Decker

Decker AI

The deterministic market-state layer your trading agents call.

Rules trade, LLMs explain. Live, non-custodial, with receipts.

Open the app · Telegram bot · Kakao channel · API docs

What you get

• Signals you can act on, with context. Not "BUY" — GO / WATCH / HOLD + progress_pct (0–100% lifecycle) + entry / stop / target.
• It explains itself. Every signal has a structural cause (multi-timeframe alignment, state machine phase) that an LLM translates into plain language.
• Same engine, two markets. Crypto (24/7) + Korean equities (KOSPI + KOSDAQ, Beta).
• Use it your way. Web app, Telegram, Kakao channel, REST API, or MCP server inside Claude / Cursor.

*"Where are we in the current structural cycle — and what's the next optimal move?"*

Get started in 60 seconds

Free tier is generous (30 calls/day on the API; Web + Telegram included). During Beta, signed-up users get PRO access for free.

See it in action

Start here — 30 seconds. No signup, no key.

curl -s https://api.decker-ai.com/api/v1/public/demo | jq .

▶️ [Play — MCP journey demo (30s)](https://gigshow.github.io/decker-ai/assets/video/decker-mcp-demo.mp4) · One live session, all 13 tools: explore a market → set your risk profile → decide → execute → manage — zero LLM in the signal path.

Shorter cut with the response and the plain-language takeaway shown together on every call (no separate captions needed): [Play — Shorts cut (35s)](https://gigshow.github.io/decker-ai/assets/video/decker-mcp-shorts.mp4)

The engine room — live FSM, MTF alignment, R:R

▶️ [Play — the live cockpit (16s)](https://gigshow.github.io/decker-ai/assets/video/decker-webapp-dashboard.mp4) · Every signal traces to a structural cause: progress_pct + operation_gate + entry / stop / target.

Signal → execution, non-custodial

▶️ [Play — non-custodial execution (16s)](https://gigshow.github.io/decker-ai/assets/video/decker-hyperliquid-page.mp4) · Click Order · wallet-sign · custody 0. Decker relays your signature only (revocable agent wallet, EIP-712). *For information only — not investment advice.*

Read it daily — and we score our own calls

▶️ Play: web hub (10s) · Telegram (6s)

Every morning (08:00 KST): the engine's view per symbol — baseline, what winning and losing look like, and a pick you can answer. Evening: the same view scored against what actually happened — hits and misses alike, on the record. *We stamp our wrong calls too.*

Web hub: decker-ai.com/briefing · Subscribe: @deckerclawbot → /briefing

Korean equities (KRX) — Beta, free

▶️ [Play — KRX (16s)](https://gigshow.github.io/decker-ai/assets/video/decker-krx-page.mp4) · Same deterministic engine on KOSPI + KOSDAQ. Portfolio states — ADD / HOLD / REDUCE / EXIT, not buy/sell. Daily closing-bell checkup at 16:30 KST · @krxdeckerbot.

Three things that make it different

1. `progress_pct` — every signal has a lifecycle. A signal at 25% progress is a different trade than the same signal at 80%. Most tools just say "BUY"; Decker tells you *where in the move you are*.

Entry                                                           Target

0%──────────33%──────────50%──────────67%──────────83%────────100% Wait Entry Active Late TP Final TP Exit

2. `GO / WATCH / HOLD` — three gates, not binary.

WATCH is the gate most tools skip. It's why users enter too early.

3. Deterministic + traceable. LLM explains, doesn't decide.

Pricing

Beta (now): all authenticated users get PRO for free via BETA_TIER_OVERRIDE=PRO. No payment required.

Web sign-up and Telegram bot are always free for the basics.

For developers

Building a bot, app, or agent on top of Decker? Everything you need — REST endpoints, MCP server (Claude / Cursor / Codex), Python SDK, OpenClaw skill, self-host — lives in one place:

→ [DEVELOPER_README.md](DEVELOPER_README.md)

# 60-second smoke test (no auth needed)

curl https://api.decker-ai.com/api/v1/public/demo

# With an API key (decker-ai.com → Settings → API Keys, or Telegram /apikey)

curl "https://api.decker-ai.com/api/v1/public/signals/BTCUSDT/latest?timeframe=1h" \ -H "X-API-Key: dk_live_xxx"

Prefer a runnable file? → examples/quickstart.py — zero dependencies (stdlib only), no key, prints the composed view + receipts in one run. Wrapping Decker for an agent crew: examples/langgraph_decker_tool.py. More in examples/.

The demo returns the composed view — the same card our daily briefing sends:

{ "layer": "STATE_VIEW", "symbol": "BTCUSDT", "ref_price": 63650.0,

"lines": ["■ BTC — 층간 힘겨루기: 주 판 아래쪽 · 지금 판 위쪽", "…"], "wait_target": "...", "invalidation": "...", "verdict_recent": [{"briefing_date": "2026-07-05", "slot": "morning", "verdict": "hit"}], "provenance": { "composer": "briefing_story.compose_card" } }

Add to Claude Desktop / Cursor (MCP): guided 2-minute setup with per-client config → [decker-ai.com/mcp](https://decker-ai.com/mcp).

Cursor (~/.cursor/mcp.json) takes a remote server directly:

{

"mcpServers": { "decker": { "url": "https://api.decker-ai.com/api/v1/mcp", "headers": { "X-API-Key": "dk_live_YOUR_KEY" } } } }

⚠ Endpoint is /api/v1/mcp (stateless Streamable HTTP) — an old /sse suffix now returns 405 Method Not Allowed.

Claude Desktop / Codex reach it through the mcp-remote bridge (needs Node/npx) — see decker-ai.com/mcp or [DEVELOPER_README.md](DEVELOPER_README.md) (endpoints · auth · rate limits · MCP tools · SDK · OpenClaw · self-host).

Running a multi-agent crew (TradingAgents / LangGraph / AutoGen)? Give your analysts one deterministic market-state instrument — with receipts — instead of re-deriving structure per prompt: → [docs/integrations/multi-agent-frameworks.md](docs/integrations/multi-agent-frameworks.md)

How the engine works (one diagram)

Raw OHLCV candles

↓ Sequence Labeler → every candle gets a role (anchor / test / signal) ↓ State Machine → C_SET → B_FORMING → B_SET → A_FORMING → W_PENDING ↓ Operation Gate → GO · WATCH · HOLD ↓ RULES Engine → 9-layer YAML rulebook → strategy + ranked choices ↓ AI Consultation → LLM translates structural state → plain language ↓ "67% progress. B-leg confirmed. Recommended: 30% partial TP or hold to target."

No price prediction. No black box. Every output traces to a formal structural cause.

Deep dives: Sequence Engine · Labeling Algorithm · Market State Theory

Supported