{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"awesome-filescopemcp","slug":"filescopemcp","name":"FileScopeMCP","type":"mcp","url":"https://github.com/admica/FileScopeMCP","page_url":"https://unfragile.ai/filescopemcp","categories":["mcp-servers"],"tags":[],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"awesome-filescopemcp__cap_0","uri":"capability://data.processing.analysis.multi.language.dependency.graph.construction.with.bidirectional.tracking","name":"multi-language dependency graph construction with bidirectional tracking","description":"Parses source code in Python, Lua, C, C++, Rust, and Zig using language-specific import pattern matching (regex-based for each language) to build a bidirectional dependency map. The system constructs a directed graph where nodes are files and edges represent import relationships, enabling traversal of both incoming and outgoing dependencies. Uses buildDependentMap() to resolve import paths and track which files depend on which other files across the entire codebase.","intents":["understand which files are most critical by analyzing how many other files depend on them","identify dead code or unused modules by finding files with no incoming dependencies","trace the impact of changes by seeing all files that depend on a modified file","visualize the architecture of a multi-language project to understand module organization"],"best_for":["teams maintaining large codebases with mixed language ecosystems","developers refactoring legacy code and needing to understand coupling","AI assistants analyzing unfamiliar projects to prioritize which files to examine first"],"limitations":["regex-based pattern matching cannot resolve dynamic imports or conditional requires","does not track transitive dependencies through package managers (npm, pip, cargo)","relative import resolution may fail with complex path aliasing or monorepo structures","no support for circular dependency detection or cycle breaking strategies"],"requires":["Node.js 16+","source files in supported languages (Python, Lua, C, C++, Rust, Zig)","filesystem access to entire codebase"],"input_types":["source code files","directory paths","import statements (extracted via regex)"],"output_types":["dependency graph (JSON structure)","bidirectional edge lists","file importance scores (0-10)"],"categories":["data-processing-analysis","codebase-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-filescopemcp__cap_1","uri":"capability://data.processing.analysis.file.importance.scoring.with.multi.factor.ranking.algorithm","name":"file importance scoring with multi-factor ranking algorithm","description":"Calculates a normalized importance score (0-10) for each file using a weighted combination of factors: dependency count (how many files depend on it), file type heuristics (core files like main.py or index.ts score higher), directory depth (files closer to root are weighted higher), and naming patterns (files matching keywords like 'config', 'utils', 'core' receive boosts). The calculateImportance() function in file-utils.ts combines these signals into a single comparable metric, enabling AI assistants to prioritize which files to analyze first.","intents":["quickly identify the most critical files in an unfamiliar codebase for AI context window optimization","rank files by architectural importance to guide code review or refactoring priorities","surface entry points and core modules that should be understood before peripheral utilities","help AI assistants allocate limited context tokens to the highest-impact files"],"best_for":["AI-assisted code analysis where context is limited and prioritization is critical","onboarding developers to large projects by highlighting key files","automated code quality tools that need to focus analysis on important modules"],"limitations":["heuristic-based scoring may not reflect actual architectural importance in unconventional projects","naming pattern matching is language and convention-specific (assumes common naming like main.py, index.ts)","does not account for cyclomatic complexity, test coverage, or runtime criticality","scores are relative within a single codebase and not comparable across projects"],"requires":["completed dependency graph (buildDependentMap must run first)","file metadata (extension, path, name)","configurable weighting parameters (optional)"],"input_types":["file paths","file extensions","dependency counts","directory structure"],"output_types":["numeric score (0-10 float)","ranked file list","scoring breakdown (optional)"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-filescopemcp__cap_2","uri":"capability://image.visual.mermaid.diagram.generation.with.customizable.visualization.and.filtering","name":"mermaid diagram generation with customizable visualization and filtering","description":"Generates interactive Mermaid flowchart diagrams from the dependency graph, with support for customizable node styling, layout algorithms, and filtering options. The MermaidGenerator class in mermaid-generator.ts converts the file dependency graph into Mermaid syntax, applies visual styling based on file importance scores (color intensity, node size), and produces HTML output via createMermaidHtml(). Supports filtering by file type, importance threshold, or specific file patterns to reduce diagram complexity for large codebases.","intents":["visualize codebase architecture to understand module relationships at a glance","generate shareable diagrams for documentation or team communication","identify architectural patterns or anti-patterns (e.g., circular dependencies, hub-and-spoke structures)","create focused diagrams of subsystems by filtering to specific file types or importance levels"],"best_for":["technical documentation and architecture reviews","onboarding and knowledge transfer sessions","AI assistants that need to explain codebase structure to