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Generates book recommendations via a Node.js-based Model Context Protocol (MCP) server, designed for extensibility and integration with external APIs.
Deploys a Model Context Protocol (MCP) server on Cloudflare Workers, featuring integrated OAuth login.
Provides a Model Context Protocol (MCP) server for Warp integration and a traditional HTTP REST API for development.
Enhances Android testing capabilities and streamlines development workflows using the Espresso Android Test Framework.
Monitors and analyzes the Fetch.ai autonomous agent economy, providing real-time insights into agent interactions, transactions, and network health.
Bridges various Model Context Protocol (MCP) transports used by IDEs and AI agents with Sequa's native HTTP MCP endpoint.
Facilitates connection testing between Cline and an MCP server.
Provides read-only access to Sage 50 UK data, enabling connections from AI clients like Claude Desktop via CData JDBC Drivers.
Facilitates model-based workflows by logging meditation and critique cycles, detecting optimal mode-switch moments using neuroscience heuristics, and seamlessly injecting context.
Enables AI agents to search and retrieve content from websites.
Provides a collection of server tools built with TypeScript.
Executes XPath queries on XML and HTML content, including fetching content from URLs.
Centralizes and automates the management of global rules for AI coding assistants.
Generates structured text context files from public and private GitHub repositories, optimizing code information for large language model (LLM) task resolution.
Manages and automates web browsers, providing an interface to control browser functions, tabs, and web page interactions.
Enables large language models to interact with the GitHub API for tasks like issue creation and repository searching.
Enables Large Language Models to interact with and manage Linear issues via the Model Context Protocol.
Demonstrates the Model Context Protocol (MCP) server capabilities with support for both Stdio and Server-Sent Events (SSE) transports.
Provides access to the Hugging Face Inference API, enabling the execution of over 200,000 machine learning models for diverse AI tasks.
Provides a foundational template for developing custom Model Context Protocol (MCP) servers integrated with Puch AI.
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