mcp-server-chart vs antigravity-workspace-template

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

	mcp-server-chart by antvis	antigravity-workspace-template by study8677
Stars	★ 4,068	★ 1,219
30d uses	10,239	—
Score	84	55
Official	—	—
Categories	AI / LLM ToolsDeveloper ToolsProductivity	Developer ToolsAI / LLM ToolsKnowledge Graph
Language	TypeScript	Python
Last commit	this month	this month

mcp-server-chart · Summary

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

antigravity-workspace-template · Summary

Multi-agent knowledge engine that turns any codebase into a queryable AI assistant with MCP integration.

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

antigravity-workspace-template · Use cases

Understanding complex codebases by asking natural language questions about code structure and functionality
Accelerating code reviews by quickly locating specific implementations and dependencies
Onboarding new developers to existing projects with instant access to contextual knowledge

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"]
    }
  }
}

antigravity-workspace-template · Install

Option A — Plugin install for Claude Code / Codex CLI

# Claude Code (auto-installs the Python engine CLI on first session via SessionStart hook)
/plugin marketplace add study8677/antigravity-workspace-template
/plugin install antigravity@antigravity
/antigravity:ag-setup            # interactive: pick LLM provider, paste API key, writes .env
/antigravity:ag-refresh          # runs ag-refresh directly; first refresh auto-creates .antigravity/

# Codex CLI (install the engine manually first; Codex hooks are not yet supported)
pipx install "git+https://github.com/study8677/antigravity-workspace-template.git#subdirectory=engine"
codex plugin marketplace add study8677/antigravity-workspace-template
/ag-setup                        # same flow, no antigravity: prefix in Codex

Option B — Manual install: engine + CLI via pip

pip install "git+https://github.com/study8677/antigravity-workspace-template.git#subdirectory=cli"
pip install "git+https://github.com/study8677/antigravity-workspace-template.git#subdirectory=engine"

cd my-project
cat > .env <<EOF
OPENAI_BASE_URL=https://your-endpoint/v1
OPENAI_API_KEY=your-key
OPENAI_MODEL=your-model
AG_ASK_TIMEOUT_SECONDS=120
EOF

ag-refresh --workspace .
ag-ask "How does auth work in this project?"

Option C — Register as MCP server

claude mcp add antigravity ag-mcp -- --workspace $(pwd)

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