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Enables AI models to interact with Ethereum Layer 2 networks for deploying tokens and managing transactions.
Streamline the management and optimization of container environments, offering efficient deployment and monitoring across various platforms.
Calculates technical analysis indicators, specifically Exponential Moving Averages (EMAs), for cryptocurrency trading data via an SSE transport layer.
Enables AI agents and automation scripts to control and program a Commodore 64 via its REST API, specifically for Ultimate 64 hardware.
Automate PostgreSQL management, monitoring, security, diagnostics, and optimization through an AI-integrated server, offering 237+ specialized tools for AI assistants like Claude and ChatGPT.
Fetches trending topics from various online platforms using the Model Context Protocol (MCP).
Provides an Elixir DSL for defining Model Context Protocol (MCP) tools, prompts, and routers.
Provides a mixture-of-experts visual question-answering server, solving complex visual grounding and image question-answering tasks.
Facilitates interaction with OpenAI, Anthropic, and EnrichB2B services using the Model Context Protocol.
Analyzes and automates Zabbix events using AI-powered Model Context Protocol.
Enhances web research capabilities for large language models through intelligent search queuing and content extraction.
Analyzes customer data, creates targeted marketing campaigns, and provides actionable business insights using AI agents within a Customer Relationship Management system.
Connects AI systems to real-time cryptocurrency data and trading platforms through standardized Model Context Protocol servers.
Facilitates seamless interaction for AI agents with Firebase services through a standardized Model Context Protocol server.
Provides semantic memory capabilities using the Qdrant vector database with configurable embedding models for efficient vector search and retrieval.
Leverages Google Gemini AI to provide intelligent project planning and comprehensive code review capabilities via the Model Context Protocol.
Develops a chatbot application leveraging Aspire, Semantic Kernel, and Ollama for conversational AI and local LLM support.
Enables document question answering by ingesting and querying PDF documents using the GroundX API.
Provides a custom Databricks server to test Model Context Protocol (MCP) integrations and On-Behalf-Of (OBO) authentication.
Establishes a connection and provides a standardized protocol for interacting with a Crawl4AI Docker API server.
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