A Model Context Protocol (MCP) server that provides programmatic access to TradingView's technical indicators and market data for automated trading analysis and strategy development.
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"tradingview": {
"args": [
"--from",
"/absolute/path/to/mcp-tradingview-server",
"mcp-tradingview"
],
"command": "uvx"
}
}
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FastMCP v2 server that exposes TradingView technical indicators and OHLCV data through the tradingview_scraper library. The mcp-tradingview console entry powers Claude Desktop or any MCP-aware client.
No automated test available for this server. Check the GitHub README for setup instructions.
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FastMCP v2 server that exposes TradingView technical indicators and OHLCV data through the tradingview_scraper library. The mcp-tradingview console entry powers Claude Desktop or any MCP-aware client.
./setup.sh
uv venv --python 3.11 && source .venv/bin/activateuv pip install -e .uv run mcp-tradingviewuv run mcp-tradingview --transport sse --host 0.0.0.0 --port 8000uv run mcp-tradingview --transport http --host 0.0.0.0 --port 8000 --path /mcpFASTMCP_HOST, FASTMCP_PORT, and FASTMCP_PATH environment variables override the bind settings when present.
get_indicators(symbol, exchange="BINANCE", timeframe="1h", all_indicators=True, export_result=False) – full TradingView indicator snapshot; returns success, symbol, exchange, timeframe, and an indicators mapping.get_specific_indicators(symbol, indicators, exchange="BINANCE", timeframe="1h", export_result=False) – filters the full snapshot to requested keys (case-insensitive) and echoes requested_indicators.get_historical_data(symbol, exchange="BINANCE", timeframe="1h", max_records=100, export_result=False) – streams OHLCV candles via Streamer, returning records_collected, data, and optional export_file.indicators/{symbol} emits a formatted indicator report using get_indicators defaults.export_result=True, JSON payloads are written to export/; keep large archives out of version control.Add the server to claude_desktop_config.json. Here are the recommended configurations:
claude mcp add tradingview -- uvx --from /absolute/path/to/mcp-tradingview-server mcp-tradingview
Or with uv run:
claude mcp add tradingview -- uv run mcp-tradingview --cwd /absolute/path/to/mcp-tradingview-server
{
"mcpServers": {
"tradingview": {
"command": "uvx",
"args": ["--from", "/absolute/path/to/mcp-tradingview-server", "mcp-tradingview"]
}
}
}
Alternative with uv run:
{
"mcpServers": {
"tradingview": {
"command": "uv",
"args": ["run", "mcp-tradingview"],
"cwd": "/absolute/path/to/mcp-tradingview-server"
}
}
}
{
"mcpServers": {
"tradingview": {
"command": "uv",
"args": ["run", "mcp-tradingview", "--transport", "http", "--host", "0.0.0.0", "--port", "8001", "--path", "/mcp"],
"cwd": "/absolute/path/to/mcp-tradingview-server"
}
}
}
Restart Claude Desktop after updating the configuration. The bundled CLAUDE.md provides extra guidance the model can reference while chatting.
uv run pytest executes the asynchronous test suite in test_server.py.logging.getLogger(__name__) for diagnostics; avoid printing secrets.export/ for captured fixtures when updating tests or documentation.This project is provided as-is for educational and research purposes.