ChatWise

Visual Studio Code

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.

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

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.

# 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" ] } } } ```

Your Data. Your AI. Your Rules. Ontheia is a self-hosted, open-source AI agent platform. Run AI agents, automate workflows, and connect AI models to any tool — entirely on your own infrastructure, without sending data to external cloud services.

A standalone Python/FastAPI server that implements the Model Context Protocol (MCP) for the OPTIX threat intelligence platform. It exposes 26 analyst-friendly tools that AI assistants and programmatic consumers can use to query threat feeds, search documents and indicators, manage watchlists, triage IOCs, generate detection rules, trigger AI research, and produce intelligence reports — without needing to understand OPTIX's internal REST API.

Lutra is the first MCP compatible client built for everyone

The AI Code Editor

Conenct your ads to claude Supporting all ads channels (Google Ads, Linkedin Ads, Meta Ads, TikTok Ads) + GA4 and GTM

DOHOO is an AI-native social media management platform that lets you publish, schedule, and automate content across 8 platforms simultaneously — TikTok, Instagram, Facebook, YouTube, X (Twitter), Threads, LinkedIn, and Pinterest. With the DOHOO MCP connector, Claude can: - Schedule and publish posts, images, videos, and carousels to any connected social account - Manage 40+ social profiles from a single session - Upload media to DOHOO storage and get permanent CDN URLs - List, organize, and reuse media files and folders - Check scheduled post status and publishing history - Trigger multi-platform publishing workflows in one command Built for SMM specialists, agencies, and founders who want to run their entire social media operation directly from Claude — no switching tabs, no manual copy-paste. Connect once. Publish everywhere.

Voyei is a collaborative travel-planning app (Brazil-first, PT-BR). Its native MCP server lets you connect your own AI client — Claude, ChatGPT, Cursor or any MCP-compatible client — and have it read and edit your trips in real time, using your AI plan (Voyei never charges per token nor trains on your data). The AI can create and edit trips (days auto-generated), add and schedule places, manage reservations (hotels, restaurants, tours, events) and transport (flights, trains, cars, cruises), build budgets with expense-splitting, assemble packing lists, collaborate (shared notes, polls, messages, to-dos), update your travel Atlas and journey log, and search places & weather. Exposes 78 tools and 15 read resources, with granular OAuth scopes (read/write per area).

## 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`

SEO research tools for AI agents: keyword research and metrics, SERP and local SERP results, domain and backlink analysis, rank tracking, and Google Search Console performance.

Official npm package for Misar.Blog MCP — install with `npx -y @misarblog/mcp@latest`

Explorer-first MCP client that renders any MCP server's tools as interactive UI — no LLM required, no tool-calling loop. Point it at any MCP server over stdio or SSE and get cards, tables, charts, forms, pipelines, and dashboards auto-generated from your tool outputs. Install with `npx burnish -- <your-mcp-server>`.