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Enables object detection, segmentation, classification, and real-time camera analysis within Claude AI using YOLO models.
Visually reviews UI edit requests by comparing before and after screenshots.
Enables AI models to interact with MySQL databases through a standardized interface.
Enables seamless integration and interaction between large language models (LLMs) and various tools, resources, and workflow prompts.
Provides a starter template for building Model Context Protocol (MCP) servers using TypeScript.
Orchestrates multiple LLMs through a single unified API, enabling routing, comparison, and multi-LLM workflows.
Enables programmatic management of Jupyter notebooks, allowing interaction and manipulation of notebook content via code.
Enables natural language interaction with SingleStore databases through the Model Context Protocol (MCP).
Provides an SSE-based Model Context Protocol server for querying the Open Source Vulnerabilities (OSV) database.
Enables Cheat Engine-like memory manipulation for MCP.
Fetches and parses standard RSS/Atom feeds, including specialized support for RSSHub, to deliver structured content to language models and other Model Context Protocol clients.
Enables large language models to safely generate and execute JavaScript code within an isolated .NET runtime environment.
Enables AI agents to search for Rust crates and retrieve their documentation from docs.rs.
Perform offline IP Whois lookups and keyword-based IP range searches to gather target asset information.
Provides persistent AI memory for code context, decisions, and knowledge across various AI tools and sessions.
Enables AI assistants like Claude to manage Apifox projects through natural language, facilitating the creation, update, and auditing of API interfaces.
Establishes a unified rules system for consistent coding standards across various AI assistants and development workflows.
Empowers AI agents by providing a local, self-hosted universal memory system that eliminates 'AI amnesia,' automatically capturing, clustering, and surfacing knowledge across all developer projects and tools.
Integrates IDA Pro's powerful analysis capabilities with large language models, serving as an MCP server plugin for LLM clients.
Enables AI assistants to control Android emulators and devices via ADB for interaction and debugging.
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