What does the Hunter MCP Server do?
It wraps the Hunter API from Qianxin, enabling AI assistants to search for information about internet-connected devices and services.
@help116114
Basic information
An Model Context Protocol (MCP) server that provides access to Hunter API functionality, allowing AI assistants to query information about internet-connected devices and services.
No standard config provided
This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.
RepositoryTool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
A Model Context Protocol (MCP) server that provides access to Hunter (Qianxin) API functionality, allowing AI assistants to query information about internet-connected devices and services.
Clone the repository, install dependencies, build the server, set the Hunter_API_KEY environment variable, and start with npm start. Integrate with Claude or other MCP-compatible assistants by adding the server to your MCP settings with the command node /path/to/build/index.js and the environment variable HUNTER_API_KEY.
It wraps the Hunter API from Qianxin, enabling AI assistants to search for information about internet-connected devices and services.
Node.js version 14.17 or higher and a valid Hunter API key (obtainable from the Hunter platform) are required.
You must set your Hunter API key via the environment variable `Hunter_API_KEY` (or `HUNTER_API_KEY` in MCP settings) before running the server.
All data is retrieved live from the Hunter (Qianxin) API; the server does not store any data locally beyond caching search results as resources.
The server uses standard I/O (stdio) transport, as typical for MCP servers. The command is `node` with the built `index.js` as argument.
AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents

A good sequence diagram can solve almost any communication problem in engineering. Volley lets your agent write them as plain text, with the real request and response payloads on every arrow. It checks its own syntax wi

Model Context Protocol Servers

Model Context Protocol Servers
Open-source MCP to use Blender with any LLM
Comments