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Integrates Wazuh security data with Large Language Models, providing real-time security context.
Stores and retrieves AI assistant interaction data using a Neo4j graph database.
Locates nearby places using IP-based geolocation and the Google Places API.
Provides a curated list of Model Context Protocol (MCP) server implementations for various integrations and functionalities.
Integrates a Message Communication Protocol (MCP) server with Wireshark to analyze and interact with network packets using natural language.
Provides an MCP Server for accessing and searching data related to the JSer.info JavaScript information website.
Connect AI agents and LLMs to Google Flights data for comprehensive flight information and booking assistance.
Enables interaction with GrowthBook directly from LLM clients for managing feature flags and experiments.
Monitors file system events and provides real-time notifications to MCP clients for file changes.
Enables seamless data connectivity to the Trading212 trading platform, facilitating advanced interaction capabilities via the public beta API.
Enables AI assistants to interact with Paper's trading platform API using natural language.
Integrates Firewalla firewall data with AI platforms like Claude for advanced network security monitoring and management.
Caches and indexes `llms.txt` documentation locally for lightning-fast, line-accurate lookups.
Transforms AI assistants into powerful offensive security companions by providing seamless access to professional penetration testing and CTF-solving tools from Kali Linux.
Enables AI agents to generate and execute Python code in a sandboxed environment, seamlessly integrating with external Model Context Protocol tools.
Provides a persistent memory system for AI robots to learn from experience.
Empower AI assistants to control multiple CAD applications via the Model Context Protocol.
Automatically enhances Claude Code setups by continuously learning best practices from high-signal GitHub repositories and proposing safe `CLAUDE.md` improvements.
Provides a shared memory system for multi-agent AI applications, enabling seamless knowledge retention and collaboration across diverse systems and machines.
Provides AI agents with a self-hosted, three-tiered persistent memory system featuring semantic embeddings and zero API costs.
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