"Building and Deploying a React Application with Docker and a Postgres Backend" matching MCP servers:

Manages Docker containers, images, and Compose stacks on a remote host over SSH, with file sync and deploy orchestration.

A local, read-only MCP server that analyzes Python backend projects by providing tools to scan, map, and selectively read files, reducing token usage for AI clients.

Exposes mobile system capabilities as MCP tools so AI agents can access clipboard, location, calendar, contacts, files, storage, networking, and device connectivity through standard transports. It applies permission policies and native adapters for integration into mobile apps without bundling an AI agent or host bridge.

Enables ChatGPT web to read local files, search code, run shell commands, and drive a local Codex CLI via an official MCP connector, with human approval for risky commands and full audit logging.

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

Enables secure execution of shell commands and file operations within isolated Docker containers. Provides process management, interactive input handling, and comprehensive file system operations for containerized development environments.

A read-only MCP connector that lets ChatGPT on the web plan tasks and independently review real Git diffs for local coding agents across many registered projects through one shared OAuth-protected hub connection, with no API key required. It exposes only file reads — never edits or shell tools — so the coding agent keeps full ownership of execution while the web subscription handles the reasoning and review.

Enables executing Python code, managing environments and packages, and performing file operations within Docker containers.

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.

locidx

Provides a sandboxed filesystem API for AI agents, enabling natural-language file read, write, append, delete, move, list, create, and metadata operations through MCP tools.

Provides a secure workspace for AI-driven file management and Python script execution designed to run on Vercel. It enables tools for full file operations and code execution within a sandboxed environment.

Provides secure filesystem access for AI models through the Model Context Protocol with strict path validation, file operations, directory management, and system command execution within predefined directories.

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.

An MCP server that converts Markdown files containing Mermaid diagrams into PDF documents by rendering diagrams as SVG images. It provides a specialized tool to automate document conversion while ensuring all visual charts are correctly embedded in the final output.

Provides a read-only MCP bridge that lets Claude Web inspect workspace files, git state, and recorded test results while Codex remains the sole executor of changes.

A local MCP bridge that lets ChatGPT chat mode operate the user's own computer, running project, file, and shell tasks through a local executor and returning progress and results to the conversation. It also coordinates Codex sessions (persistent or one-off) and other agent CLIs as sub-agents.

An HTTP MCP server that indexes large documents into exact-line-numbered sections, enabling AI models to locate, read, summarize, and edit parts of a document without ingesting the whole file.

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 self-hosted MCP server that enables AI coding agents to read, edit, search, and run code in local projects with human review loops and policy controls.

Enables interaction with the WhkerDB shared PDF editor to manage collaborative rooms, file structures, and real-time annotations. It allows users to upload PDFs and images, manage note trees, and sync data across platforms through natural language.

Enables digital forensics investigation by exposing SANS SIFT tools (The Sleuth Kit, Volatility 3, Plaso, etc.) as callable MCP tools, running in a self-contained Docker container with safe, allowlisted commands.

Hardened C# Model Context Protocol (MCP) server for MS SQL Server and PostgreSQL databases featuring read-only transaction safeguards, command security filters, and path traversal protection.

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 Claude to read and analyze PDF documents with automatic OCR processing for scanned files. Features intelligent text extraction, caching for performance, and secure file access with search capabilities.

Enables agents to compress JPEG, PNG, and WebP images to a target byte size, split PDFs by page or ranges, and remove image metadata while processing local files without sending file bytes over the network.

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.

Enables offline inspection, structural comparison, and transactional staged editing of local copies of Omron Sysmac Studio (.smc2) projects, covering variables, POU, tasks, I/O bindings, and selected DataTypes with preview, validation, rollback, and export. Optionally integrates with a locally installed IDE on Windows for open-copy, rebuild, and guarded export operations without ever connecting to a PLC.

Memory bank with Server as SSH support for central knowledge base

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.

Lightweight object storage with S3, HTTP, and MCP interfaces, enabling AI agents to store and retrieve files via structured tool definitions.

Enables secure filesystem access with privacy controls using .mcpignore files to block MCP clients from reading or writing sensitive files and directories while allowing directory browsing and search.

Enables AI models to access external services including weather data, file system operations, and SQLite database interactions through a standardized JSON-RPC interface. Features production-ready architecture with security, rate limiting, and comprehensive error handling.

A Model Context Protocol server providing file search and question tools for AI models. Enables keyword search in files with line numbers and integration with external chat services.

Enables Codex to read locally stored profile and material data, inspect and fill authorized Chrome web application forms, and attach selected files through a local MCP bridge.

Exposes a secure OAuth2 + SSE Model Context Protocol endpoint that lets Gemini Web read a local project's files, directory trees, search results, git status/diffs, and workspace info on a read-only basis. It also pairs the browser-side automation with a local bridge daemon so prompts and answers flow both ways between Gemini Web and Google Antigravity.

Exposes the agent's sandboxed file tool over stdio so any MCP client can retrieve the contents of a UTF-8 text file inside the working directory, with failures returned as recoverable error strings instead of exceptions. It lets the same ReAct loop swap in-process dispatch for an MCP hop without changing tool signatures.

Enables AI agents to interact with both frontend and backend projects by providing file system access and context through the MCP protocol, facilitating full-stack development assistance.

Provides tools for file system operations and text generation using OpenAI-compatible models via the Model Context Protocol, supporting both stdio and HTTP transports.

MCP server that allows AI agents to read, search, summarize, and answer questions about local PDF, DOCX, XLSX, and TXT files through five tools.