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Extracts and transforms webpage content into clean, LLM-optimized Markdown using the Model Context Protocol.
Enables web searches using DuckDuckGo and fetches/summarizes content from the results using the Jina API.
Connects to Typesense collections and retrieves data using an MCP client.
Enables AI assistants to efficiently retrieve GitHub data through GraphQL queries.
Integrates Shaka Packager with Claude AI applications, enabling video transcoding, packaging, and analysis.
Provides HTTP requests to the NFTGo Developer API, allowing access to NFT data and analytics.
Leverages AI to enhance security operations, particularly in Red Team and Pentesting workflows.
Enables intelligent AI persona collaboration and analysis through a Model Context Protocol (MCP) client.
Enables high-performance, lock-free clipboard access for AI assistants, specifically bridging Windows clipboard content to WSL2 environments.
Integrates Claude with Obsidian notes for semantic and full-text search capabilities.
Enables text models to interact with multimodal AI models through a standardized Model Context Protocol (MCP) server.
Connects Autodesk Fusion 360 with multiple AI backends to enable AI-powered parametric CAD design via natural language.
Provides AI assistants with a temporal memory system featuring human-like forgetting curves and local, human-readable data storage.
Provides real-time access to Pyth Network's decentralized oracle price feeds via the Hermes API, optimized for seamless integration into AI agents and autonomous systems.
Indexes Git repositories and provides intelligent hybrid semantic code search for AI agents via a self-hosted Model Context Protocol server.
Deploys a production-ready template for specialized medical agents as discoverable MCP tools via the Agent Orchestration Protocol.
Provides comprehensive system information and management capabilities for Linux servers through MCP and HTTP REST APIs, enabling AI agents to monitor and interact with server resources.
Empowers AI agents to interact with local code and data through an optimized Python-based Model Context Protocol server.
Exposes EMBA firmware analysis results as structured tools, enabling Large Language Models to query and reason about security findings.
Enhances AI agent reasoning with a 6-stage cognitive pipeline, multi-layer anti-hallucination, and robust bias detection.
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