users","teams using Mermaid-compatible tools (GitHub, GitLab, Notion, etc.)"],"limitations":["Mermaid rendering performance degrades with >100 nodes; large codebases require aggressive filtering","no support for hierarchical/layered layouts (only flowchart layouts available in Mermaid)","styling is limited to Mermaid's built-in theme system; custom CSS is not supported","generated diagrams are static snapshots; real-time updates require regeneration"],"requires":["completed dependency graph","Mermaid.js library (included in HTML output)","modern browser for interactive rendering"],"input_types":["dependency graph (JSON)","file metadata (importance scores, types)","filter criteria (optional)"],"output_types":["Mermaid diagram syntax (text)","HTML file with embedded Mermaid rendering","SVG export (via Mermaid CLI)"],"categories":["image-visual","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-filescopemcp__cap_3","uri":"capability://memory.knowledge.file.tree.state.persistence.with.multi.project.configuration.management","name":"file tree state persistence with multi-project configuration management","description":"Manages persistent storage of file analysis results across multiple independent projects using a configuration-based approach. The storage-utils.ts module provides createFileTreeConfig(), saveFileTree(), and loadFileTree() functions that serialize the complete file tree (nodes, edges, importance scores, metadata) to disk in JSON format. Each project maintains its own configuration file, enabling users to analyze multiple codebases independently and reload previous analyses without re-scanning.","intents":["cache analysis results to avoid re-scanning large codebases on every tool invocation","maintain separate analysis contexts for multiple projects or branches","enable incremental updates by loading previous state and applying filesystem changes","share codebase analysis snapshots with team members or AI assistants"],"best_for":["teams analyzing multiple projects or monorepos with independent file trees","development workflows where codebase analysis is expensive and should be cached","CI/CD pipelines that need to persist analysis state across runs","collaborative scenarios where analysis results need to be shared or versioned"],"limitations":["no built-in versioning or diff tracking; overwrites previous state on save","JSON serialization can be slow for very large codebases (>10k files)","no automatic cache invalidation; stale analysis persists until explicitly refreshed","no conflict resolution for concurrent modifications to the same project config"],"requires":["filesystem write access to configuration directory","Node.js fs module","JSON serialization support"],"input_types":["file tree object (nodes, edges, metadata)","project configuration (paths, filters, settings)","file paths"],"output_types":["JSON configuration files","serialized file tree state","metadata (timestamps, version info)"],"categories":["memory-knowledge","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-filescopemcp__cap_4","uri":"capability://automation.workflow.real.time.filesystem.monitoring.with.automatic.dependency.graph.updates","name":"real-time filesystem monitoring with automatic dependency graph updates","description":"Watches the filesystem for changes (file creation, deletion, modification) using Node.js fs.watch() and automatically updates the dependency graph when files are added or removed. The FileWatcher class in mcp-server.ts implements handleFileEvent() to detect changes, re-analyze affected files, and update the bidirectional dependency map incrementally. This enables the MCP server to maintain a current view of the codebase without requiring manual refresh or full re-scans.","intents":["keep AI assistants' understanding of codebase structure synchronized with live development","detect when new files are added and automatically include them in dependency analysis","identify when files are deleted and remove them from the dependency graph","enable real-time feedback on how code changes affect architectural importance scores"],"best_for":["long-running AI development sessions where codebase is actively being modified","IDE integrations that need to reflect current project state","continuous analysis workflows where stale data is problematic","development environments with frequent file operations"],"limitations":["fs.watch() is platform-dependent and may miss rapid successive changes on some systems","no debouncing by default; high-frequency file operations can trigger excessive re-analysis","does not detect changes to import statements within existing files (only file add/delete)","performance degrades with very large codebases (>50k files) due to re-analysis overhead"],"requires":["Node.js fs.watch() support (all modern versions)","filesystem permissions to watch target directories","active MCP server process"],"input_types":["filesystem events (add, delete, modify)","file paths","file metadata"],"output_types":["updated dependency graph","modified file tree state","change notifications (optional)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-filescopemcp__cap_5","uri":"capability://tool.use.integration.mcp.protocol.server.implementation.with.tool.based.api.exposure","name":"mcp protocol server implementation with tool-based api exposure","description":"Implements the Model Context Protocol (MCP) specification as a TypeScript server that exposes file analysis capabilities as callable tools. The mcp-server.ts file (lines 297-369, 571-575, 578-1584) defines the MCP server initialization, tool registration, and request/response handling. Tools are registered with JSON schemas describing parameters and return types, enabling AI clients to discover and invoke capabilities like 'analyze_codebase', 'get_file_importance', 'generate_diagram' through standard MCP protocol messages over stdio