"Hugging: Exploration and Resources" matching MCP servers:

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Provides AI coding agents with five intelligence layers (dependency graph, git history, documentation, architectural decisions, code health) via nine MCP tools, enabling deep codebase understanding and reducing exploration cost.

An MCP server that wraps Microsoft's FastContext as a read-only repository exploration subagent, enabling coding agents to delegate broad code searches and receive compact file:line citations.

Enables efficient codebase exploration with tools to list exports, get file outlines, read targeted regions, and find references without loading entire files.

Provides coding agents with a mental map of codebases via progressive disclosure, enabling efficient exploration of project structure and entity relationships.

Enables token-efficient structural code exploration using tree-sitter AST parsing, with tools for symbol search, outlines, source unfolding, call graphs, and related-file discovery.

A semantic code context server that connects your local repository to AI assistants via the Model Context Protocol, enabling dynamic codebase exploration without copy-pasting.

Enables fast code analysis and navigation through hybrid semantic search, graph-based relationship tracking, and structure exploration across multiple programming languages with optimized indexing for large codebases.

Combines semantic search with AST-based code exploration for AI agents, enabling natural language code search, file structure browsing, symbol inspection, and dependency analysis through the Model Context Protocol.

Analyzes source code structure across multiple languages using tree-sitter, extracting classes, functions, methods, and metadata with precise line numbers for efficient codebase exploration and AI-assisted development.

Enables exploration and decompilation of Minecraft source code, allowing users to list versions, search classes, and decompile .class files on-the-fly.

Exposes CodeGraph capabilities for multiple local repositories to MCP-compatible AI coding assistants, enabling multi-repo code exploration and cross-repo symbol tracing.

Provides various utilities including timezone-aware time queries, basic calculator operations, multilingual greetings, code review prompts, and AI image generation through Hugging Face API.

Read-only repository context explorer for coding agents. Provides repository exploration tools via CLI or MCP adapter.

Provides deterministic Python codebase symbol exploration using AST parsing, with tools for definition lookup, signatures, references, call chains, and class hierarchy queries.

AST-aware TypeScript/JavaScript codebase exploration for AI agents, providing high-precision symbol resolution, reference finding, and structural analysis via MCP tools.

Enables AI agents to assess AI-readiness and improve AI leverage through analysis tools, resources, and prompts for project scanning and remediation.

Gives Claude Code, Cursor and other agents structural awareness of a PyTorch model: layers, params, FLOPs, blast radius, the design linter, a full readiness/cost/deployment verdict, and a ranker for which of k candidate designs to train. Reads a .py, a .neurarch.json, 81 bundled reference architectures, or a Hugging Face repo. Offline, no API key.

An MCP server that provides ultra-efficient code exploration through AST analysis, reducing LLM token usage by up to 95% while enabling instant call graph generation and dependency analysis for massive codebases.