
│   │   └── system-tools.ts      # System tools (health, stats, etc.)
│   └── utils/                   # Utility functions
│       ├── api-client.ts        # Meilisearch API client
│       └── error-handler.ts     # Error handling utilities

Implementation Phases

Phase 1: Project Setup and Refactoring

  1. Create the directory structure
  2. Extract configuration into config.ts
  3. Create utility modules for API client and error handling
  4. Refactor the existing monolithic implementation into separate modules

Phase 2: Core Functionality Implementation

  1. Index Management Tools

    • List indexes
    • Get index information
    • Create index
    • Update index
    • Delete index
    • Get index stats

  2. Document Management Tools

    • Add/update documents
    • Get documents
    • Delete documents
    • Batch document operations

  3. Search Tools

    • Basic search
    • Search with filters
    • Search with sorting
    • Faceted search

Phase 3: Advanced Functionality

  1. Settings Management Tools

    • Get index settings
    • Update settings
    • Reset settings
    • Configure specific settings (synonyms, stop words, etc.)

  2. Task Management Tools

    • Get tasks
    • Get task by ID
    • Cancel tasks

  3. System Tools

    • Health check
    • Version information
    • Stats

  4. Vector Search Tools

    • Configure embedders
    • Perform vector search
    • Hybrid search
    • Vector search with filters

Testing and Documentation

  1. Create unit tests for each module
  2. Add integration tests for end-to-end functionality
  3. Update README with detailed usage instructions
  4. Create example scripts and configurations

Timeline

  • Phase 1: 1 day
  • Phase 2: 2-3 days
  • Phase 3: 2-3 days
  • Testing and Documentation: 1-2 days

Total estimated time: 6-9 days

Dependencies

  • @modelcontextprotocol/sdk: For MCP server implementation
  • axios: For HTTP requests to Meilisearch API
  • zod: For parameter validation

Notes

  • Vector search functionality requires Meilisearch to have vector search enabled as an experimental feature
  • The implementation will be backward compatible with existing clients
  • All tools will include detailed error handling and descriptive responses