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Integrates Google's OR-Tools constraint programming solver with Large Language Models using the Model Context Protocol for AI models.
Provides a standardized connection layer between artificial intelligence systems and diverse biomedical resources.
Enables semantic search and management of documentation through vector similarity using RAG techniques.
Empower AI agents to remotely control graphical user interfaces on Windows, Linux, macOS, and other VNC-compatible systems.
Enables agents and LLMs to view, rent, and manage GPU instances on the Hyperbolic cloud.
Enables LLMs in agent mode to analyze images by extracting and converting them to base64.
Generates images from text prompts using the Together AI platform through a Model Context Protocol (MCP) server.
Provides resource-based access to AI model inference, particularly for image generation tasks, through the Replicate API.
Empowers AI agents with enterprise-grade access to Kotlin-based Android development projects, enabling AI-assisted coding and comprehensive project management.
Determines when human intervention is needed in AI agent operations through a sequential scoring system.
Empower AI agents with comprehensive knowledge and tools for AI-assisted development of SAP Mobile Development Kit (MDK) applications.
Integrates Extend APIs with AI frameworks like Anthropic's MCP, OpenAI, LangChain, and CrewAI.
Provides comprehensive access to the UniProt protein database via the Model Context Protocol (MCP).
Enables LLMs to record, retrieve, and manage their reasoning processes during problem-solving.
Provides comprehensive document processing capabilities via a Model Context Protocol (MCP) server.
Provides real-time cryptocurrency price data from the OKX exchange via the Model Context Protocol.
Bridges various AI agent command-line interfaces with Sequa's native streamable HTTP Model Context Protocol endpoint.
Provides a standardized interface for interacting with Azure FHIR servers using the Model Context Protocol (MCP).
Facilitates interaction with Cisco Modeling Labs (CML) via the Model Context Protocol (MCP) for LLM applications.
Enables AI models to interact with Ethereum blockchain data via JSON-RPC calls.
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