ZBS Index What actually exists in applied AI, with the source next to it

mcp server

decker

Deterministic market-state engine for trading agents — state, gate, coordinates, with receipts.

Description as published by the maintainer. Source

  • version 1.10.0
  • active

active — Most recent push to the repository was 2026-08-08.

What this server can do

12 functions, named and described by the server itself. Parameter names are shown because they say more about what a function does than its name usually does.

decker.close_position(symbol, close_fraction)
Axis③ (Order/Execution) — closes (or partially reduces) an existing position through DECKER'S OWN execution engine (see decker.place_order for what that means — same account-linkage requirement applies here for real positions). Unlike place_order, there is no crypto-6 restriction — this reduces risk, not adds it, so any symbol you actually hold (including HL-synthetic/KRX paper positions) can be closed. Mode is NOT chosen by the caller — this looks up whatever position(s) actually exist for the symbol (real via live exchange query, virtual via the paper ledger) and closes whichever are open; if both a real and a virtual position exist for the same symbol, both are closed and the response reports execution_mode as 'mixed'. No open position for the symbol = a clean not-found response, not an error — safe to call speculatively. Required: symbol.
decker.get_assembly(symbol)
Multi-timeframe optimal-path assembly per symbol (STRATEGY_LAYER §8): one deterministic machine verdict combining all live timeframes — direction, grade (aligned | structure+pullback | exhaustion-reversal), entry (now vs wait, with source TF), stop (risk stop), target (upper-TF target), RR, and a conditional switch coordinate on mixed structure. Upper TF supplies the target (slower = higher success), lower TF supplies the entry. This is the single judgment authority — narrate or filter it, do not re-decide coordinates. Omit symbol for all 14 universe symbols.
decker.get_market_state(symbol, timeframe)
Market State v0 — current engine structural state for a symbol/timeframe (latest evaluated bar, persisted engine emit read as-is, zero recompute). DOMAIN FRAME (why this engine exists): the market is read as a TARGET GAME — every coordinate comes from a *verified anchor* (a past level where a triggered move actually succeeded). The `game` block tells you the context that matters: game.status = forming_target (new anchor set, awaiting test) | testing_target (price is testing whether the declared target holds) | direction_resolved (game decided, price traveling); game.target = WHO is being judged (anchor id/phase/band); game.progress_dest = where price goes if the move proceeds (the opposing verified anchor to conquer); game.reverse_dest = where it goes if the move fails (the opposite house — also the stop logic's home); game.why_gate = full gate derivation chain; game.zt_regime = output canonicality (restored = deterministic delta lineage). action_gate alone (GO/WATCH/HOLD) is only a posture — the game context is the information. RAW CONTRACT: fields are engine-native vocabulary (c_state, hold_reason, R_* risk enums …), NOT customer-facing prose — for a human-language view use decker.get_view (with tf) or decker.get_reading. layer=STATE: this is a market-state reading, NOT a trade instruction. Absent fields are null (engine did not emit that axis — no filling). Before placing any order through any execution tool, check the intent with decker.validate_intent. Required: symbol, timeframe.
decker.get_positions
Axis③ (Order/Execution) — this user's actual exposure: real open futures positions (execution_mode=real, with live sl_price/tp_price), virtual (paper) open positions, and the last 10 closed round-trips per mode. This is what your money actually did, distinct from decker.get_signals (axis②, what the engine recommends) — use this before deciding whether to place another order (avoid duplicate/over-exposure) and to check current protective stop/target on a real position.
decker.get_reading(tf, symbol, include_tfs)
AI-synthesized market reading for a symbol/timeframe, in customer-facing language: current state description, directional bias scores, bidirectional break targets, MTF verdict per timeframe, and an execution hint (stance + long/short setups). Engine-native raw fields are NOT exposed here — use the REST raw contract (GET /public/reading) or decker.get_market_state for those. Required: symbol.
decker.get_signals(limit, symbols, timeframe, action_gate, min_progress)
Active trading signals for the current user (with Skill Overlay applied), in customer-facing shape: coordinates (entry/target/stop), decision (ENTER/WAIT/SKIP), action_gate posture (GO/WATCH/HOLD — a stance, not an order command), progress, MTF verdict, and a plain-language summary_ko line. risk_reward_ratio is computed on the DISPLAYED coordinates (after overlay). Signals are retained rather than cut when they age (turn-retention policy) — read freshness_state (open|aged) / age_bars / freshness_sec before treating an old PENDING row as current. Filtered by symbols / min_progress / action_gate. Before placing any order through any execution tool, check the intent with decker.validate_intent.
decker.get_state_timeline(limit, since, symbol, timeframe)
Market State v0 — per-bar state timeline for a symbol/timeframe (same schema as decker.get_market_state, except each item carries a SLIM `game` tag {status, target_id, zt_regime, provenance} instead of the full game block — read status transitions across bars to see how the target game unfolded (forming → testing → resolved/failed); ascending by bar_ts). Bars the engine did not emit are simply absent (honest gaps, no filling). Required: symbol, timeframe.
decker.get_user_skills
Trading skill catalog + currently active overlay for this user. Returns 3 base skills (conservative_v0/standard_v0/aggressive_v0) and the user's selected one.
decker.get_view(tf, symbol)
The engine's VIEW for a symbol — the same composed card the daily briefing sends (single composer, verbatim): overall verdict, big/main timeframe alignment, the current game narrative in plain language, coordinates (baseline ref_price / target / invalidation), 'at this price, this view', and recent self-scoring verdicts (receipts). layer=STATE_VIEW: a market-state reading, NOT a trade instruction. Prefer this over get_market_state when you want the interpreted view instead of raw engine fields. Before placing any order through any execution tool, check the intent with decker.validate_intent. Required: symbol.
decker.place_order(side, symbol, notional_usd)
Axis③ (Order/Execution) — unlike every other tool here, this one moves money. It places a market order through DECKER'S OWN execution engine (same path as the decker-ai.com chat trading UI, source='mcp') — it does NOT hand off to your own broker connection or exchange account; Decker executes using whatever exchange credentials this user has separately linked to their Decker account on the website. execution_mode (virtual|real) is NOT chosen by the caller — it is resolved server-side from this user's account settings (user_settings.execution_mode) AND the platform's real-trading kill switch; a real-money order requires both an explicit user opt-in AND role/tier eligibility (PRO/ENTERPRISE or admin) AND passing the tier's hard notional/leverage/daily-count caps (checked here before dispatch — violation blocks the order, does not downgrade it to virtual). The response always states which mode actually executed — treat 'virtual' in the response as authoritative even if you expected real. Restricted to the crypto-6 universe (BTCUSDT/ETHUSDT/SOLUSDT/BNBUSDT/XRPUSDT/DOGEUSDT) for this MCP path — HL-synthetic and KRX symbols are read-only via other tools. Call decker.validate_intent first to read the engine's current stance; this tool does not check it for you. Required: symbol, side, notional_usd.
decker.set_skill_overlay(skill_id)
Change active trading skill overlay for this user. Immediately affects all subsequent get_signals calls and downstream channels. Required: skill_id.
decker.validate_intent(side, symbol, timeframe, order_type)
Pre-trade gate check for a proposed order intent. Call this BEFORE placing any order through any execution tool (e.g. a broker MCP's review→place flow). Checks the intent (symbol + side) against Decker's deterministic market state: engine action_gate (GO/WATCH/HOLD — a transition posture, not an order command), current structural state, and the active signal's direction / invalidation (stop) coordinates. Returns a stance reading, NOT an approval or rejection: the vocabulary is the engine gate as-is plus a mechanical side_alignment (aligned/opposed vs the active signal's direction). covered=false means the engine does not emit state for this symbol — treat as unknown, not as HOLD. The order decision and responsibility remain with the calling agent/user. Every check is persisted to an auditable decision ledger (check_id). Required: symbol, side.

