"How to update an MCP configuration file" matching MCP servers:

A tool that helps manage and synchronize MCP server configurations across different AI assistant clients (Cline, Roo Code, WindSurf, Claude), automating the process of retrieving, listing, adding, and removing server configurations from client configuration files.

Educational MCP server for basic file operations (read/write) via the Model Context Protocol.

Enables blazingly fast file and content searching in large codebases using ripgrep, with intelligent filtering, fuzzy finding, and directory tree visualization while respecting .gitignore and avoiding common bloat directories.

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 local file management through natural language interactions using the Gemini API, with tools for listing, reading, writing, deleting, and updating files.

Local-first filesystem MCP bridge with ripgrep search, atomic writes, multiple transports

Windows-first MCP server for deterministic file writes with atomic create, replace, and structured edit operations, preserving encoding and newline styles.

file operation

Enables AI models to perform file system operations (reading, creating, and listing files) on a local file system through a standardized Model Context Protocol interface.

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 moving artifacts from ChatGPT/Codex sandboxes to remote server storage via host-native file parameters, streaming large files without Base64 or model-context overhead.

An MCP server that gives AI agents file system access: read, write, search, hash, directory trees — 12 tools, zero dependencies, pure Python stdlib.

Enables AI agents and LLMs to perform comprehensive file system operations including CRUD, search, archive, hashing, and duplicate detection via the Model Context Protocol.

Provides comprehensive file system operations including reading, writing, searching, patching, code analysis, SSH transfers, and git operations, while aiming to reduce token usage in Claude Desktop.

A beginner MCP server that enables Claude to read local text, CSV, and Markdown files. Built as a learning project to understand how to connect AI to local file systems using the MCP protocol.

Search local file contents recursively with keyword matching

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Enables MCP clients to turn Make blueprints and Zapier exports into n8n workflow files, with a per-step report of what converted, what to review, and what must be finished by hand. Also lists zaps, explains how individual steps are handled, checks workflow files for broken links or placeholders, and can upload the result to an n8n instance as an inactive workflow.

MCP server that gives Claude Desktop and other desktop MCP clients filesystem powers—read, write, edit, and manage files like AI coding assistants.

Enables MCP clients to replace hardcoded text in source files with i18n resource keys, with support for previewing changes, profiles, resource sets, and machine translation.