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Query the VirusTotal API for comprehensive security analysis and relationship data.
Integrates with the ElevenLabs text-to-speech API for generating audio from text.
Connects agentic systems to search systems using a searXNG instance.
Enables AI interactions with WordPress installations during development using the Model Context Protocol.
Provides examples and tutorials for building AI applications using the watsonx.ai Flows Engine.
Deploys a custom remote Model Context Protocol (MCP) server to the cloud using Azure Functions with Python.
Improves AI coding by providing better context.
Automates the generation of OpenAI plugins by defining API specifications in markdown.
Manages persistent context for AI coding assistants within an MCP server environment.
Integrates the Google Ads API with Model Context Protocol clients like Claude Desktop, enabling direct data access, automated authentication, and advanced query execution.
Enables AI agents to store, retrieve, and semantically search through memories using vector embeddings.
Offers Svelte 5 and SvelteKit documentation as an MCP endpoint and LLM presets for AI assistants.
Enables Large Language Models to interact with Model Context Protocol (MCP) servers by writing and executing TypeScript/JavaScript code through a local HTTP proxy.
Serves as a powerful AI agent and IoT platform core, providing backend services for smart hardware and intelligent applications.
Empower AI agents to build effectively with Sanity using a collection of resources and integrations.
Wraps popular developer tools with structured, token-efficient, schema-validated output for AI coding agents.
Scores text based on rule-based patterns to identify formulaic AI writing and provide actionable advice.
Provides a high-performance, multi-protocol mock server supporting HTTP, WebSocket, gRPC, MQTT, SSE, GraphQL, and SOAP from a single binary.
Enables AI assistants to inspect, control, and automate the Firefox browser through the Remote Debugging Protocol, leveraging WebDriver BiDi.
Provides a privacy-first, local AI memory system that learns from user feedback and conversations to improve its responses over time.
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