admica/FileScopeMCP
by Various
Analyzes your codebase identifying important files based on dependency relationships. Generates diagrams and importance scores per file, helping AI assistants understand the codeba
MCP
admica/FileScopeMCP
Added 1 June 2026
Overview
FileScopeMCP analyzes a codebase by parsing dependency relationships across files. It generates importance scores and diagrams for each file, helping AI assistants understand the project structure. The tool supports Python, C, C++, Rust, Zig, and Lua.
Best for
Best for
Developers working with supported languages who want to give AI tools a structured understanding of their codebase
Use cases
- Identify critical files in a large codebase for refactoring or documentation
- Generate dependency diagrams to visualize module relationships
- Provide AI assistants with a structured map of the codebase for context-aware suggestions
How to use
Install
npm run install-claude-code # or: npx filescope-install --claude-code Tools exposed
find_important_filesget_file_summarylist_filesfind_symbolfind_callersfind_calleeslist_changed_sinceget_communitiesdetect_cyclesget_cycles_for_filescan_allset_base_directoryset_file_summaryset_file_importanceexclude_and_remove
Tested with
Claude Code, Cursor, ChatGPT
Notes
FileScopeMCP analyzes a codebase by parsing dependency relationships across files. It generates importance scores and diagrams for each file, helping AI assistants understand the project structure. The tool supports Python, C, C++, Rust, Zig, and Lua.
292 stars on GitHub. Last updated 2026-05-10.
Use cases
- Identify critical files in a large codebase for refactoring or documentation
- Generate dependency diagrams to visualize module relationships
- Provide AI assistants with a structured map of the codebase for context-aware suggestions
Pros
- Automatically parses multiple popular languages without manual configuration
- Produces concrete importance scores and diagrams, not just raw dependency lists
- Open source with 292 stars and active TypeScript codebase
Cons
- Limited to languages it can parse, excluding many others like Java or JavaScript
- Dependency analysis may miss dynamic imports or runtime-resolved dependencies
- Requires integration with an MCP-compatible AI assistant to be useful
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Automatically parses multiple popular languages without manual configuration
- Produces concrete importance scores and diagrams, not just raw dependency lists
- Open source with 292 stars and active TypeScript codebase
Cons
- Limited to languages it can parse, excluding many others like Java or JavaScript
- Dependency analysis may miss dynamic imports or runtime-resolved dependencies
- Requires integration with an MCP-compatible AI assistant to be useful
Pairs with
Other entries in the index that connect to this one. Click through to see the chain.
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