"An overview or information about file systems" matching MCP servers:

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 AI agents to debug and repair historical Solaris/SPARC systems by providing an out-of-band control plane with guest DTrace, QEMU monitor access, SPARC-aware GDB, host eBPF/perf tracing, and an immutable evidence ledger for cross-layer hypothesis testing.

An agentic file-system assistant that lets users read, write, list, and search local files through natural language, using a LangChain agent with an Ollama LLM backed by a FastMCP server.

A Model Context Protocol (MCP) server that enables AI assistants to perform comprehensive file operations including finding, reading, writing, editing, searching, moving, and copying files with security validations.

This MCP server enables AI agents to manage artifacts across sessions by providing tools for searching, retrieving, and registering entries in a persistent ledger, ensuring consistency and traceability of agent outputs.

A local server that enables Google's Gemini AI to safely read, write, and list files within a controlled sandbox folder on your computer through natural language chat interactions.

Turnkey on-premise private Agentic AI on NVIDIA DGX. Query specs, model CapEx ROI & join Partner Program.

Enables AI agents to interactively explore PDDL planning problems by exposing a PDDL engine as MCP tools for initialization, action execution, state inspection, and goal checking.

Enables the creation and execution of task-specific AI sub-agents defined in markdown across any MCP-compatible tool like Cursor or Claude Desktop. It integrates with execution engines such as Claude Code, Cursor CLI, and Gemini CLI to provide portable and reusable specialized agent workflows.

MCP server that keeps language server sessions warm and routes multiple languages through one process. Agents get persistent cross-file awareness, speculative execution (simulate edits before writing to disk), and 20 skills that encode correct multi-step operations like safe rename, blast-radius analysis, and end-to-end refactoring. Single Go binary, no runtime dependencies.

Provides human-like memory dynamics for AI assistants where memories naturally fade over time unless reinforced through use, mimicking the Ebbinghaus forgetting curve. Enables automatic saving, searching, and management of contextual information with temporal decay algorithms.

Runtime decision firewall for AI agents that exposes the CSC engine as an MCP server, allowing agents to consult before executing risky actions.

Gates agent tool execution with human approval, audit trails, and replay-resistant permits, enabling safe use of tools in agent loops.

Governance primitives for autonomous agents. Verify actions against policy, record signed provenance, and bind intents cryptographically. Free tier available.

This MCP server enables an AI agent to control a Windows PC through human-like interactions such as screen capture, OCR, mouse, keyboard, and navigation, without using shortcut APIs.

A minimal MCP server that lets AI agents pause for a specified duration before resuming their workflow. Useful for polling patterns like waiting for PR approval or file creation.

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.

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 coding agents to load and route reusable, file-defined thinking routines as checklists or staged procedures, injecting the relevant chains into prompts when a task matches.

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.