Cherry Studio

Ai arcade

Premium AI image suite offering advanced fine-tuning and professional editing tools.

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。

## 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`

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Rust MCP server that gives AI agents reliable web access. Bypasses Cloudflare and bot protection using Chrome-level TLS fingerprinting, no headless browser needed. 10 tools for scraping, crawling, search, structured extraction, summarization, and more. Output is clean markdown optimized for LLMs with 67% fewer tokens than raw HTML. 8 of 10 tools work locally without an API key.

Persistent cloud memory for AI coding agents. 14 MCP tools — store, recall, semantic search, knowledge graph. Works with Claude Code, Cursor, Windsurf, OpenClaw. One config file, zero SDK.

MCP server for German & EU law. Verified, citable legal context for any LLM. Daily updates from official sources, hosted in Germany

The new purpose-built IDE to harness magic

A Tiny Terminal Chat App for AI Models with MCP Client Support

# archon-mcp-client A completely silent, standards-compliant [Model Context Protocol (MCP)](https://modelcontextprotocol.io/) client bridge that natively proxies Claude Desktop `stdio` requests directly into an Archon `SSE` remote backend over HTTPS. Unlike other public MCP proxies, this package guarantees complete `stdout` JSON-RPC hygiene, preventing log pollution that crashes Claude Desktop's strict parsers. ## Usage You do not need to install this library. Just configure your `claude_desktop_config.json` to execute it remotely via `npx`. Find more information and full documentation at [https://archonspecs.dev/docs.html](https://archonspecs.dev/docs.html). ```json { "mcpServers": { "archon-mcp": { "command": "npx", "args": [ "-y", "archon-mcp-client", "https://archonspecs.dev/mcp/sse?apiKey=your_api_key_here" ] } } } ```

MCPwner is a Model Context Protocol (MCP) server that integrates security testing tools into LLM-driven workflows. It provides a unified interface for secret scanning, static analysis (SAST), software composition analysis (SCA), and vulnerability research including 0-day discovery. Instead of manually chaining tools and pasting outputs into your LLM, MCPwner standardizes and streams results directly into the model's working context. This enables continuous reasoning, correlation, and attack path discovery across the entire security research lifecycle - from identifying known vulnerabilities to uncovering novel attack vectors.

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.

Advanced multimodal AI music generator with realistic vocals and pro-level arrangements.

Creative AI art engine designed for unique style transfers and instant visual magic.