GREB-MCP

GREB-MCP

A hybrid search MCP that enables users to find coding chunks like RAG without indexing their codebase, without any vector database. World's first context attention MCP. It gives results in below 5 seconds in a repository as big as VS Code.

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README

GREB MCP Server

Semantic code search for AI agents. Search your codebase using natural language queries.

npm version PyPI version

Features

  • Natural Language Search - Describe what you're looking for in plain English
  • High-Precision Results - Smart ranking returns the most relevant code first
  • Works with Any MCP Client - Claude Desktop, Cursor, Windsurf, Cline, Kiro, and more
  • No Indexing Required - Search any codebase instantly without setup
  • Fast - Results in under 5 seconds even for large repositories

Installation

Install Greb globally using pip or npm:

Python:

pip install cheetah-greb

Node.js:

npm install -g cheetah-greb

Get Your API Key

  1. Go to Dashboard → API Keys
  2. Click Create API Key
  3. Copy the key (starts with grb_)

Configuration

Add to your MCP client config (Cursor, Windsurf, Claude Desktop, Kiro, etc.):

Python installation:

{
  "mcpServers": {
    "greb-mcp": {
      "command": "greb-mcp",
      "env": {
        "GREB_API_KEY": "grb_your_api_key_here"
      }
    }
  }
}

Node.js installation:

{
  "mcpServers": {
    "greb-mcp": {
      "command": "greb-mcp-js",
      "env": {
        "GREB_API_KEY": "grb_your_api_key_here"
      }
    }
  }
}

Claude Code Setup

Mac/Linux (Python):

claude mcp add --transport stdio greb-mcp --env GREB_API_KEY=grb_your_api_key_here -- greb-mcp

Windows PowerShell (Python):

claude mcp add greb-mcp greb-mcp --transport stdio --env "GREB_API_KEY=grb_your_api_key_here"

Mac/Linux (Node.js):

claude mcp add --transport stdio greb-mcp --env GREB_API_KEY=grb_your_api_key_here -- greb-mcp-js

Windows PowerShell (Node.js):

claude mcp add greb-mcp greb-mcp-js --transport stdio --env "GREB_API_KEY=grb_your_api_key_here"

Tool: code_search

Search code using natural language queries powered by AI.

Parameters

Parameter Type Required Description
query string Yes Natural language search query
keywords object Yes Search configuration
keywords.primary_terms string[] Yes High-level semantic terms (e.g., "authentication", "database")
keywords.code_patterns string[] No Literal code patterns to grep for
keywords.file_patterns string[] Yes File extensions to search (e.g., ["*.ts", "*.js"])
keywords.intent string Yes Brief description of what you're looking for
directory string Yes Full absolute path to directory to search

Example

{
  "query": "find authentication middleware",
  "keywords": {
    "primary_terms": ["authentication", "middleware", "jwt"],
    "code_patterns": ["authenticate(", "isAuthenticated"],
    "file_patterns": ["*.js", "*.ts"],
    "intent": "find auth middleware implementation"
  },
  "directory": "/Users/dev/my-project"
}

Response

Returns ranked code snippets with:

  • File paths
  • Line numbers
  • Relevance scores
  • Code content
  • Reasoning for each match

Usage Examples

Ask your AI assistant to search code naturally:

"Use greb mcp to find authentication middleware"
"Use greb mcp to find all API endpoints"
"Use greb mcp to look for database connection setup"
"Use greb mcp to find where user validation happens"
"Use greb mcp to search for error handling patterns"

Links

License

This project is licensed under the MIT License — see the LICENSE file for details.

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