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Streams real-time Binance market data via WebSockets.
Provides a secure, containerized environment for executing tools and code requested by large language models.
Integrates Figma design files with AI coding tools, enabling accurate code generation.
Integrates Grok AI's capabilities, including chat completion, image understanding, and function calling, into Cline via the Model Context Protocol.
Declaratively configures Model Context Protocol (MCP) servers across supported AI assistant clients using Nix.
Enables execution of MATLAB code from Large Language Models (LLMs) through a Model Context Protocol (MCP) server.
Demonstrates an identity-aware MCP server leveraging Tailscale Serve to access user information within a private Tailnet.
Aggregates functionalities from multiple Model Context Protocol (MCP) servers into a single interface.
Facilitates interaction with Raindrop.io bookmarking service as an MCP server.
Enables AI agents to interact with a Hasura GraphQL endpoint for API discovery, data fetching, mutations, aggregations, and health checks.
Provides a curated navigation site for Model Context Protocol (MCP) resources, tools, and services.
Enables AI agents to communicate, coordinate, and collaborate in real-time within the Model Context Protocol (MCP) ecosystem.
Integrates AI-powered web search directly into your development environment via a Model Context Protocol server.
Integrates AI interfaces with specialized Contextual AI agents for context-aware, grounded responses.
Integrate AI assistants with GitLab to enable conversational access to merge request information, reviews, and discussions.
Enables AI agents, assistants, and chatbots to query Kubernetes Audit Logs through the Model Context Protocol (MCP).
Caches and indexes `llms.txt` documentation locally for lightning-fast, line-accurate lookups.
Provides AI assistants with static code analysis capabilities using Joern's Code Property Graph (CPG).
Exposes CodeScene’s Code Health analysis as local, AI-friendly tools for development environments.
Enables large language models to control a computer's mouse and keyboard through an MCP or HTTP server wrapper for PyAutoGUI.
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