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RelayPulse

AI developer platforms

RelayPulse is an LLM relay service monitoring platform for developers, officially positioned to monitor in real time the availability, latency, and sponsorship links of global LLM relay services. By continuously detecting interface connectivity, it helps developers quickly assess the service quality of different providers and thereby discover more stable API providers. According to the official introduction, the platform supports connectivity monitoring for mainstream model interfaces such as Claude, GPT, and Gemini, primarily addressing the problem that developers find it difficult to judge service stability when using third-party relay APIs. Currently, the available information does not provide details such as specific monitoring metrics, data refresh frequency, whether it is paid, the number of supported relay providers, whether registration or login is required, or specific usage steps; this content is not yet available.

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Remote-MCP

AI developer platforms

Remote-MCP is a type-safe solution for remote MCP (Model Context Protocol) communication, developed by ssut and open-sourced on GitHub. It provides bidirectional, concise remote communication capabilities, allowing local MCP clients to connect to remote MCP servers, thereby enabling remote access to and centralized management of model context. The project includes two core packages, @remote-mcp/client and @remote-mcp/server: the client library can run as a local MCP server and connect to a remote implementation, while the server library is used to create remotely accessible MCP services. It supports basic MCP commands, tools, and Prompt capabilities, and provides mechanisms such as custom HTTP headers, authentication middleware, basic middleware, and basic error handling, while also planning to support a full event subscription system (resource change, tool/prompt list change notifications), crash-safe handling, and more. The project also provides implementation examples such as Cloudflare Workers and standalone Node.js, and includes a Nest.js integration package. This library is a supplementary extension to the official MCP specification and is not part of the official specification. It is licensed under the MIT License. The project is currently in active development and is experimental, and breaking changes may occur.

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Respira WordPress MCP Server: 17 Page Builders

AI developer platforms

Respira WordPress MCP Server is an open-source wrapper (MIT licensed) that acts as a client for the commercial Respira for WordPress plugin, letting AI clients read and write WordPress page builder content at the element level, supporting 17 builders including Elementor, Divi, and Bricks. It automatically creates a snapshot before every write, and provides safety mechanisms such as restore, diff comparison, copy-before-edit, read-only mode, activity logs, and per-tool toggles. The server runs locally via npx and must be used together with the Respira plugin and an API key. It supports clients such as Claude Code, Claude Desktop, Cursor, Codex, and Windsurf, and also offers a hosted remote MCP server with OAuth. Core capabilities include element-level editing, declarative page building, HTML/Figma conversion, design direction and tokens, site memory, snapshot rollback, SEO and accessibility analysis, and more. The plugin is a commercial product; the README states that paid plans start at 9 euros per month, with a free trial included.

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RestGPT

AI developer platforms

RestGPT is an autonomous agent based on large language models, designed to control real-world applications such as movie databases and music players through RESTful APIs. The project was released by Yifan-Song793 on GitHub and includes the paper's code. RestGPT adopts an iterative coarse-to-fine online planning framework and introduces an executor to invoke RESTful APIs. Its core components include a planner (which generates a natural language subtask for the current step), an API selector (which maps coarse-grained high-level subtasks into finer-grained API call plans), and an executor (which executes the API call plan, where the caller organizes parameters according to the API plan and documentation, and the parser generates Python code according to the response schema to parse the response). To evaluate performance, the project also proposes the RestBench benchmark, which includes two real-world scenarios, the TMDB movie database and the Spotify music player, as well as manually annotated instructions and golden solution paths. The code has been released, and the demo is under construction.

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