Pattern intelligence API: search 24M historical charts, forward returns, regime analysis.
{
"mcpServers": {
"io-github-grahammccain-chart-library": {
"command": "<see-readme>",
"args": []
}
}
}No install config available. Check the server's README for setup instructions.
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Pattern intelligence API: search 24M historical charts, forward returns, regime analysis.
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Last commit 2 days ago. 1 stars.
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Transport: stdio. Works with Claude Desktop, Cursor, Claude Code, and most MCP clients.
No automated test available for this server. Check the GitHub README for setup instructions.
No known vulnerabilities.
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Works with: Claude Desktop | Claude Code | ChatGPT | GitHub Copilot | Cursor | VS Code | Any MCP client
Ask your AI agent "what happened the last 10 times a chart looked like this?" and get a real answer.
24 million pattern embeddings. 10 years of history. 15,000+ stocks. One tool call.
> "What does NVDA's chart look like right now?"
Found 10 similar historical patterns for NVDA (2026-04-04, RTH timeframe):
Closest match: AAPL 2023-05-12 (distance: 0.41)
Forward returns across all 10 matches:
1-day: +0.8% avg (7/10 positive)
5-day: +3.1% avg (8/10 positive)
10-day: +4.7% avg (7/10 positive)
Summary: NVDA's current consolidation near highs mirrors 10 historical
setups, most notably AAPL's May 2023 pre-breakout pattern. 8 of 10
resolved higher within a week, with a median 5-day gain of +2.8%.
No hallucinated predictions. No refusals. Just factual historical data your agent can cite.
pip install chartlibrary-mcp
Download the chart-library-1.1.1.mcpb extension file and open it with Claude Desktop for automatic installation.
claude mcp add chart-library -- chartlibrary-mcp
Add to claude_desktop_config.json:
{
"mcpServers": {
"chart-library": {
"command": "chartlibrary-mcp",
"env": {
"CHART_LIBRARY_API_KEY": "cl_your_key"
}
}
}
}
Add to .cursor/mcp.json or VS Code MCP settings:
{
"servers": {
"chart-library": {
"command": "chartlibrary-mcp",
"env": {
"CHART_LIBRARY_API_KEY": "cl_your_key"
}
}
}
}
Add to .vscode/mcp.json in your project (this file is already included in the chart-library repos):
{
"servers": {
"chart-library": {
"command": "chartlibrary-mcp",
"env": {
"CHART_LIBRARY_API_KEY": "cl_your_key"
}
}
}
}
Copilot Chat will auto-detect the MCP server when you open the project. Use @mcp in Copilot Chat to invoke tools.
ChatGPT connects to MCP servers via remote HTTP endpoints. To set up:
https://chartlibrary.io/mcpNote: The remote endpoint at
https://chartlibrary.io/mcpuses Streamable HTTP transport. If you need SSE fallback, usehttps://chartlibrary.io/mcp/sse.
For any MCP client that supports remote HTTP connections:
https://chartlibrary.io/mcp
This endpoint supports both Streamable HTTP and SSE transports, no local installation required.
Free tier: 200 calls/day, no credit card required. Get an API key at chartlibrary.io/developers or use basic search without o