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Enables Large Language Models to execute Python code through the Model Context Protocol (MCP) interface.
Enables remote control of smart home devices via an MCP server, leveraging Home Assistant as a bridge.
Integrates AI agents with a knowledge graph database to provide persistent memory and contextual continuity for prompts.
Enables AI models to integrate with JustCall APIs through function calling within Model Context Protocol clients like Claude Desktop.
Enables developers to build applications that interact with the Story Protocol.
Enables persistent knowledge storage for Claude through a knowledge graph with multiple storage backends.
Establishes a bi-directional protocol bridge between Claude 4.5 Sonnet and GLM-4.6, enabling real-time architectural consultation for system design and technical decision-making.
Implements a cross-platform C SDK for the Model Context Protocol (MCP) using modern C23.
Transforms an organization's documentation into an AI-powered knowledge base, offering instant answers via chat interfaces and AI assistant integrations.
Simplifies AI agent development through a Docker-like interface for building, managing, and deploying agents using the Model Context Protocol.
Enables conversion between various geographic data formats, coordinate systems, and spatial references.
Provides access to the Exploit Database functionality, enabling users to query information about security exploits and vulnerabilities.
Provides semantic analysis of C++ codebases using libclang, enabling AI models to understand code structure.
Enables searching and retrieving research papers from various academic sources via a Model Context Protocol (MCP) server.
Integrates a comprehensive Model Context Protocol (MCP) server with LightRAG API, offering 22 tools for document management, querying, knowledge graph operations, and system management.
Enables Claude Desktop to generate images using Google's Gemini AI models.
Enables querying documents through a Langflow backend using the Model Context Protocol.
Enhances AI coding assistants by providing a persistent memory and cross-project intelligence layer within integrated development environments.
Processes images from URLs, local file paths, and numpy arrays, returning base64-encoded strings with MIME types.
Provides call graph analysis capabilities to LLMs through a Model Context Protocol (MCP) server.
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