mcp-server-chart vs langchain-mcp-server
Side-by-side comparison to help you pick between these two MCP servers.
mcp-server-chart by antvis | langchain-mcp-server by LiteObject | |
|---|---|---|
| Stars | ★ 4,068 | ★ 1 |
| 30d uses | 10,239 | — |
| Score | 84 | 33 |
| Official | — | — |
| Categories | AI / LLM ToolsDeveloper ToolsProductivity | AI / LLM ToolsDeveloper Toolsdocumentation |
| Language | TypeScript | Python |
| Last commit | this month | 6 mo ago |
mcp-server-chart · Summary
A TypeScript MCP server for generating 26+ visualization charts using AntV, supporting multiple chart types and deployment options.
langchain-mcp-server · Summary
Dual-mode MCP server providing live LangChain documentation, API references, and code examples from official sources.
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
langchain-mcp-server · Use cases
- LangChain developers needing quick reference to documentation and API while working
- AI assistants integrated with LangChain requiring up-to-date documentation access
- Educational platforms teaching LangChain with real-time examples and references
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"]
}
}
}langchain-mcp-server · Install
Installation
Using Docker (Recommended)
git clone https://github.com/LiteObject/langchain-mcp-server.git
cd langchain-mcp-server
docker-compose up --buildLocal Development
pip install -r requirements.txt
python run.py mcpClaude Desktop Configuration
Add to your claude_desktop_config.json:
{
"mcpServers": {
"langchain-docs": {
"command": "python",
"args": ["path/to/langchain-mcp-server/run.py", "mcp"],
"env": {
"PYTHONPATH": "path/to/langchain-mcp-server"
}
}
}
}