接入你的智能体
发布者自己的命令。不是 PlugMCP 端点。
用我们的密钥与日志托管一份副本。
npx -y @dwlf/[email protected]Claude Code 没有针对本地命令的安装链接。复制下方命令并在终端中运行。
claude mcp add dwlf-mcp-server -- npx -y @dwlf/mcp-server@0.67.0在终端中运行。
{ "mcpServers": { "dwlf-mcp-server": { "command": "npx", "args": [ "-y", "@dwlf/[email protected]" ] } }}claude_desktop_config.json
远程 URL 还是本机命令？ 两种安装方式的区别
来自发布者
MCP server for the DWLF market analysis platform. 45+ tools that turn market noise into semantic data AI agents can reason about — candles, indicators, support/resistance, events, strategies, backtests, portfolios, trade journals, symbol activations, and more.
Works with Claude Desktop, Cursor, VS Code, and any MCP-compatible client.
MCP server for DWLF market analysis platform — exposes market data, indicators, signals, strategies, backtests, portfolio, trade journal, and more as AI-accessible tools
🤖 AI Agents: To ensure strategies created via MCP are accessible via REST API, use the same API key for both. See Agent Onboarding Guide.
The fastest way to get running — no cloning needed:
npx -y @dwlf/mcp-server
Or install globally:
npm install -g @dwlf/mcp-server
dwlf-mcp-server
You'll need a DWLF_API_KEY environment variable. See Getting an API Key below.
Add to your claude_desktop_config.json:
{
"mcpServers": {
"dwlf": {
"command": "npx",
"args": ["-y", "@dwlf/mcp-server"],
"env": {
"DWLF_API_KEY": "dwlf_sk_your_key_here"
}
}
}
}
Add to .cursor/mcp.json:
{
"mcpServers": {
"dwlf": {
"command": "npx",
"args": ["-y", "@dwlf/mcp-server"],
"env": {
"DWLF_API_KEY": "dwlf_sk_your_key_here"
}
}
}
}
Add to .vscode/mcp.json:
{
"mcp": {
"servers": {
"dwlf": {
"command": "npx",
"args": ["-y", "@dwlf/mcp-server"],
"env": {
"DWLF_API_KEY": "dwlf_sk_your_key_here"
}
}
}
}
}
dwlf_sk_DWLF_API_KEY in your MCP client configAI agents can register programmatically without browser access:
curl -X POST https://api.dwlf.co.uk/v2/agent/register \
-H "Content-Type: application/json" \
-d '{
"email": "[email protected]",
"agentId": "my-trading-bot",
"purpose": "Autonomous trading"
}'
Returns an API key immediately. Use this key for both REST API and MCP to ensure account consistency.
📖 See Agent Onboarding Guide for complete setup instructions.
Get OHLCV candles, list symbols, support/resistance levels, and indicator events (crossovers, breakouts, divergences, candlestick patterns).
Daily SMA/EMA values (10–200), trendlines (daily, weekly, hourly), market regime, and indicator events: DSS, Bollinger, EMA/SMA crosses, swing structure, SMC, VWAP, cycle pivots.
Active signals, signal history with P&L, and performance stats (win rate, avg return).
Create, update, compile, and browse visual trading strategies. List public community strategies.
Run backtests (async), get results with Sharpe ratios, and aggregate performance summaries.
Portfolio holdings with P&L, historical snapshots, trade logging, notes, and plan templates.
Activate symbols for event detection and strategy signal generation. Manage which symbols are actively monitored.
Create custom indicator-based triggers (e.g. "DSS exits oversold with bullish cross").
Full account dashboard, single-symbol briefs, and strategy performance overviews — pre-aggregated for AI consumption.
Browse educational tracks, read lessons, and search academy content.
"How's BTC looking right now?"
"Where is AAPL relative to its 50 and 200 day moving averages?"
"What active trade signals do we have?"
"Create a Golden Cross strategy using EMA 50/200"
"Backtest my strategy on NVDA over the last year"
"Log a long on ETH at 3,200 with stop at 3,050"
"Activate TSLA for my momentum strategy"
git clone https://github.com/andywilliams/dwlf-mcp-server.git
cd dwlf-mcp-server
npm install
npm run build
DWLF_API_KEY=dwlf_sk_your_key npm run start
For hot reload during development:
DWLF_API_KEY=dwlf_sk_your_key npm run dev
For multi-step workflows, see docs/cookbook.md.
Building a dashboard or visualization? Use the same libraries that power the DWLF platform:
Fetch candles via dwlf_get_market_data, compute indicators with @dwlf/indicators, render with @dwlf/charting.
MIT — DWLF / Andy Williams
MCP server for DWLF market analysis platform — exposes market data, indicators, signals, strategies, backtests, portfolio, trade journal, and more as AI-accessible tools
{ "mcpServers": { "dwlf-mcp-server": { "command": "npx", "args": [ "-y", "@dwlf/[email protected]" ] } }}工具
暂无工具列表。远程服务器在首次健康检查后会获得工具列表。
常见问题
在本页复制适用于 Cursor、Claude Desktop、Claude Code 或 VS Code 的 stdio 配置。它使用发布者的安装方式，而不是 PlugMCP 代理。
此记录未列出必需的环境变量。
@dwlf/ 通过 stdio 在本地运行。
上次检查时间：2026-11-15。 MCP server for DWLF market analysis platform — exposes market data, indicators, signals, strategies, backtests, portfolio, trade journal, and more as AI-accessible tools