mcp-server-chart vs scopus-mcp
Side-by-side comparison to help you pick between these two MCP servers.
mcp-server-chart by antvis | scopus-mcp by qwe4559999 | |
|---|---|---|
| Stars | ★ 4,068 | ★ 25 |
| 30d uses | 10,239 | — |
| Score | 84 | 43 |
| Official | — | — |
| Categories | AI / LLM ToolsDeveloper ToolsProductivity | AI / LLM ToolsDeveloper ToolsKnowledge Graph |
| Language | TypeScript | Python |
| Last commit | this month | 4 mo ago |
mcp-server-chart · Summary
A TypeScript MCP server for generating 26+ visualization charts using AntV, supporting multiple chart types and deployment options.
scopus-mcp · Summary
An MCP server connecting AI assistants to Elsevier Scopus for academic paper search and analysis.
mcp-server-chart · Use cases
- Data analysts creating visual reports from datasets
- AI assistants generating custom charts based on user requests
- Web applications embedding visualization capabilities via HTTP API
scopus-mcp · Use cases
- Academic researchers can search and analyze scientific papers related to their field
- AI assistants can provide comprehensive summaries and analyses of academic literature
- Students and researchers can track author publication histories and research impact
mcp-server-chart · Install
Installation
Install globally:
npm install -g @antv/mcp-server-chartFor Desktop Apps (e.g., Claude Desktop, VSCode):
{
"mcpServers": {
"mcp-server-chart": {
"command": "npx",
"args": ["-y", "@antv/mcp-server-chart"]
}
}
}For Windows:
{
"mcpServers": {
"mcp-server-chart": {
"command": "cmd",
"args": ["/c", "npx", "-y", "@antv/mcp-server-chart"]
}
}
}scopus-mcp · Install
Installation
Quick Setup (with uv)
- Install uv package manager
- Windows: powershell -c "irm https://astral.sh/uv/install.ps1 | iex" - macOS/Linux: curl -LsSf https://astral.sh/uv/install.sh | sh
- Get API key from [Elsevier Developer Portal](https://dev.elsevier.com/)
- Configure in Claude Desktop:
{
"mcpServers": {
"scopus-assistant": {
"command": "uvx",
"args": [
"scopus-mcp"
],
"env": {
"SCOPUS_API_KEY": "YOUR_API_KEY_HERE"
}
}
}
}Manual Setup
- Install Python 3.10+
- Install dependencies:
pip install . - Create config.json with API key
- Import MCP_tool_config.json into your MCP client