transport.","intents":["integrate FileScopeMCP with AI development tools (Claude, Devin, etc.) that support MCP","expose codebase analysis as discoverable, schema-validated tools for AI assistants","enable AI clients to request specific analyses without direct filesystem access","provide a standardized interface for tool composition and chaining"],"best_for":["AI development environments that support MCP (Claude, Devin, custom agents)","teams building AI-assisted development workflows","developers integrating FileScopeMCP into larger MCP ecosystems","scenarios where AI assistants need structured access to codebase analysis"],"limitations":["MCP protocol overhead adds latency (~50-200ms per tool call) compared to direct library usage","stdio transport is synchronous; concurrent requests are serialized","tool schemas must be manually maintained in sync with implementation changes","no built-in authentication or authorization; relies on client-side access control"],"requires":["Node.js 16+","MCP-compatible client (Claude, Devin, or custom implementation)","stdio transport (default; no HTTP/WebSocket support)"],"input_types":["MCP tool call requests (JSON)","tool parameters (schema-validated)","codebase paths"],"output_types":["MCP tool responses (JSON)","structured analysis results","error messages with diagnostic info"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-filescopemcp__cap_6","uri":"capability://memory.knowledge.file.metadata.and.summary.storage.with.human.ai.annotation.support","name":"file metadata and summary storage with human-ai annotation support","description":"Stores and retrieves file-level metadata including human-written or AI-generated summaries, descriptions, and custom annotations. The updateFileNode() and getFileNode() functions in storage-utils.ts manage a file node structure that includes not just dependency information but also descriptive text, tags, and custom properties. This enables AI assistants to augment their understanding of files with human-provided context or to store AI-generated summaries for future reference.","intents":["attach human-written descriptions to files for AI assistants to reference during analysis","store AI-generated file summaries to avoid re-analyzing the same files repeatedly","tag files with custom metadata (e.g., 'deprecated', 'performance-critical', 'untested')","build a knowledge base of file purposes and relationships beyond what code analysis can infer"],"best_for":["teams that want to enrich AI understanding with human domain knowledge","projects where file purposes are non-obvious from code alone","workflows where AI-generated summaries should be cached and reused","collaborative scenarios where team members annotate files for shared understanding"],"limitations":["no versioning or change tracking for annotations; overwrites previous values","no conflict resolution for concurrent edits to the same file's metadata","annotations are stored in the same JSON file as analysis results; no separate audit trail","no built-in validation of annotation content or format"],"requires":["filesystem write access to configuration directory","file node structure (created by dependency analysis)","JSON serialization support"],"input_types":["file paths","summary text (string)","custom metadata (key-value pairs)","tags (string array)"],"output_types":["updated file node object","serialized metadata (JSON)","retrieval results"],"categories":["memory-knowledge","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-filescopemcp__cap_7","uri":"capability://data.processing.analysis.language.specific.import.pattern.matching.and.path.resolution","name":"language-specific import pattern matching and path resolution","description":"Implements language-specific regex patterns to extract import statements from source code and resolve them to actual file paths. For each supported language (Python, Lua, C, C++, Rust, Zig), the system defines IMPORT_PATTERNS that match language-specific import syntax (e.g., 'import X' for Lua, 'from X import Y' for Python, '#include' for C/C++). The resolveImportPath() function in file-utils.ts converts extracted import names to filesystem paths, handling relative imports, package names, and file extensions.","intents":["extract dependency information from source code without parsing ASTs","support multiple programming languages with a single pattern-matching framework","resolve import statements to actual file paths for accurate dependency tracking","enable lightweight analysis that doesn't require language-specific parser libraries"],"best_for":["polyglot projects with multiple programming languages","resource-constrained environments where AST parsing overhead is prohibitive","quick codebase scans where regex-based analysis is sufficient","projects that need to support emerging or less common languages"],"limitations":["regex patterns cannot handle complex import syntax (e.g., dynamic requires, conditional imports)","does not resolve package manager dependencies (npm, pip, cargo, etc.)","relative import resolution may fail with path aliases, monorepo structures, or non-standard layouts","no support for language features like namespace aliasing or re-exports","patterns must be manually maintained for each language; no automatic pattern generation"],"requires":["source code files in supported languages","configured IMPORT_PATTERNS for target languages","filesystem access for path resolution"],"input_types":["source code text","file paths","language identifiers"],"output_types":["extracted import statements (array)","resolved file paths","dependency edges (source -> target)"],"categories":["data-processing-analysis","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-filescopemcp__cap_8","uri":"capability://data.processing.analysis.codebase.scanning.and.file.tree.construction.from.filesystem","name":"codebase scanning and file tree construction from