"Information about Meta (Facebook's parent company)" matching MCP servers:

Enables AI models to dynamically create and execute their own custom tools through a meta-function architecture, supporting JavaScript, Python, and Shell runtimes with sandboxed security and human approval flows.

Figma MCP server that lets agents execute arbitrary JavaScript inside a running Figma desktop app via a local development plugin, enabling real-time document inspection and manipulation while avoiding REST API rate limits.

Lightweight MCP server for After Effects that enables Cursor Agent to execute ExtendScript code inside AE via a single tool, similar to Blender MCP.

Aggregates tools from multiple MCP servers, generates TypeScript definitions, and executes custom TypeScript scripts to orchestrate cross-server tool calls.

Provides Copilot Studio with six tools for secure workspace file operations and one-time execution of pre-approved Python jobs in isolated, network-less Docker containers, with strict access controls and audit logging.

MCP server for Python build123d to help AIs develop and reason about 3D models and CAD

A meta-MCP server that orchestrates tools from multiple MCP servers, enabling complex Python workflows with loops and conditionals.

An MCP server that enhances sequential thinking with meta-cognitive capabilities including confidence tracking, hypothesis testing, and organized memory storage through graph-based libraries and structured JSON documents.

A comprehensive learning project demonstrating MCP server implementation with tools for calculator operations, file management, and system information retrieval, including Google ADK integration patterns and best practices.

A boilerplate project for quickly developing Model Context Protocol (MCP) servers using TypeScript SDK. Includes example tools for calculations and greetings, plus system information resources.

Provides comprehensive documentation about AWS AgentCore framework to GenAI tools, enabling users to build production-ready AI agents with enterprise-grade security, observability, and scalability. Offers guidance on identity management, API integration, monitoring, code execution, memory storage, and tool integration for AI agents.

A boilerplate project for quickly developing Model Context Protocol (MCP) servers using TypeScript SDK. Includes example tools like calculator and greeting functions, plus system information resources.

Aggregates tools from multiple upstream MCP servers and exposes them through 4 meta-tools, enabling LLMs to discover and use hundreds of tools without loading all schemas upfront.

Provides AI-driven development tools including file system operations, multi-language code analysis with tree-sitter, Git operations, code execution, and system information retrieval.

A cheap, fast execution layer for MCP agents that delegates file reads, edits, and command runs to a local DeepSeek Harness, reducing cost and latency while keeping the parent agent in control of planning and reasoning.

Enables large language models to access user geolocation information through EdgeOne Pages Functions using the Model Context Protocol.

MCP server to provide Sketch layout information to AI coding agents like Cursor

Enables agents to use many MCP servers without context bloat by exposing meta-tools (search, load, call, run_code) that reduce token usage via progressive disclosure and result trimming.

A Model Context Protocol server that enables Claude AI to interact with Paybyrd's payment processing API, allowing for creating payment links, processing refunds, and retrieving order information.

A self-improving coding agent MCP server that enables code execution, semantic memory, and reusable skills via sub-agents, turning your AI client into a meta-operating system.