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A robust, production-ready Model Context Protocol (MCP) server that empowers AI agents with deep understanding and manipulation capabilities for software repositories. It inclued crucial tools for code quality and safety.

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Project Scope MCP Server

A robust, production-ready Model Context Protocol (MCP) server empowering AI agents with deep semantic understanding and safe manipulation of software repositories.


Overview

Project Scope moves beyond simple file reading to provide semantic analysis, AST-based refactoring, Git integration, and defense-in-depth security validation. It allows Large Language Models (LLMs) to interact with codebases reliably and safely, bridging the gap between chat interfaces and complex development workflows.

Key Features

  • Semantic Repository Analysis: Parse and understand code structure, dependencies, and relationships using Tree-sitter.
  • Context-Aware Security: Advanced scanner with zero false positives on source code, detecting SQLi, XSS, and RCE attempts in runtime inputs.
  • Safe Refactoring: AST-based renaming and extraction tools with "preview first" capabilities to prevent syntax errors.
  • Git Integration: Comprehensive version control management including history, diffing, and branch operations.
  • Defense-in-Depth: Multi-layered protection including Prompt Injection detection (Regex + LLM Guard), input validation, and file access controls.

Table of Contents


npm version


Quick Start

Run instantly with npx:

npx -y @adityasasidhar/project-scope-mcp

Installation (Source)

To build from source:

# Clone the repository
git clone https://github.com/adityasasidhar/Project-Scope-MCP.git
cd Project-Scope-MCP

# Install dependencies
npm install

# Build the project
npm run build

Configuration

Security is a primary focus of Project Scope. The server is highly customizable to match your risk profile.

Security Modes

  • strict (default): Blocks operations immediately if a potential threat is detected.
  • advisory: Logs and warnings are generated, but operations are allowed to proceed (useful for initial audits).

Sensitivity Levels

  • high: Aggressive detection, useful for untrusted user inputs.
  • medium (default): Balanced profile for standard development.
  • low: Only flags high-confidence known attack signatures.

LLM Guard (Optional)

For state-of-the-art protection against prompt injection attacks, enable Meta Llama Prompt Guard 2:

  • Set useGuardModel: true in your requests.
  • Requires a valid HuggingFace API token.

Security Architecture

The server features a Context-Aware Security Scanner designed to eliminate false positives while maintaining rigorous threat detection.

Intelligent Context Detection

The scanner uses file categorization to determine the appropriate validation strategy:

File Type Extension Scanning Strategy Reason
Source Code .ts, .py, .go Skipped Source code syntax (semi-colons, pipes) mimics attack patterns.
Templates .hbs, .jinja2 Syntax-Aware Validates usage but allows standard template tokens.
Config .json, .yaml Minimal Allows standard configuration strings.
Runtime Input (None) Strict Full regex and heuristic scanning for malicious payloads.

Line-Level Filtering

Within analyzed files, the engine intelligently ignores:

  • Comments: //, /*, #
  • Imports: import, require
  • Definitions: interface, type, class

This ensures that documenting a security vulnerability in a comment or test file does not trigger a false alarm, while executing or receiving a malicious payload is caught.


πŸ”Œ Connecting Clients

Claude Desktop

  1. Open your configuration file:

    • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
    • Windows: %APPDATA%\Claude\claude_desktop_config.json
  2. Add the server definition:

{
  "mcpServers": {
    "project-scope": {
      "command": "node",
      "args": ["/absolute/path/to/ProjectScopeMCP/dist/index.js"]
    }
  }
}

Claude Code (CLI)

The official Claude Code CLI supports MCP natively.

  1. Add the server: Run the following command in your terminal:

    claude mcp add project-scope -- npx -y @adityasasidhar/project-scope-mcp
  2. Verify: Run claude and type /mcp to see the connected servers.

Codex CLI

Codex CLI (if applicable) supports MCP via its TOML configuration.

  1. Edit Configuration: Open ~/.codex/config.toml.

  2. Add Server:

    [mcp.servers.project-scope]
    command = "npx"
    args = ["-y", "@adityasasidhar/project-scope-mcp"]

Gemini CLI

Gemini CLI supports MCP via its JSON configuration.

  1. Edit Configuration: Open ~/.gemini/settings.json (create if it doesn't exist).

  2. Add Server:

    {
      "mcpServers": {
        "project-scope": {
          "command": "npx",
          "args": ["-y", "@adityasasidhar/project-scope-mcp"]
        }
      }
    }

Generic Clients

For any other client that supports MCP (like Windsurf, Smithery, Goose, or custom implementations), use the standard stdio configuration:

npx -y @adityasasidhar/project-scope-mcp

Cursor

  1. Open Cursor Settings (Cmd/Ctrl + Shift + J).
  2. Navigate to Features > MCP Servers.
  3. Click + Add New MCP Server.
  4. Configure:
    • Name: project-scope
    • Type: command
    • Command: node /absolute/path/to/ProjectScopeMCP/dist/index.js (Or use npm run start if preferred)

GitHub Copilot (VS Code)

  1. Open GitHub Copilot Chat in VS Code.
  2. Click the Attach Context (paperclip) or Tools icons.
  3. Select Connect to MCP Server...
  4. Choose Command (or similar) and enter:
    • Command: npx
    • Args: -y @adityasasidhar/project-scope-mcp

Note: Requires GitHub Copilot Agent Mode enabled in VS Code settings.

Tool Reference

Repository Analysis

get_repo_structure

Generates a hierarchical map of the repository, respecting .gitignore.

  • input: { "path": "/path/to/repo", "format": "tree" }

analyze_impact

Predicts the "blast radius" of changing a symbol (function, variable) by finding all references via AST.

  • input: { "path": "...", "filePath": "src/utils.ts", "symbolName": "processData", "line": 42 }

Security Scanning

scan_repo_for_threats

Audits the entire repository for security risks (secrets, injection patterns). Skips ignored files for performance.

  • input: { "path": "/path/to/repo", "excludePatterns": ["dist"] }

scan_file_for_threats

Deep-scans a single file or string with the context-aware engine.

  • input: { "filePath": "/path/to/file.ts", "mode": "strict" }

validate_shell_input

Validates shell commands for injection risks before execution.

  • input: { "input": "rm -rf /", "mode": "strict" }

Refactoring

refactor_rename

Semantically renames a symbol across the project.

  • input: { "path": "...", "filePath": "...", "oldName": "foo", "newName": "bar", "apply": false }
  • Note: Always use "apply": false first to preview changes.

refactor_extract_function

Extracts selected lines of code into a new function.

  • input: { "path": "...", "filePath": "...", "startLine": 10, "endLine": 20, "functionName": "newFunc" }

Git Operations

Includes standard Git tools for agentic workflows:

  • git_status
  • git_commit_history
  • git_compare_branches
  • git_init

Troubleshooting

"Repo Scan Too Slow"

  • Add large directories (e.g., vendor, node_modules) to excludePatterns.
  • Large files (>1MB) are automatically skipped.

"Refactoring Failed to Parse"

  • Ensure the code is syntactically valid before refactoring. Tree-sitter parsers typically require valid syntax to generate accurate ASTs.

License

This project is licensed under the ISC License.

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A robust, production-ready Model Context Protocol (MCP) server that empowers AI agents with deep understanding and manipulation capabilities for software repositories. It inclued crucial tools for code quality and safety.

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