"Generating a series of images using MCP from a sample image" matching MCP servers:

Provides agents with real Linux VMs to run commands, manage files, expose ports, and track costs, all through an ephemeral sandbox service.

A personal MCP bridge that lets ChatGPT drive a local Codex CLI, translating instructions into Codex app-server threads and returning compact summaries of what Codex did.

An educational implementation of a Model Context Protocol server that demonstrates how to build a functional MCP server integrating with various LLM clients.

Chain of Draft Server is a powerful AI-driven tool that helps developers make better decisions through systematic, iterative refinement of thoughts and designs. It integrates seamlessly with popular AI agents and provides a structured approach to reasoning, API design, architecture decisions, code r

A meta-server that aggregates multiple MCP servers into a single interface, reducing token usage by 98%+ through progressive tool discovery and direct code execution that processes data between tools without consuming context window space.

Enables agents to accomplish multi-step work by writing a single sandboxed JavaScript program that drives shell, filesystem, HTTP, and every tool of any configured MCP server, returning only a small summary instead of raw JSON. This collapses dozens of advertised tool schemas into one tool, cutting per-request context by roughly 26× while keeping disabled upstream servers reachable.

Gives AI coding agents typed, mode-gated access to a real WordPress site — content, media, users and settings via core REST, plus PHP execution, SQL queries, filesystem operations and Elementor page read/build/patch/snapshot via a companion bridge plugin. Destructive actions and code execution are guarded by feature flags, explicit confirm literals, dry runs, redaction and audit logging.

A sample MCP server implementation in TypeScript that demonstrates tool creation with a mock AI completion endpoint. Provides a basic example for developers to learn MCP server development patterns and tool registration.

An MCP server that uses Groq's API to expose raw chain-of-thought tokens from Qwen's qwq model, enabling LLMs to think step-by-step before responding.

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.

A simple MCP server implementation in TypeScript that communicates over stdio, allowing users to ask questions that end with 'yes or no' to trigger the MCP tool in Cursor.

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.

The AIGC solution based on the MCP protocol seamlessly transforms the ComfyUI workflow into an MCP Tool with zero code, enabling LLMS and ComfyUI to join forces and focus on image generation tasks. qwen-image, flux, and FLUx-KREA can be used for image generation.

Provides econometric modeling capabilities through R, enabling AI assistants to perform sophisticated analyses including linear regression, panel data models, instrumental variables regression, and diagnostic tests.

A lightweight TypeScript-based MCP server that demonstrates how to build custom MCP tools by implementing a simple addition calculator. Serves as a starting point for building MCP-compatible tools.

A sample implementation of Model Context Protocol server demonstrating core functionality with simple arithmetic tools and greeting resources.

A simple MCP server sample that provides a greeting tool which echoes back a personalized Japanese greeting message. Demonstrates basic MCP server implementation using FastMCP framework.

Composes arbitrary MCP tools using JavaScript, enabling discovery, composition, and execution of other MCP servers through a single 'exec' tool.

Enables running one Codex CLI task at a time in an isolated temporary folder, returning Codex's answer and a manifest of produced files for manual review and selective copying.

Enables agents to interact with the Logflare API by writing JavaScript functions that run in a Vercel Sandbox, using three tools: search, execute_read, and execute_write.