Mymcp4
Description
# DataEyes MCP Service [](https://pypi.org/project/dataeyes-mcp-server/) [](LICENSE) [中文版说明](README_zh.md) This project provides an MCP…
About
# DataEyes MCP Service [](https://pypi.org/project/dataeyes-mcp-server/) [](LICENSE) [中文版说明](README_zh.md) This project provides an MCP (Machine-Comprehensible Protocol) service powered by…
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- Author
- dataeyesai
- Downloads
- 241
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- Standardized MCP-compatible protocol for seamless integration
- Hosted SSE service and self-hosted CLI options available
- Extensible toolset with reader and search tools
- Reader returns web content in LLM-friendly Markdown format
- Search retrieves relevant web page summaries
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Mymcp4Command (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Obtain an API KEY from https://shuyanai.com, then either point your AI Agent to the hosted SSE endpoint (https://mcp.shuyanai.com/sse?key=YOUR_API_KEY) or install and run the server locally via uvx dataeyes-mcp-server after setting the DATAEYES_API_KEY environment variable.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"mymcp4": {
"dataeyes-mcp-server": {
"command": "uvx",
"args": [
"dataeyes-mcp-server"
],
"env": {
"DATAEYES_API_KEY": "sk-WEqKb5gdY84MAbTj3rHYZ1nvUhB3ogkC"
}
}
}
}
}McpServers
{
"dataeyes-mcp-server": {
"command": "uvx",
"args": [
"dataeyes-mcp-server"
],
"env": {
"DATAEYES_API_KEY": "sk-WEqKb5gdY84MAbTj3rHYZ1nvUhB3ogkC"
}
}
}DataEyes MCP Service
This project provides an MCP (Machine-Comprehensible Protocol) service powered by DataEyes Intelligence. It exposes a series of tools (e.g., web content reading) to enhance the capabilities of AI Agents.
🤔 What is MCP?
MCP (Machine-Comprehensible Protocol) is a protocol designed for communication between AI Agents and tools. It standardizes how an agent discovers the capabilities of a tool and how it invokes them, enabling seamless integration between different AI systems and services.
✨ Features
- Standardized Protocol: Fully compatible with the MCP standard for easy integration.
- Hosted & Self-Hosted Options: Provides a stable, high-performance hosted SSE service and a self-hosted CLI for flexibility.
- Extensible Toolset: Offers an expanding suite of tools.
🛠️ Available Tools
This service provides a set of tools that can be invoked through the MCP protocol.
📖 reader
The reader tool can access a web page URL and return the main content in a clean, LLM-friendly Markdown format.
Parameters:
- url (string, required): The URL of the web page to read.
- timeout (integer, optional, default: 30): The page load timeout in seconds (range: 1-60).
🔍 search
The search tool allows you to search the internet and returns relevant web page summaries.
Parameters:
- q (string, required): The search query keywords.
- num (integer, optional, default: 10): Number of search results to return (min: 1, max: 50).
🚀 Getting Started
1. Obtain Your API KEY
An API KEY is required to use the DataEyes services.
Official Website: https://shuyanai.com
Please register and log in to obtain your exclusive API KEY.
2. Choose Your Usage Method
Option A: Hosted SSE Service (Recommended)
This is the easiest way to get started. Just point your AI Agent to our hosted SSE (Server-Sent Events) endpoint.
Endpoint URL:
https://mcp.shuyanai.com/sse?key=YOUR_API_KEY
Remember to replace
YOUR_API_KEY with the key you obtained.
Option B: Self-Hosting via CLI
If you prefer to run the server locally, you can install it as a command-line tool.
a. Installation
We recommend using uv to install and run the tool in an isolated environment.
# First, install uv if you don't have it
pip install uv
Run the server using uvx
uvx dataeyes-mcp-server
b. Environment Variable
For self-hosting, the server reads the API KEY from the DATAEYES_API_KEY environment variable.
- For macOS/Linux:
export DATAEYES_API_KEY='your_api_key'
- For Windows:
setx DATAEYES_API_KEY "your_api_key"
> Note: You may need to restart your terminal for the changes to take effect.
Once the environment variable is set, you can run uvx dataeyes-mcp-server to start the service, which will communicate via stdio.
📄 License
This project is licensed under the MIT License.
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