Power your agent
คำสั่งของผู้เผยแพร่เอง ไม่ใช่เอนด์พอยต์ของ PlugMCP
Host a copy with our keys and logs.
npx -y @dwlf/[email protected]Claude Code ไม่มีลิงก์ติดตั้งสำหรับคำสั่งแบบโลคัล ให้คัดลอกคำสั่งด้านล่างแล้วรันในเทอร์มินัล
claude mcp add dwlf-mcp-server -- npx -y @dwlf/mcp-server@0.67.0รันในเทอร์มินัล
{ "mcpServers": { "dwlf-mcp-server": { "command": "npx", "args": [ "-y", "@dwlf/[email protected]" ] } }}claude_desktop_config.json
URL แบบรีโมตหรือคำสั่งบนเครื่องของคุณ? การติดตั้งสองแบบต่างกันอย่างไร
รันบน PlugMCP
A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.
เปิดจากผู้เผยแพร่
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]" ] } }}เครื่องมือ
ยังไม่มีรายการเครื่องมือ เซิร์ฟเวอร์แบบรีโมตจะได้รายการหลังการตรวจสอบสถานะครั้งแรก
FAQ
คัดลอกคอนฟิก stdio สำหรับ Cursor, Claude Desktop, Claude Code หรือ VS Code ได้ในหน้านี้ คอนฟิกนี้ใช้การติดตั้งของผู้เผยแพร่ ไม่ใช่พร็อกซีของ PlugMCP
ระเบียนนี้ไม่ได้ระบุตัวแปรสภาพแวดล้อมที่จำเป็น
@dwlf/ ทำงานแบบโลคัลผ่าน stdio
ตรวจสอบล่าสุดเมื่อ 2026-11-13 MCP server for DWLF market analysis platform — exposes market data, indicators, signals, strategies, backtests, portfolio, trade journal, and more as AI-accessible tools