PreviewShip is a frontend preview deployment and sharing platform for developers. Deploy your static site and get a shareable preview URL in seconds — no Git, no CI/CD, no complex configuration.

HyperChat is a Chat client that strives for openness, utilizing APIs from various LLMs to achieve the best Chat experience, as well as implementing productivity tools through the MCP protocol.

GPT Image 2 AI is an MCP-compatible service for generating and transforming images using text prompts. It provides a simple interface for AI agents and developer tools to create visual outputs, refine images, and experiment with generative workflows in a programmatic way. The service is designed to be lightweight and easy to integrate into MCP-based environments, enabling use cases such as: text-to-image generation image refinement and variation visual prototyping workflows AI-assisted content pipelines 👉 https://gptimg2ai.net This server can be used by AI agents to generate visual assets dynamically, making it suitable for creative tooling, automation workflows, and experimental AI applications.

Roo Code (prev. Roo Cline) gives you a whole dev team of AI agents in your code editor.

AiPy Pro 就是个能听懂你说话的智能助手，跟它说句话就能帮你写好 PPT、自动操作电脑、手机和服务器，还能处理数据写代码，不用自己动手，工作省事很多。

Your AI Partner on Desktop

Code at the speed of thought – Zed is a high-performance, multiplayer code editor from the creators of Atom and Tree-sitter.

Call MCP Server Tools Online

Experimental AI audio platform for ambient soundscapes and innovative sound design.

A local-only macOS Model Context Protocol server that exposes your Proton Mail account to Claude Desktop and Claude Code via Touch-ID-gated tool calls.

## Overview ### what is Chain.Love MCP? Chain.Love MCP is a hosted remote MCP server and gateway for AI agents. It provides a single endpoint for discovering and comparing Web3 infrastructure services across 50+ blockchain networks, including RPCs, indexing, oracles, storage, compute, and developer tools. ### how to use Chain.Love MCP? To use Chain.Love MCP, add the hosted endpoint to your MCP client and connect to `https://app.chain.love/mcp` over Streamable HTTP. For public use cases, the basic MCP server URL is enough. For private downstream MCPs, add credentials only when required using `x-chainlove-cred-<credentialKey>` headers. ### key features of Chain.Love MCP? - Hosted remote MCP gateway for AI agents - Single endpoint for Web3 infrastructure discovery across 50+ blockchain networks - Aggregates infrastructure options across RPCs, indexing, oracles, storage, compute, and developer tools - Streamable HTTP transport - Public documentation and onboarding resources available online ### use cases of Chain.Love MCP? - Discovering and comparing Web3 infrastructure providers across many blockchain networks - Finding RPC, indexing, oracle, storage, compute, and developer tooling options through one MCP server - Giving AI agents a single hosted integration surface for Web3 infrastructure discovery - Reducing the need to integrate many separate provider-specific endpoints ### FAQ from Chain.Love MCP? - Can Chain.Love MCP be used as a hosted remote MCP server? Yes. Chain.Love MCP is designed to be consumed as a hosted remote MCP endpoint at `https://app.chain.love/mcp`. - Does Chain.Love MCP require credentials? Not always. Some downstream integrations may require credentials, which can be passed using `x-chainlove-cred-<credentialKey>` headers when needed. - How do I know which credential header to use? You can check the open-source Chain.Love registry at `https://github.com/Chain-Love/chain-love/blob/main/references/offers/mcpservers.csv` or browse `https://app.chain.love/toolbox/mcpservers` and look for the relevant `credentialKey` value. - Where can I learn more? Landing page: `https://www.chain.love/mcp-gateway` Documentation: `https://chain-love.gitbook.io/mcp-module`

Studio is where you run MCP tools in the browser against real credentials -- see inputs, outputs, and errors before you trust an agent. Enable bundles in your workspace, then add your Hub or per-bundle streamable HTTP URL in Cursor, Claude, ChatGPT, or VS Code. Workspace-scoped credentials; optional mcpbundles CLI on PyPI.

Visual Studio Code

High-fidelity AI video generator specializing in cinematic realism and complex motion dynamics.

Manage your LinkaGoGo bookmarks through any AI assistant that supports the Model Context Protocol (MCP). Search, add, organize, tag, move, and export bookmarks conversationally — 16 tools for full bookmark and folder management. Connect via Claude.ai, Claude Desktop, or any MCP-compatible client.

Lutra is the first MCP compatible client built for everyone

Fast, intuitive AI image generation platform for everyday creative inspiration.