"A guide to file operations" matching MCP servers:

前端ai主导的全流程，自动化的预开发；旨在解决前端开发在联调前期的各种繁琐工作

Enables AI agents to control a Playwright-driven browser through natural-language instructions, including page interaction and live browser task execution.

Listens for Slack @mentions and publishes them as real-time events to the KĀDI event bus, enabling event-driven architectures with low latency.

Comprehensive quest orchestration system with KĀDI broker integration, multi-channel approval workflow, and Git-backed data storage.

基于MCP架构的微信公众号文章爬虫系统，支持AI智能体通过Selenium自动抓取微信公众号文章内容和图片，实现文章内容的智能分析。

Enables separate desktop IDE agent hosts to hand off and review code tasks through a shared, contract-driven MCP bus with deterministic state transitions, file SHA-256 verification, and schema-validated outputs.

Enables real-time user intervention for MCP agents through a web UI, allowing users to review context and provide feedback when AI agents drift from intent, keeping them on track.

Discover and connect your agents with other agents via A2A protocol. Share resources for free or fee.

Connects Claude Code instances to a clawborrator hub via WebSocket, enabling cross-session communication, file exchange, and agent dispatch.

Enables agents to accomplish multi-step work by writing a single sandboxed JavaScript program that drives shell, filesystem, HTTP, and every tool of any configured MCP server, returning only a small summary instead of raw JSON. This collapses dozens of advertised tool schemas into one tool, cutting per-request context by roughly 26× while keeping disabled upstream servers reachable.

Enables peer-to-peer asynchronous conversation between Claude.ai and Claude Code instances via a shared file-based notebook, allowing them to leave messages, start threads, and organize by project.

An MCP server that enables a supervising OpenAI Codex agent to delegate bounded implementation tasks to isolated worker threads with enforced file scopes and verification, optionally running in parallel git worktrees.

Enables terminal AI coding assistants to interact with web AI chat services through browser automation, supporting multiple platforms like Doubao and ChatGPT.

Enables collaboration across Claude, GPT, and Gemini through a unified MCP interface, with configurable execution policies for synthesizing or directly delivering worker outputs.

Enables a host AI agent to trigger a multi-agent debate, running N-rounds where agents critique each other's answers, then synthesizes a consensus recommendation with ranked options.

Local-first MCP proxy with BM25 tool discovery, quarantine security, Docker isolation, OAuth support, activity logging, and web UI. Routes multiple upstream MCP servers through a single endpoint.

A Model Context Protocol (MCP) server that provides intelligent search capabilities for discovering relevant Claude Agent Skills using vector embeddings and semantic similarity. This server implements the same progressive disclosure architecture that Anthropic describes in their Agent Skills enginee

Lets separate coding-agent sessions coordinate through a shared, role-addressed mailbox instead of a human relaying every message, over a single local SQLite file or a hosted server with many isolated channels. Messages can be sent as tracked obligations that stay open until one side resolves and the other confirms, alongside threads, full-text search, work statuses, and an append-only versioned pin system where protected changes require recorded agreement from every declared role.

Enables AI agents to drive a Chromium browser through MCP, with persistent sessions, compact page snapshots, guarded actions, batched operations, and explicit result verification.

Enables multiple AI agents to coordinate work on the same codebase by providing real-time file locking, commit approval, and agent awareness through a lightweight WebSocket-based MCP server.

A lightweight, zero-dependency Python MCP server that exposes a single do_everything tool. Any AI agent that supports MCP can use it to offload all language-model work to a local OpenAI-compatible endpoint, reducing cost on the agent's primary LLM.

MCP server that lets you drive Claude Code sessions hands-free by voice from any MCP client, enabling remote models to send prompts, monitor progress, and get results read back.

Enables AI coding agents from any vendor to resume a task from the exact stopping point without model calls, re-reading old sessions, or re-exploring the code, by merging host hooks, agent checkpoints, and Git deltas into one compact brief. It also guards credits outside the model with a prompt clarity gate, a loop guard, and configurable token profiles.

MCP server for inter-agent mailbox communication using file-based mailboxes in .claude directories.

Enables MCP clients to submit tasks to a local file-backed queue and later read or cancel them by ID, with results produced by a separately run worker.

Enables AI agents to interact with issue, comment, document, and agent workflows through a simplified HTTP API, returning compact Markdown or file-based snapshots.

Bridges Claude to a local OpenClaw gateway on Android via Termux, enabling agent dispatch, observation, control, file operations, and system commands through 10 consolidated tools optimized for the God Orchestrator pattern.

Just to be clear about the final JSON: the MCP server is named herdr-inbox, and it enables Claude Code agents in herdr to ask questions asynchronously without stalling, with all open questions answered from one popup and answers routed back to the asking agent.

A comprehensive server that enables AI agents to interact with multiple EVM-compatible blockchain networks through a unified interface, supporting ENS resolution, token operations, and smart contract interactions.

Enables Claude Code and other MCP clients to obtain fast, low-latency snap decisions — tool choice, option selection, and abstention when confidence is low — from a pluggable local decision engine such as Laya, Von, an Ollama chat model, or a custom provider. Engines can be swapped without changing the stable tools the client sees, with validation, per-attempt timeouts, confidence thresholds, and fallback chains handled by the server.