Seroost Search MCP Server

A Model Context Protocol (MCP) server that provides AI agents with powerful codebase search capabilities using the Seroost semantic search engine.

Features

• Semantic Code Search: Find functions, classes, and code patterns using natural language queries

• Ranked Results: Get relevance-scored search results with line numbers and file paths

• Fast Indexing: Quick indexing of entire codebases including dependencies

• MCP Integration: Works with any MCP-compatible AI system (Claude, VS Code Copilot, etc.)

• JSON API: Structured responses perfect for programmatic use

Prerequisites

• Node.js 18+

• Seroost installed and built in release mode

• TypeScript (for development)

Installation

1. Install Seroost (if not already installed):

   # Clone and build Seroost git clone https://github.com/Parado-xy/seroost cd seroost cargo build --release # Make sure the binary is in your PATH

2. Clone this repository:

   git clone https://github.com/Parado-xy/semantic-search-mcp cd search-mcp

3. Install dependencies:

   npm install

4. Build the project:

   npm run build

Usage

As an MCP Server

Configure your MCP client to use this server:

Available Tools

seroost_set_index

Configure the target directory for indexing.

Parameters:

• path (string): Absolute path to the directory to index

Example:

seroost_index

Build the search index for the configured directory.

Parameters: None (uses path set by seroost_set_index)

Example:

seroost_search

Search through the indexed codebase.

Parameters:

• query (string): Search term, function name, or natural language description

Example:

Response:

Workflow

1. Set Index Path: Use seroost_set_index to configure which directory to search

2. Build Index: Run seroost_index to process and index all files

3. Search: Use seroost_search to find relevant code with natural language queries

Example Searches

• "function createUser" - Find user creation functions

• "error handling" - Find error handling patterns

• "database connection" - Find database-related code

• "React components" - Find React component definitions

• "API endpoints" - Find REST API route definitions

Development

Building

Project Structure

How It Works

This MCP server acts as a bridge between AI agents and the Seroost search engine:

1. Indexing: Seroost processes your codebase and creates a searchable index

2. Querying: AI agents send search queries through the MCP protocol

3. Results: Seroost returns ranked, relevant code snippets with metadata

4. Integration: AI agents can use these results to understand and work with your code

Benefits for AI Agents

• Faster Code Discovery: Find relevant code without reading entire files

• Semantic Understanding: Search by intent, not just exact text matches

• Contextual Results: Get ranked results with relevance scores

• Large Codebase Support: Handle projects with thousands of files

• Cross-File Analysis: Find usage patterns across the entire project

License

ISC

Contributing

Contributions welcome! Please feel free to submit issues and pull requests.

Related Projects

• Seroost - The underlying search engine

• Model Context Protocol - The protocol this server implements