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A Model Context Protocol server for analyzing large codebases using Gemini 2.0

Project description

DeepView MCP

DeepView MCP is a Model Context Protocol server that enables IDEs like Cursor and Windsurf to analyze large codebases using Gemini's extensive context window.

PyPI version

Features

  • Load an entire codebase from a single text file (e.g., created with tools like repomix)
  • Query the codebase using Gemini's large context window
  • Connect to IDEs that support the MCP protocol, like Cursor and Windsurf
  • Configurable Gemini model selection via command-line arguments

Prerequisites

Installation

Using pip

pip install deepview-mcp

Usage

Starting the Server

Note: you don't need to start the server manually. These parameters are configured in your MCP setup in your IDE (see below).

# Basic usage with default settings
deepview-mcp [path/to/codebase.txt]

# Specify a different Gemini model
deepview-mcp [path/to/codebase.txt] --model gemini-2.0-pro

# Change log level
deepview-mcp [path/to/codebase.txt] --log-level DEBUG

The codebase file parameter is optional. If not provided, you'll need to specify it when making queries.

Command-line Options

  • --model MODEL: Specify the Gemini model to use (default: gemini-2.0-flash-lite)
  • --log-level {DEBUG,INFO,WARNING,ERROR,CRITICAL}: Set the logging level (default: INFO)

Using with an IDE (Cursor/Windsurf/...)

  1. Open IDE settings
  2. Navigate to the MCP configuration
  3. Add a new MCP server with the following configuration:
    {
      "mcpServers": {
        "deepview": {
          "command": "/path/to/deepview-mcp",
          "args": ["/path/to/codebase.txt"],
          "env": {
            "GEMINI_API_KEY": "your_gemini_api_key"
          }
        }
      }
    }
    
  4. Reload MCP servers configuration

Available Tools

The server provides one tool:

  1. deepview: Ask a question about the codebase
    • Required parameter: question - The question to ask about the codebase
    • Optional parameter: codebase_file - Path to a codebase file to load before querying

Preparing Your Codebase

DeepView MCP requires a single file containing your entire codebase. You can use repomix to prepare your codebase in an AI-friendly format.

Using repomix

  1. Basic Usage: Run repomix in your project directory to create a default output file:
# Make sure you're using Node.js 18.17.0 or higher
npx repomix

This will generate a repomix-output.xml file containing your codebase.

  1. Custom Configuration: Create a configuration file to customize which files get packaged and the output format:
npx repomix --init

This creates a repomix.config.json file that you can edit to:

  • Include/exclude specific files or directories
  • Change the output format (XML, JSON, TXT)
  • Set the output filename
  • Configure other packaging options

Example repomix Configuration

Here's an example repomix.config.json file:

{
  "include": [
    "**/*.py",
    "**/*.js",
    "**/*.ts",
    "**/*.jsx",
    "**/*.tsx"
  ],
  "exclude": [
    "node_modules/**",
    "venv/**",
    "**/__pycache__/**",
    "**/test/**"
  ],
  "output": {
    "format": "xml",
    "filename": "my-codebase.xml"
  }
}

For more information on repomix, visit the repomix GitHub repository.

License

MIT

Author

Dmitry Degtyarev (ddegtyarev@gmail.com)

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