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Automates browsers and APIs using the Playwright Model Context Protocol, enabling LLMs to interact with web pages.
Manages authentication through secure credential management and multi-protocol support.
Connects AI models to the Google Blogger API for content management.
Interacts with a Model Context Protocol server, enabling users to send commands, query data, and manage resources.
Find rental properties on daft.ie using an MCP client.
Interfaces with FHIR servers to retrieve healthcare data using natural language queries.
Facilitates structured clarification and information gathering from users by enabling an AI to ask strategic questions, process responses, and summarize gathered data.
Enables programmatic interaction with web browsers through a server and extension.
Integrates the GitLab API, enabling LLMs to manage repositories, merge requests, and issues.
Empowers AI assistants to generate images using the Black Forest Labs API and FLUX models.
Integrates AI assistance with Ghidra for enhanced binary analysis through the Model Context Protocol.
Provides a comprehensive toolkit unifying 50+ free tools, a built-in RAG system, and a GUI, all designed to run out-of-the-box with various LLM clients.
Establishes a production-ready trading server for integrating with the Zerodha Kite Connect API and compliant with the MCP Protocol.
Exposes Datadog APM, logs, and metrics via Model Context Protocol for AI-driven debugging and observability.
Provides a powerful Model Context Protocol server equipped with over 100 practical tools for AI development and integration projects.
Empowers AI agents with LLM-native persistent memory stored as atomic markdown files for long-term knowledge retention across sessions.
Captures the entire macOS screen and saves it as a PNG file, integrating seamlessly with Model Context Protocol clients.
Builds a self-improving knowledge graph that enhances AI agent memory and learning capabilities.
Exposes command-line interface tools for zsv, a high-performance CSV processor, as an MCP server for AI clients.
Provides visual feedback for LVGL UI code on ESP32 by compiling C snippets in a headless simulator to generate PNG screenshots and JSON widget trees.
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