Last successful function declaration observed on . Source: https://api.decker-ai.com/api/v1/mcp. We list what the server declared; we do not call any of these functions.

Endpoint status observed on . Source: https://api.decker-ai.com/api/v1/mcp.

Signals

These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.

Signal Value What it measures Window Observed Source
GitHub stars 3 Number of GitHub accounts that bookmarked this repository since it was created. It is a bookmark count, not installs, not active users and not quality. cumulative, all time GitHub
Last commit 2026-08-08 Date of the most recent push to any branch. This is the strongest cheap indicator of whether the project is still maintained. point in time GitHub
Open issues 0 Open issues plus open pull requests, as GitHub counts them together. A high number can mean an active project or an abandoned one. as of fetch GitHub
Latest published version 1.10.0 Latest version string the maintainer published to the registry. as of fetch Model Context Protocol
Registry record last updated 2026-07-12 When the registry record was last updated by its maintainer. point in time Model Context Protocol
License MIT Licence GitHub detected in the repository. Detection can be wrong; the LICENSE file is authoritative. as of fetch GitHub
First listed in the MCP Registry 2026-07-12 Date this server was first published to the official MCP Registry. Not a usage or quality measure. point in time Model Context Protocol
repository status active The repository exists on GitHub and is not archived. This says nothing about how recently it was worked on. as of fetch GitHub
mcp tools declared 12 tools Number of functions the server itself declared when asked to list them. This is what the server offers an agent, not a measure of how well any of them work. as of probe api.decker-ai.com
mcp endpoint status ok The server listed 12 functions when asked. as of probe api.decker-ai.com

Where to get it

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These share tags the maintainers applied themselves, such as binance, crypto, hyperliquid, trading. Common tags like "mcp" or "ai" are ignored for this: agreeing with six hundred other projects is not a similarity.

This is not a recommendation and not a test result. It is a map of what the authors said their work is about.

How the author describes it

Topics the maintainer set on GitHub: ai, binance, crypto, decker, deckerai, harness, hyperliquid, krx-api, machine-learning, openclaw, polymarket-trade-bot, telegram-bot, trading, trading-bot.

This record as data

Every field on this page, with its source and observation date, is in the catalog JSON. Fetch the whole kind at once instead of parsing this HTML.

GET /api/v1/entries/mcp_server.json

Sources

  1. Tools declared by the MCP server at https://api.decker-ai.com/api/v1/mcp — api.decker-ai.com, observed , trust tier 1.
  2. gigshow/decker-ai on GitHub — GitHub, observed , trust tier 3.
  3. Official MCP Registry — Model Context Protocol, observed , trust tier 1.