"Overview and Information on PG Vector" matching MCP servers:

Connects ChatGPT to local files, terminals, and the desktop through MCP with Chrome integration, letting users read and edit project files, run commands, and follow tool results as they arrive. It also adds durable multi-agent workers, Goal/Loop task tracking, mid-task corrections, and Compact & Resume for carrying session and worker history into a fresh chat.

Enables ChatGPT to access approved local Windows folders, run commands, control the desktop, and manage session history through a permission-bounded MCP server.

一个基于FastMCP协议的文件向量化服务，支持自动目录监控、多格式文件处理和高效向量搜索，帮助构建个人或团队知识库。

A read-only remote MCP server that searches and reads files from a personal Microsoft OneDrive folder via Cloudflare Workers, enabling live access without a local workstation or tunnel.

Enables ChatGPT's web interface to operate a real Mac by executing shell commands and reading or writing files over a reverse SSH tunnel, without installing a client or consuming API quota.

Provides tools to monitor host system health including CPU load, disk usage, and network status while enabling file system management tasks like searching and moving files. It includes built-in safety guards to prevent operations on critical system directories.

A very simple vector store that provides capability to watch a list of directories, and automatically index all the markdown, html and text files in the directory to a vector store to enhance context.

Gives ChatGPT hands-on control of a local machine: reading, patching and executing code in approved project folders, running real interactive processes, managing plans and worker sub-chats, and driving the browser or desktop through user-granted permissions. Every capability is a switch inside an approved-folder sandbox, so nothing runs that the user did not explicitly enable.

An MCP server that gives LLM clients access to a SQL Server database and the local filesystem, including file operations and image handling.

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 document conversion between PDF, DOCX, and Markdown formats to facilitate reading and editing complex files in AI tools like Claude Desktop or Cursor. It utilizes marker-pdf and pandoc to provide structured text versions of documents, helping to manage context and support unsupported file types.

A Model Context Protocol (MCP) server for ZeroDrive file management. It enables AI assistants like Claude to interact with ZeroDrive cloud storage through a standardized interface.

Enables AI clients to securely execute remote commands and transfer files over SSH through standardized MCP tools, with multi-host management, flexible authentication, and an admin console.

TheWeave is a markdown-native memory architecture for Claude and any MCP-aware agent. Your agent's memory lives as plain .md files you own: a 5-verb MCP core over the vault, query-driven PageRank retrieval, bi-temporal facts (valid_from / valid_until), and a persona-as-vault model. No database and no embeddings server. The files are the memory, inspectable in your editor and versionable in git.

Combines KC Chat Panel session interaction with AgentDock computer control tools, enabling Cursor Cloud Agent to chat and operate the local machine via AgentDock.

A local MCP server that gives Claude in the browser tools to interact with a Fedora machine, including file operations, system diagnostics, build tasks, and root actions via Polkit.

Enables AI agents and users to manage workspace files, monitor system metrics, take persistent notes, and retrieve weather data via MCP tools and resources.

Enables browsing and preparing study materials from local documents (PDF, Markdown, text, Word) via tools for overview, search, reading, chunking, and quiz generation.

locidx

Converts vector PDF circuit schematics into evidence-preserving SchematicIR JSON with tools to inspect, convert, and validate schematic PDFs.

Provides advanced document search and processing capabilities through vector stores, including PDF processing, semantic search, web search integration, and file operations. Enables users to create searchable document collections and retrieve relevant information using natural language queries.

This server is to precess files for LNR.

Lets MCP clients search, read, create, append, replace, move, and batch-update local Markdown notes safely, with conflict detection via SHA-256 and optional managed update blocks, without requiring a vector database.

Offline AI-powered local file search MCP server for Windows. Searches inside document contents (Word, Excel, PDF, PowerPoint, HWP) using BM25 + dense vector hybrid search. 100% local, no cloud, no login, no telemetry.

A modular framework for building and running multiple MCP servers with file operations, system information, and extensible tool/prompt/resource support.

Provides AI assistants with persistent memory through local ChromaDB vector storage, featuring automated file ingestion and batch processing for over 70 file types. It enables advanced vector search, EXIF metadata extraction for photos, and duplicate file detection across local directories.

Enables AI clients to securely operate servers over SSH, including remote command execution and file transfer with a built-in web admin console and Windows tray app.

Enables local-first, offline hybrid retrieval from Markdown notes, MinerU papers, and code via MCP, with BM25 keyword and local vector search, outline-aware chunking, PDF twin-binding, and incremental file watching.

A TypeScript MCP server example providing basic developer tools: hello world greeting, arithmetic calculator, and file information retrieval.