
AgentHotspot MCP
- 3 repo stars
- Updated January 21, 2026
- AgentHotspot/agenthotspot-mcp
AgentHotspot MCP is a MCP server that lets your AI agent search thousands of MCP connectors in the AgentHotspot marketplace.
About
AgentHotspot MCP is a stdio Model Context Protocol server that exposes search against the AgentHotspot marketplace so developers and teams can discover MCP connectors while coding with Claude Code, Cursor, Codex, or similar agents. Install the PyPI package, add it to your MCP config, and ask the agent to find servers by capability, vendor, or use case when you are wiring integrations, prototyping agents, or comparing alternatives to hand-rolled APIs. It does not run the connectors themselves—it is a discovery layer on top of a large catalog, which speeds the loop of shortlisting, copying install hints, and registering the right remote or local servers. Pair it with project-specific MCPs once you have narrowed choices; skip it if you already maintain a fixed connector list and rarely add new tools.
- Search the AgentHotspot marketplace for MCP connectors from inside the agent
- stdio PyPI package (agenthotspot-mcp v1.0.2) for standard MCP client config
- Marketplace-scale catalog described as thousands of connectors
- Keeps connector research in-thread instead of manual registry browsing
AgentHotspot MCP by the numbers
- Data as of Aug 10, 2026 (Skillselion catalog sync)
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| repo stars | ★ 3 |
|---|---|
| Package | agenthotspot-mcp |
| Transport | STDIO |
| Auth | None |
| Last updated | January 21, 2026 |
| Repository | AgentHotspot/agenthotspot-mcp ↗ |
What it does
Let your coding agent search AgentHotspot’s MCP connector catalog so you can pick and wire integrations without tab-hopping.
Who is it for?
Best when you're assembling or expanding an MCP toolchain and want agent-native marketplace search during integration design.
Skip if: Skip if you need hosted runtime for connectors, private enterprise catalogs only, or deep security vetting beyond search results.
What you get
Your agent can query a broad connector catalog in conversation and shortlist MCPs to register in your client config faster.
- Ranked or listed MCP connector candidates from marketplace search
- Install or registry pointers to follow up in your MCP config
- Shorter integration research loop inside the agent thread
By the numbers
- Catalog described as thousands of MCP connectors
- Package version 1.0.2 on PyPI with stdio transport
- Published as io.github.agenthotspot/agenthotspot-mcp on the MCP registry schema
README.md
AgentHotspot MCP Server
🔍 Search 6,000+ MCP connectors directly from your AI agent
Features • Quick Start • Installation • Usage • Contributing
🌟 What is AgentHotspot?
AgentHotspot a marketplace for AI agent developers. It provides:
- 🔌 6,000+ curated MCP connectors ready to connect and integrate for agent builders
- 🚀 One-click integration with Claude Desktop, OpenAI Agents, n8n, and more
- 💰 Instant Monetization tools for MCP connector creators
- 📊 Analytics dashboard to track usage and performance
This MCP server allows your AI agents to search and discover oss connectors from the AgentHotspot marketplace.
✨ Features
- 🔍 Search Connectors — Query the AgentHotspot catalog with natural language
- 📦 Lightweight — Minimal dependencies, easy to install
- 🔧 MCP Compatible — Works with any MCP-compatible client
📦 Installation
Prerequisites
- Python 3.10+
- An MCP-compatible client (Claude Desktop, OpenAI Agents SDK, custom agents, etc.)
From Source
git clone https://github.com/AgentHotspot/agenthotspot-mcp.git
cd agenthotspot-mcp
# Install dependencies
pip install -r requirements.txt
# Install module
pip install -e .
🔧 Usage
Run the Server Independently
# Run directly
python3 -m agenthotspot_mcp
# Or using the script
python3 src/agenthotspot_mcp/server.py
With Claude Desktop
Add this configuration to your Claude Desktop config file:
macOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"agenthotspot": {
"command": "python3",
"args": ["-m", "agenthotspot_mcp"]
}
}
}
With LangChain
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
async def main():
client = MultiServerMCPClient({
"agenthotspot": {
"transport": "stdio",
"command": "python3",
"args": ["-m", "agenthotspot_mcp"],
}
})
tools = await client.get_tools()
print(tools)
# Remaining code ...
# (see examples/langchain_example.py for full agent example)
asyncio.run(main())
🗂️ Project Structure
agenthotspot-mcp/
├── src/
│ └── agenthotspot_mcp/
│ ├── __init__.py # Package exports
│ ├── __main__.py # Entry point
│ └── server.py # MCP server implementation
├── examples/
│ ├── claude_config.json # Claude Desktop config example
│ └── langchain_example.py # Python langchain usage example
├── pyproject.toml # Package configuration
├── requirements.txt # Dependencies
├── LICENSE # MIT License
├── CONTRIBUTING.md # Contribution guidelines
└── README.md # This file
🤝 Contributing
We welcome contributions! See CONTRIBUTING.md for guidelines.
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
📄 License
This project is licensed under the MIT License — see the LICENSE file for details.
🔗 Links
- 🌐 Website: agenthotspot.com
- 📦 Connectors: Browse 6,000+ connectors
- 🐦 Twitter/X: @agenthotspot
- 🐙 GitHub: AgentHotspot
- 📧 Support: support@agenthotspot.com
Built with ❤️ by the AgentHotspot team
Recommended MCP Servers
How it compares
MCP marketplace search integration, not a single-purpose data or task connector.
FAQ
Who is AgentHotspot MCP MCP for?
Developers using Claude Code, Cursor, or Codex who add MCP servers often and want in-chat discovery of marketplace connectors.
When should I use AgentHotspot MCP MCP?
Use it during the build phase when you are choosing integrations, comparing MCP options, or filling gaps in your agent’s tool list.
How do I add AgentHotspot MCP MCP to my agent?
Install the PyPI package agenthotspot-mcp, register the stdio server in your client’s MCP config, restart the agent, and invoke search tools from the session.