MCP Scout (smarter-faster-better-mcp)
@iHaiduk
About MCP Scout (smarter-faster-better-mcp)
A blazing fast, ultra-lightweight Model Context Protocol (MCP) server for AST-based code intelligence and semantic discovery. It runs as compiled Node.js JavaScript for npx, uses oxc-parser by default for JavaScript/TypeScript, and can opt into web-tree-sitter for polyglot reposi
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"scout": {
"command": "npx",
"args": [
"smarter-faster-better-mcp"
]
}
}
}Tools
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Overview
What is MCP Scout?
MCP Scout is a blazing fast, ultra-lightweight Model Context Protocol server for AST-based code intelligence and semantic discovery. It uses the Rust-powered oxc-parser by default for JavaScript/TypeScript and can optionally use web-tree-sitter for polyglot repositories (Python, Go, Rust, Java, C/C++, C#, PHP, Dart, Ruby).
How to use MCP Scout?
Run directly via npx smarter-faster-better-mcp. Configure an LLM provider by creating a .env file in your project root with SCOUT_BASE_URL, SCOUT_API_KEY, and SCOUT_MODEL. Add the server to your MCP client (Claude Desktop, Cursor, Windsurf, Trae, Claude Code) using the command npx smarter-faster-better-mcp. Optionally set the --parser tree-sitter flag for polyglot support.
Key features of MCP Scout
- Zero native bindings β installs in milliseconds without node-gyp
- Deterministic Jaro-Winkler filtering for instant symbol ranking
- LLM chunk parallelism distributes classification requests efficiently
- AST extraction with
summaryOnlymode saves up to 90% of tokens - AST + regex dependency mapping via ripgrep
- Read-only contract β never modifies project source files
- Supports JavaScript, TypeScript, Python, Go, Rust, Ruby, Java, C/C++, C#, PHP, Dart
Use cases of MCP Scout
- Rapid code search and symbol discovery in large JavaScript/TypeScript projects
- Tracing exact dependency imports across files in a monorepo
- Providing LLMs with summarized file context without reading entire raw files
- Analyzing polyglot codebases (e.g., React frontend + Python backend)
- Reducing token consumption and context overflow during AI-assisted code analysis
FAQ from MCP Scout
What are the runtime requirements for MCP Scout?
Node.js >= 18, Bun >= 1.1.0 (for development testing), and Ripgrep (rg) for symbol dependency lookup.
How does MCP Scout achieve such high speed?
It uses the Rust-based oxc-parser for instant file parsing, deterministic Jaro-Winkler edit distance filtering, LLM chunk parallelism, and AST extraction that collapses code bodies into stubs, saving tokens.
Does MCP Scout modify my project files?
No, it is strictly read-only. The only writes are to its own cache files (.project_map.json and .scout-cache/), which can be safely cleaned with the cleanup_workspace tool.
Which parser engine should I choose?
Use the default oxc for pure JavaScript/TypeScript codebases. Switch to tree-sitter (via --parser tree-sitter) for monorepos or backend services that include Python, Go, Rust, Ruby, Java, C/C++, C#, PHP, or Dart files. Even in tree-sitter mode, JS/TS files are still parsed by oxc for maximum performance.
How do I configure MCP Scout?
Create a .env file in your project root with the required variables SCOUT_BASE_URL, SCOUT_API_KEY, and SCOUT_MODEL. Optional variables include SCOUT_LLM_TIMEOUT_MS, SCOUT_CONFIDENCE_THRESHOLD, SCOUT_LLM_PARALLELISM, and SCOUT_PARSER. The server loads these automatically on startup.
Frequently asked questions
What are the runtime requirements for MCP Scout?
Node.js >= 18, Bun >= 1.1.0 (for development testing), and Ripgrep (`rg`) for symbol dependency lookup.
How does MCP Scout achieve such high speed?
It uses the Rust-based oxc-parser for instant file parsing, deterministic Jaro-Winkler edit distance filtering, LLM chunk parallelism, and AST extraction that collapses code bodies into stubs, saving tokens.
Does MCP Scout modify my project files?
No, it is strictly read-only. The only writes are to its own cache files (`.project_map.json` and `.scout-cache/`), which can be safely cleaned with the `cleanup_workspace` tool.
Which parser engine should I choose?
Use the default `oxc` for pure JavaScript/TypeScript codebases. Switch to `tree-sitter` (via `--parser tree-sitter`) for monorepos or backend services that include Python, Go, Rust, Ruby, Java, C/C++, C#, PHP, or Dart files. Even in tree-sitter mode, JS/TS files are still parsed by oxc for maximum performance.
How do I configure MCP Scout?
Create a `.env` file in your project root with the required variables `SCOUT_BASE_URL`, `SCOUT_API_KEY`, and `SCOUT_MODEL`. Optional variables include `SCOUT_LLM_TIMEOUT_MS`, `SCOUT_CONFIDENCE_THRESHOLD`, `SCOUT_LLM_PARALLELISM`, and `SCOUT_PARSER`. The server loads these automatically on startup.
Basic information
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