"Information or resources about fast-filesystem-mcp" matching MCP servers:

fast-pyairbyte lets you create a data pipeline in code ,from any Airbyte connector, with a single prompt.

A Model Context Protocol server that provides AI agents with secure access to local filesystem operations, enabling reading, writing, and managing files through a standardized interface.

Enables AI-powered task management with Google Gemini integration, providing CRUD operations, task analytics, CSV export, and natural language interaction for comprehensive project management.

Enables agents to start and monitor hybrid browser automation tasks, handle approval requests, and approve or cancel them through MCP.

Enables document-grounded question answering, arithmetic calculations, live weather lookups, and persistent chat history through a ReAct agent with hybrid retrieval.

Enables natural language interaction with FastAPI applications through Google's Gemini AI using MCP tools. Provides CRUD operations for user management and application health monitoring through conversational prompts.

Enables agents to get fast, calibrated probabilistic answers from Jev (Typesafe AI) to yes/no, scale, or choice questions about provided material, without using a generative model.

A filesystem-based MCP server for AI coding agents to coordinate work across git worktrees by claiming files, checking for conflicts, and logging progress without affecting the repository's git history.

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

An improved implementation of persistent memory using a local knowledge graph with a customizable --memory-path. This lets Claude remember information about the user across chats.

Enables AI agents to capture and analyze screenshots of macOS applications, windows, or the entire screen using local (Ollama) or cloud-based AI vision models, with non-intrusive, fast screen capture via Apple's ScreenCaptureKit.

Enables local, event-driven messaging between multiple AI coding-agent sessions on the same machine using only Node.js and the filesystem, allowing them to hand off tasks, exchange replies, and broadcast announcements without external infrastructure.

An MCP server that enables AI agents to pause and request human approval or information via Slack, Telegram, or macOS dialogs before proceeding with actions.

Local inter-agent messaging for AI coding agents via filesystem relay.

Enables AI assistants to perform ultra-fast, calibrated decision tasks such as boolean evaluation, category selection, scoring, and batch decisions through TypeSafe AI's Jev model.

Provides agents with fast, typed, calibrated decision tools for classification, scoring, yes/no checks, and gating risky tool calls.

Description: Persistent memory for AI agents with rollback, audit trails, semantic search, and knowledge graph. Zero-config local SQLite or cloud API. 23 tools, 6 resources, 3 prompts.

MCP server that lets any agent or MCP host delegate tasks to the Cursor CLI agent for fast, headless execution. Supports task delegation, project discovery, file analysis, and follow-up sessions.

A public, long-lived contact and cooperation point for autonomous AI agents. Agents describe missing capabilities or resources, request help from a human operator, and leave persistent messages on a tamper-evident message board.

Turns Mac apps into MCP servers that expose an app's actions as typed, deterministic tools, so agents can drive GUI applications through the accessibility API without screenshots or pixel coordinates. Each call replays a recorded action with no model on the serving path, making interactions fast, cheap, and repeatable.