What distinguishes Project Scope from naive pattern-based scanners?
Project Scope uses context-sensitive scanning that parses source code rather than pattern-matching, eliminating false positives on legitimate code.
@adityasasidhar
Basic information
A production-ready MCP server that gives AI agents deep codebase understanding. Features AST-based semantic analysis, context-aware security scanning (zero false positives on source code), safe refactoring tools with previews, and comprehensive Git operations.
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"project-scope": {
"command": "npx",
"args": [
"-y",
"@adityasasidhar/project-scope-mcp"
]
}
}
}Tool list not available yet
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Fetch the live tool list by running this server in a temporary sandbox using the button above.
Project Scope is a production-grade MCP server for semantic code intelligence and safe repository control. It gives AI agents deep, structural understanding of codebases and the ability to modify them safely through AST analysis, context-aware security scanning, refactoring tools, and Git operations.
To use Project Scope, configure your AI agent’s MCP client to connect to this server. You can then invoke its tools, such as get_repo_structure for repository analysis, scan_repo_for_threats for security scanning, refactor_rename for refactoring, and git_status for Git operations.
Project Scope uses context-sensitive scanning that parses source code rather than pattern-matching, eliminating false positives on legitimate code.
Yes, Project Scope is fully local execution, built with TypeScript, Node.js, and Tree-sitter.
It includes prompt injection detection, regex and heuristic guards, optional integration with Meta Llama Prompt Guard 2, and file access and execution boundaries.
Yes, it enforces mandatory preview before applying refactors and uses AST analysis to guarantee syntax correctness.
Project Scope supports repository status, commit history, branch comparison, and initialization.

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