Seroost Search MCP Server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Seroost Search MCP Serverfind React components that handle form validation"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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:
{
"mcpServers": {
"seroost-search": {
"command": "node",
"args": ["/path/to/search-mcp/build/index.js"]
}
}
}Available Tools
seroost_set_index
Configure the target directory for indexing.
Parameters:
path(string): Absolute path to the directory to index
Example:
{
"name": "seroost_set_index",
"arguments": {
"path": "/home/user/my-project"
}
}seroost_index
Build the search index for the configured directory.
Parameters: None (uses path set by seroost_set_index)
Example:
{
"name": "seroost_index",
"arguments": {}
}seroost_search
Search through the indexed codebase.
Parameters:
query(string): Search term, function name, or natural language description
Example:
{
"name": "seroost_search",
"arguments": {
"query": "user authentication functions"
}
}Response:
{
"query": "user authentication functions",
"results": [
{
"rank": 1,
"path": "/home/user/project/src/auth.js",
"score": 0.8543,
"line_matches": [
{
"line": 42,
"content": "function authenticateUser(credentials) {"
}
]
}
]
}Workflow
Set Index Path: Use
seroost_set_indexto configure which directory to searchBuild Index: Run
seroost_indexto process and index all filesSearch: Use
seroost_searchto 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
npm run buildProject Structure
src/
├── index.ts # MCP server setup and tool definitions
├── commands.ts # Seroost command wrappers
build/ # Compiled JavaScript outputHow 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
Resources
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Appeared in Searches
- Assistance with Java development
- MCP server for semantic code snippet search
- A tool for searching code using semantic understanding
- A server for searching and retrieving information using keyword, semantic, or hybrid search methods
- Code intelligence tools for LLMs to understand codebase structure and locate functionality
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