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
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 PATHClone this repository:
git clone https://github.com/Parado-xy/semantic-search-mcp cd search-mcpInstall dependencies:
npm installBuild 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
Set Index Path: Use
seroost_set_index
to configure which directory to searchBuild Index: Run
seroost_index
to process and index all filesSearch: 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:
Indexing: Seroost processes your codebase and creates a searchable index
Querying: AI agents send search queries through the MCP protocol
Results: Seroost returns ranked, relevant code snippets with metadata
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
local-only server
The server can only run on the client's local machine because it depends on local resources.
Enables AI agents to perform semantic code search across entire codebases using natural language queries. Provides fast indexing and ranked search results with line numbers and file paths through the Seroost search engine.