Code Indexer

Code Index MCP

<div align="center">

Intelligent code indexing and analysis for Large Language Models

Transform how AI understands your codebase with advanced search, analysis, and navigation capabilities.

</div>

<a href="https://glama.ai/mcp/servers/@johnhuang316/code-index-mcp">

</a>

Overview

Code Index MCP is a Model Context Protocol server that bridges the gap between AI models and complex codebases. It provides intelligent indexing, advanced search capabilities, and detailed code analysis to help AI assistants understand and navigate your projects effectively.

Perfect for: Code review, refactoring, documentation generation, debugging assistance, and architectural analysis.

Quick Start

🚀 Recommended Setup (Most Users)

The easiest way to get started with any MCP-compatible application:

Prerequisites: Python 3.10+ and uv

1. Add to your MCP configuration (e.g., claude_desktop_config.json or ~/.claude.json):

   {

     "mcpServers": {

       "code-index": {

         "command": "uvx",

         "args": ["code-index-mcp"]

       }

     }

   }

   

> Optional: append --project-path /absolute/path/to/repo to the args array so the server
> initializes with that repository automatically (equivalent to calling set_project_path
> after startup).

2. Restart your application – uvx automatically handles installation and execution

3. Start using (give these prompts to your AI assistant):

   Set the project path to /Users/dev/my-react-app

   Find all TypeScript files in this project  

   Search for "authentication" functions

   Analyze the main App.tsx file

   

If you launch with --project-path, you can skip the first command above - the server already
knows the project location.

Codex CLI Configuration

If you are using Anthropic's Codex CLI, add the server to ~/.codex/config.toml.
On Windows the file lives at C:\Users\<you>\.codex\config.toml:

[mcp_servers.code-index]
type = "stdio"
command = "uvx"
args = ["code-index-mcp"]

> You can append --project-path C:/absolute/path/to/repo to the args list to set the project > automatically on startup (same effect as running the set_project_path tool).

On Windows, uvx needs the standard profile directories to be present.
Keep the environment override in the same block so the MCP starts reliably:

env = {
  HOME = "C:\\Users\\<you>",
  APPDATA = "C:\\Users\\<you>\\AppData\\Roaming",
  LOCALAPPDATA = "C:\\Users\\<you>\\AppData\\Local",
  SystemRoot = "C:\\Windows"
}

Linux and macOS already expose the required XDG paths and HOME, so you can usually omit the env
table there.
Add overrides only if you run the CLI inside a restricted container.

FastMCP & Discovery Manifests

- Run fastmcp run fastmcp.json to launch the server via FastMCP with
the correct source entrypoint and dependency metadata. Pass --project-path (or call the
set_project_path tool after startup) so the index boots against the right repository.
- Serve or copy .well-known/mcp.json to share a standards-compliant MCP manifest. Clients that
support the .well-known convention (e.g., Claude Desktop, Codex CLI) can import this file
directly instead of crafting configs manually.
- Publish .well-known/mcp.llmfeed.json when you want to expose the richer LLM Feed metadata.
It references the same code-index server definition plus documentation/source links, which
helps registries present descriptions, tags, and capabilities automatically.

When sharing the manifests, remind consumers to supply --project-path (or to call
set_project_path) so the server indexes the intended repository.

Typical Use Cases

Code Review: "Find all places using the old API"
Refactoring Help: "Where is this function called?"
Learning Projects: "Show me the main components of this React project"
Debugging: "Search for all error handling related code"

Key Features

🔍 Intelligent Search & Analysis

- Dual-Strategy Architecture: Specialized tree-sitter parsing for 10 core languages, fallback strategy for 50+ file types - Direct Tree-sitter Integration: No regex fallbacks for specialized languages - fail fast with clear errors - Advanced Search: Auto-detects and uses the best available tool (ugrep, ripgrep, ag, or grep) - Universal File Support: Comprehensive coverage from advanced AST parsing to basic file indexing - File Analysis: Deep insights into structure, imports, classes, methods, and complexity metrics after running build_deep_index

🗂️ Multi-Language Support

- 10 Languages with Tree-sitter AST Parsing: Python, JavaScript, TypeScript, Java, Kotlin, C#, Go, Objective-C, Zig, Rust - 50+ File Types with Fallback Strategy: C/C++, Ruby, PHP, and all other programming languages - Document & Config Files: Markdown, JSON, YAML, XML with appropriate handling - Web Frontend: Vue, React, Svelte, HTML, CSS, SCSS - Java Web & Build: JSP/Tag files (.jsp, .jspx, .jspf, .tag, .tagx), Grails/GSP (.gsp), Gradle & Groovy builds (.gradle, .groovy), .properties, and Protocol Buffers (.proto) - Database: SQL variants, NoSQL, stored procedures, migrations - Configuration: JSON, YAML, XML, Markdown - View complete list

⚡ Real-time Monitoring & Auto-refresh

- File Watcher: Automatic index updates when files change - Cross-platform: Native OS file system monitoring - Smart Processing: Batches rapid changes to prevent excessive rebuilds - Shallow Index Refresh: Watches file changes and keeps the file list current; run a deep rebuild when you need symbol metadata

⚡ Performance & Efficiency

- Tree-sitter AST Parsing: Native syntax parsing for accurate symbol extraction - Persistent Caching: Stores indexes for lightning-fast subsequent access - Smart Filtering: Intelligent exclusion of build directories and temporary files - Memory Efficient: Optimized for large codebases - Direct Dependencies: No fallback mechanisms - fail fast with clear error messages

Supported File Types

<details>
<summary><strong>📁 Programming Languages (Click to expand)</strong></summary>

Languages with Specialized Tree-sitter Strategies:
- Python (.py, .pyw) - Full AST analysis with class/method extraction and call tracking
- JavaScript (.js, .jsx, .mjs, .cjs) - ES6+ class and function parsing with tree-sitter
- TypeScript (.ts, .tsx) - Complete type-aware symbol extraction with interfaces
- Java (.java) - Full class hierarchy, method signatures, and call relationships
- Kotlin (.kt, .kts) - Package-aware symbol extraction with methods and call relationships
- C# (.cs) - Namespace-aware type/member extraction with call relationships
- Go (.go) - Struct methods, receiver types, and function analysis
- Rust (.rs) - Functions, module-aware names, impl methods, structs/enums/traits, and basic call relationships
- Objective-C (.m, .mm) - Class/instance method distinction with +/- notation
- Zig (.zig, .zon) - Function and struct parsing with tree-sitter AST

…