"A server or service related to @amap" 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 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 unified HTTP/HTTPS service that exposes Model Context Protocol (MCP) functionality over HTTP endpoints, allowing clients to list available tools and call them through a standardized API.

Enables an MCP-compatible AI client to author Blender Python, run Blender, import the resulting asset into Unity with materials and a prefab, place it in the active scene, verify the import, and revise the same asset using stable IDs.

A runtime-free MCP server that converts source code into AST🌲, regardless of language.

Connects ChatGPT to Roblox Studio's built-in MCP, enabling natural-language reading and writing of game data, including executing Luau code and modifying scripts and instances.

A service that processes natural language requests to perform mathematical calculations by integrating Claude AI with a calculator API through the Model-Context-Protocol architecture.

MCP-ORTools integrates Google's OR-Tools constraint programming solver with Large Language Models through the MCP, enabling AI models to: Submit and validate constraint models Set model parameters Solve constraint satisfaction and optimization problems Retrieve and analyze solution

A 3-tier relay service that serves MCP tools via WebSocket, including calculator, scripture lookup, and location-based recommendations.

An MCP server implementation that helps Claude remember and learn from programming errors by storing, retrieving, and finding similar errors with full context.

Enables a bot to inspect, query, create, edit, and script Roblox Studio instances in token-cheap batches, plus run Luau, playtests, screenshots, and inputs through Roblox's official Studio MCP connection. It runs locally over stdio or an authenticated local HTTP endpoint, returning small structured answers instead of dumping whole games into context.

A Model Context Protocol (MCP) server that converts LaTeX mathematical expressions to MathML format.

Exposes the Grok Build CLI as MCP tools for Claude Code and other clients, enabling headless AI agents to perform tasks like code reviews, web research, and file operations with configurable permission levels.

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.

Enables AI assistants to write and execute C# code directly inside Autodesk Civil 3D, providing full API access through code generation and execution.

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.

Bridges Claude Desktop with Claude Code CLI to delegate complex coding tasks like creating React apps, building APIs, and debugging scripts while maintaining interaction through the Desktop interface.

Converts Figma designs to React Native components, allowing users to extract components from Figma designs and generate corresponding React Native components with proper typing and styling.

Enables MCP clients such as Claude Desktop or Cursor to inspect a coffee-shop sales database schema, validate SQL, and run guarded read-only queries. It supports natural-language questions by exposing tools for schema description, SQL checking, and safe query execution.

Enables container orchestration on the local Docker daemon, allowing management of jobs and services via MCP tools.

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.

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.

Integrates ElevenLabs Text-to-Speech capabilities with Cursor through the Model Context Protocol, allowing users to convert text to speech with selectable voices within the Cursor editor.

MCP server that gives AI assistants a secure gVisor-isolated sandbox to run Python or JavaScript code, returning stdout, stderr, and exit codes without local access.

Enables any MCP client to evaluate Wolfram Language code in a persistent local Mathematica or Wolfram Engine kernel, export results to common file formats, and inspect or manage kernel status without cloud APIs, API keys, or runtime dependencies.

A FastMCP server that turns JSON data into Plotly figures, deployable as an isolated service on Modal. Data goes in as JSON; a validated Plotly figure (JSON) or a rendered PNG comes back over the Model Context Protocol.

A mathematical computation service that enables users to perform symbolic calculations including basic arithmetic, algebra, calculus, equation solving, and matrix operations through the MCP protocol.

A foundational project for quickly developing Model Context Protocol servers using the TypeScript SDK and Zod for schema validation. It features pre-implemented examples for tools like a calculator and greeting service, along with templates for managing dynamic resources.

Provides a headless session runtime for reactive compute graphs, enabling MCP-driven cell operations without a DOM or browser.

Enables AI agents to safely read, edit, and execute local Jupyter notebooks without running a separate service. Edits are guarded by compare-and-swap hashes and execution resumes or replays kernel state, so long-running cells aren't needlessly re-run.