filesystem","description":"Recursively scans a filesystem directory to discover all source files and build an initial file tree structure. The file analysis processing pipeline (src/mcp-server.ts lines 98-178) walks the directory tree, filters files by extension, and creates file nodes with metadata (path, name, extension, size). This foundational capability enables all downstream analysis by establishing which files exist and their basic properties before dependency analysis begins.","intents":["discover all source files in a codebase for analysis","build a baseline file tree structure that dependency analysis can augment","filter files by type (e.g., exclude test files, build artifacts, node_modules)","establish file metadata (paths, extensions) needed for importance scoring"],"best_for":["initial codebase analysis workflows","projects with standard directory structures","scenarios where file discovery is the first step before deeper analysis"],"limitations":["does not follow symlinks by default; may miss linked files or directories","performance degrades with very large codebases (>100k files) due to filesystem I/O","no built-in filtering for common artifacts (node_modules, .git, build directories) — requires configuration","does not detect files that are generated at runtime or not yet written to disk"],"requires":["filesystem read access to target directory","Node.js fs module","configured file extension filters (optional)"],"input_types":["directory paths","file extension filters (optional)"],"output_types":["file tree structure (nodes with metadata)","file list (paths, extensions, sizes)","directory hierarchy"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-filescopemcp__cap_9","uri":"capability://automation.workflow.configuration.driven.analysis.with.project.specific.settings","name":"configuration-driven analysis with project-specific settings","description":"Supports project-specific configuration files that control analysis behavior including file filters, import patterns, importance weighting, and output options. The createFileTreeConfig() function in storage-utils.ts and Application Configuration section enable users to define which files to analyze, how to weight importance factors, and which languages to support. Configuration is stored in JSON format and can be version-controlled, enabling teams to maintain consistent analysis across environments.","intents":["customize analysis behavior for project-specific conventions and structures","exclude build artifacts, dependencies, and generated files from analysis","adjust importance weighting to reflect project-specific architectural priorities","enable reproducible analysis across team members and CI/CD environments"],"best_for":["teams with non-standard project structures or naming conventions","projects that want to exclude specific directories or file types from analysis","workflows where analysis configuration should be version-controlled","CI/CD pipelines that need consistent, reproducible analysis"],"limitations":["configuration changes require server restart; no hot-reload support","no validation of configuration values; invalid settings may cause silent failures","configuration format is JSON; no schema validation or IDE support","no built-in configuration inheritance or composition for monorepos"],"requires":["JSON configuration file","filesystem write access to configuration directory","Node.js fs module for reading config"],"input_types":["JSON configuration files","file path filters (glob patterns or regex)","weighting parameters (numeric)","language settings"],"output_types":["parsed configuration object","applied settings (for verification)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":30,"verified":false,"data_access_risk":"high","permissions":["Node.js 16+","source files in supported languages (Python, Lua, C, C++, Rust, Zig)","filesystem access to entire codebase","completed dependency graph (buildDependentMap must run first)","file metadata (extension, path, name)","configurable weighting parameters (optional)","completed dependency graph","Mermaid.js library (included in HTML output)","modern browser for interactive rendering","filesystem write access to configuration directory"],"failure_modes":["regex-based pattern matching cannot resolve dynamic imports or conditional requires","does not track transitive dependencies through package managers (npm, pip, cargo)","relative import resolution may fail with complex path aliasing or monorepo structures","no support for circular dependency detection or cycle breaking strategies","heuristic-based scoring may not reflect actual architectural importance in unconventional projects","naming pattern matching is language and convention-specific (assumes common naming like main.py, index.ts)","does not account for cyclomatic complexity, test coverage, or runtime criticality","scores are relative within a single codebase and not comparable across projects","Mermaid rendering performance degrades with >100 nodes; large codebases require aggressive filtering","no support for hierarchical/layered layouts (only flowchart layouts available in Mermaid)","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.45,"ecosystem":0.39999999999999997,"match_graph":0.25,"freshness":0.52,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-06-17T09:51:03.039Z","last_scraped_at":"2026-05-03T14:00:15.503Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=filescopemcp","compare_url":"https://unfragile.ai/compare?artifact=filescopemcp"}},"signature":"znbjW/vJ2XOqnz4kmOA5c418qc21Um0Nk4Cd0+VI16Fd+t1Hz92LPlA/4/Je8JRT2F8nwiy55cFcZVy7hvYuDw==","signedAt":"2026-06-22T03:55:47.387Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/filescopemcp","artifact":"https://unfragile.ai/filescopemcp","verify":"https://unfragile.ai/api/v1/verify?slug=filescopemcp","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}