"Files" matching MCP servers:

Enables agents to quickly find and edit code in a codebase with surgical precision. Find symbols, edit them everywhere with tools for reading code blocks, searching/replacing text, and making precise line-based modifications.

Reduces Claude's context window costs by automatically summarizing inactive files to their public interfaces using AST parsing, keeping only the full contents of the currently active file.

Enables intelligent handling of large files through smart chunking, search with regex support, line navigation, and streaming capabilities without loading entire files into memory.

Enables read-only auditing of repositories by scanning actual files, flagging risky code, secrets, and untrusted platform configs, and generating Chinese-language reports for human decision-making.

Provides LLM-optimized filesystem access with intelligent file pagination for large files, lightning-fast ripgrep-powered code search with regex support, and security sandboxing to safely explore and search codebases.

A TypeScript tool that ranks files in your codebase by importance, tracks dependencies, and provides file summaries to help understand code structure through Cursor's Model Context Protocol.

Enables AI coding agents to index local codebases and search them by natural-language intent, find related files through imports and semantic similarity, and check indexing status. All processing runs locally via MCP tools.

Enables MCP clients to read only explicitly allowlisted Linux project files and selected Codex conversation turns. It supports listing projects and files, reading UTF-8 files, bounded text search, and paged reading of authorized conversations.

An MCP server that provides a flexible lens into directory structures and files, enabling LLM clients to efficiently navigate and understand codebases with minimal noise. It offers secure, gitignore-aware file access with tools like directory listing, file reading, and grep-like search.

Enables precise file patching using SEARCH/REPLACE blocks, with mandatory directory sandboxing, automatic Python QA (Ruff/Black/MyPy), and git versioning for rollback.

Enables AI coding agents to extract structural C# contracts from files and build solution-wide dependency graphs, so they can navigate code and assess change impact without reading entire files.

Enables powerful code search across millions of public GitHub repositories using grep.app API, with capabilities to discover code examples, retrieve specific files, and batch fetch multiple files for learning from open source projects.

Provides LLM-optimized tools for advanced code analysis, repository complexity evaluation, and call graph generation. It enables users to visualize directory structures, detect code patterns, and build semantic context with significant token savings.

Enables Claude to list directories, read text files, and search code within a designated read-only project folder, while skipping common dependency folders and blocking sensitive files.

Enables Claude Web to securely inspect, search, and modify local project files through a sandboxed MCP server with atomic writes, path traversal protection, and sensitive file blocking.

MCP server that enables AI agents to search code, find files, and read files in a codebase at lightning speed using ripgrep.

Enables analysis of multi-file git workspaces to synthesize dependency diffs and refactor sequences.

An MCP server that lets coding agents read individual functions, classes and symbols from source files instead of loading whole files, cutting the tokens spent reading code by 85-95% on large files. It provides outlining, exact symbol reads, and project-wide symbol definition and reference lookups across many programming languages, running entirely locally with no index.

Enables read-only, workspace-bound inspection of repositories and log files, returning JSON reports with file counts, largest files, TODO/FIXME markers, and warning/error counts.

A production-ready MCP server enabling Claude and other LLMs to perform intelligent file operations with minimal token usage.