mcp-server-chart vs contextplus

Side-by-side comparison to help you pick between these two MCP servers.

	mcp-server-chart by antvis	contextplus by forloopcodes
Stars	★ 4,068	★ 1,896
30d uses	10,239	—
Score	84	56
Official	—	—
Categories	AI / LLM ToolsDeveloper ToolsProductivity	Developer ToolsAI / LLM ToolsKnowledge Graph
Language	TypeScript	TypeScript
Last commit	this month	1 mo ago

mcp-server-chart · Summary

A TypeScript MCP server for generating 26+ visualization charts using AntV, supporting multiple chart types and deployment options.

contextplus · Summary

Context+ is an MCP server that transforms codebases into searchable feature graphs using RAG, AST parsing, and semantic linking.

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

contextplus · Use cases

Large-scale code navigation and understanding in complex codebases
Semantic code search and identifier-level retrieval across projects
Code analysis including blast radius tracing and static analysis
Knowledge management for code with Obsidian-style feature hubs

mcp-server-chart · Install

Installation

Install globally:

npm install -g @antv/mcp-server-chart

For 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"]
    }
  }
}

contextplus · Install

Installation

Quick Start (npx / bunx)

No installation needed. Add Context+ to your IDE MCP config.

For Claude Code, Cursor, and Windsurf, use mcpServers:

{
  "mcpServers": {
    "contextplus": {
      "command": "bunx",
      "args": ["contextplus"],
      "env": {
        "OLLAMA_EMBED_MODEL": "nomic-embed-text",
        "OLLAMA_CHAT_MODEL": "gemma2:27b",
        "OLLAMA_API_KEY": "YOUR_OLLAMA_API_KEY"
      }
    }
  }
}

For VS Code (.vscode/mcp.json), use servers and inputs:

{
  "servers": {
    "contextplus": {
      "type": "stdio",
      "command": "bunx",
      "args": ["contextplus"],
      "env": {
        "OLLAMA_EMBED_MODEL": "nomic-embed-text",
        "OLLAMA_CHAT_MODEL": "gemma2:27b",
        "OLLAMA_API_KEY": "YOUR_OLLAMA_API_KEY"
      }
    }
  },
  "inputs": []
}

Comparison generated from public README + GitHub signals. Last updated automatically.