Scopewalker MCP
MCP server providing codebase analysis tools for AI assistants, including line counts, function metrics, threshold checks, and code quality detection.
README
Scopewalker MCP
AI agents will happily create 1000+ line source files and add a 20th parameter to a function call, even if there's a rule file telling them not to. Scopewalker exists to enforce stricter codebase standards.
It's a local MCP server (open source, runs over stdio, makes no network calls) that exposes 8 read-only tools:
get_line_counts- line countsget_functions- function counts and per-function line metricsget_complexity_metrics- cognitive complexity, nesting depth, parameter countscheck_thresholds- oversized-file/function checker against configurable thresholdsget_code_inventory- classes, methods, functions, and exports inventoryget_documentation_coverage- doc coverageget_code_smells- TODO/FIXME/HACK/BUG markers in comments, plus unsafe castsget_prop_drilling- parameter threading across function chains
It's tree-sitter + tokei + fast-glob under the hood; nothing is custom-parsed. Tested on macOS with Claude Code, but should work with Cursor, VS Code, Windsurf, Gemini CLI, Codex, or anything else that speaks MCP.
See TOOLS.md for detailed parameter and response documentation.
Safety Defaults
- No network access: All analysis runs locally over stdio — no data leaves your machine, no API keys or external services involved.
- Path scoping: All tools only operate inside allowed roots (defaults: current working directory and system temp). Override with
SCOPEWALKER_ALLOWED_ROOTS=/abs/path1,/abs/path2. - Large file guard: AST-based tools skip files larger than 1 MB to avoid excessive memory/CPU use. Tokei-based line counts do not enforce this limit.
- Output limits: Tools default to returning 20 files/items unless
limitis set. - Comment redaction:
get_code_smellsredacts comment text by default; passinclude_text: trueto return snippets explicitly.
Requirements
- Node.js 22+
- tokei - Install via
brew install tokeiorcargo install tokei
Installation
npm install
npm run build
Configuration
Claude Code
Add to ~/.claude.json:
{
"mcpServers": {
"scopewalker-mcp": {
"command": "node",
"args": ["/path/to/scopewalker-mcp/dist/index.js"]
}
}
}
Or use the CLI:
claude mcp add scopewalker-mcp --scope user -- node /path/to/scopewalker-mcp/dist/index.js
See Claude Code MCP documentation for details.
Cursor
Add to ~/.cursor/mcp.json (global) or .cursor/mcp.json (project):
{
"mcpServers": {
"scopewalker-mcp": {
"command": "node",
"args": ["/path/to/scopewalker-mcp/dist/index.js"]
}
}
}
Or configure via File > Preferences > Cursor Settings > MCP.
See Cursor MCP documentation for details.
VS Code (GitHub Copilot)
Add to .vscode/mcp.json in your workspace:
{
"servers": {
"scopewalker-mcp": {
"command": "node",
"args": ["/path/to/scopewalker-mcp/dist/index.js"]
}
}
}
Requires VS Code 1.102+ with Agent Mode enabled.
See VS Code MCP documentation for details.
Windsurf
Add to ~/.codeium/windsurf/mcp_config.json:
{
"mcpServers": {
"scopewalker-mcp": {
"command": "node",
"args": ["/path/to/scopewalker-mcp/dist/index.js"]
}
}
}
Or configure via Windsurf Settings > Cascade > Manage MCPs.
See Windsurf MCP documentation for details.
Gemini CLI
Add to ~/.gemini/settings.json:
{
"mcpServers": {
"scopewalker-mcp": {
"command": "node",
"args": ["/path/to/scopewalker-mcp/dist/index.js"]
}
}
}
See Gemini CLI MCP documentation for details.
OpenAI Codex CLI
Add to ~/.codex/config.toml:
[mcp_servers.scopewalker-mcp]
command = "node"
args = ["/path/to/scopewalker-mcp/dist/index.js"]
Or use the CLI:
codex mcp add scopewalker-mcp -- node /path/to/scopewalker-mcp/dist/index.js
See Codex MCP documentation for details.
Usage
Once configured, the assistant calls Scopewalker's tools on its own — no special syntax needed. Ask things like:
- "Check this repo against our size thresholds before I commit"
- "Which functions in
src/have the highest cognitive complexity?" - "Find undocumented exports in
src/auth" - "Are there any TODO/FIXME/HACK markers left in this module?"
- "Show me functions that take more than 5 parameters"
It picks the right tool (check_thresholds, get_complexity_metrics, get_documentation_coverage, get_code_smells, etc.) and parameters for the request. See TOOLS.md for the quick reference and docs/ for per-tool parameters and example responses.
This repo also dogfoods its own tools via Claude Code skills and agents:
.claude/skills/check-quality/SKILL.md— runscheck_thresholdsandget_code_smellsas part of the quality gate.claude/agents/standards-enforcer.md— uses the full tool set to find and fix standards violations.claude/agents/docs-reality-sync.md— usesget_documentation_coverage,get_code_inventory, andget_functionsto keep docs in sync with code
Development
npm run build # Build the project
npm run check # Lint + typecheck
npm run test # Run tests
npm run test:coverage # Run tests with coverage
See CONTRIBUTING.md for contribution guidelines and docs/patterns.md for tool registration, error handling, and testing patterns.
Supported Languages
Function detection and parsing support:
- TypeScript/JavaScript
- Python
- Go
- Rust
- Java
- C/C++
- Ruby
Architecture
| Task | Library |
|---|---|
| Line counting | tokei (CLI) |
| Code parsing | tree-sitter |
| File discovery | fast-glob |
| Input validation | zod |
License
MIT
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。