"Gcore" matching MCP servers:

It enables MCP integrations to safely access a chosen project folder with path-boundary enforcement, read and search files, and perform confirmed writes over a bounded local Unix-socket transport.

Remote execution layer for agentic systems exposing 64 production tools via MCP for file, network, system, text, git, crypto, and monitoring operations.

An MCP filesystem telemetry server that watches directories and records every file change with SHA-256 hashes, enabling verification of edits through tools like recent_changes and query_events, with multi-project support and idle suspension.

Provides coding agents with file inventory, ranked search, location-aware reading, code packing, and note writing over the workspace folder through MCP, without involving a model.

Local-first operator MCP server: recall across your own sessions, chats and files, an encrypted vault, SSH to your own hosts, and gated shell, browser and device tools. 130 tools over stdio or HTTP; everything runs on your machine — no hosted service, no account, no API key.

A Model Context Protocol server that enables Claude Desktop and other MCP clients to interact with TrueNAS Core systems through the TrueNAS API, supporting user management, storage operations, sharing, and snapshot creation.

Installs an agent on Linux hosts to allow shell commands, file edits, and service management through Claude.ai or ChatGPT via a secure outbound WebSocket connection.

Lets AI assistants read a student's Canvas LMS/Moodle courses, deadlines, announcements, grades and course files using their normal browser login instead of an access token. It is read-only and keeps all session data and downloads on the user's own machine.

Enables local file editing, terminal commands, and durable session management for ChatGPT.

Exposes local file system operations to AI assistants via Streamable HTTP with security features like auth, path whitelisting, and audit logging.

Connects Gemini on the web to a user's own Windows PC, letting it read files, run commands, write to disk, and invoke local skills and other MCP plugins. It reaches the machine through a stable self-hosted Tailscale Funnel URL, with tools enabled and approved by the user.

Enables ChatGPT to work on a local project by reading and editing files, running shell commands, keeping terminals and desktop sessions open, and splitting work across durable workers whose context persists between tasks. Long-running work can be steered mid-flight, tracked with Goal, and carried into fresh chats via Compact & Resume.

Lets ChatGPT work directly on a local project by reading and editing files, running shell commands and tests, keeping terminals open, and using the user's desktop, all paired with an approved workspace folder. It also splits independent jobs across persistent workers that retain context, while riding the user's existing ChatGPT plan rather than Codex quota.

Enables file system operations, web scraping, and AI-powered search through MCP tools for use by LLM agents.