markettrace-agent-feed
MarketTrace agent-feed
Read-only crypto perps microstructure for AI agents — normalized cross-exchange market state with self-declared coverage and freshness on every metric. Facts and normalization, no verdicts: the agent interprets.
Hosted MCP:
https://api.markettrace.ai/mcp(Streamable HTTP, OAuth — no API keys)Official registry:
ai.markettrace/agent-feed
This repo is the front door — connection configs, the interface contract, and a thin stdio bridge. The data pipeline itself (4-venue ingest, archives, normalization) is not open source.
What it serves
9 assets (BTC, ETH, SOL, BNB, XRP, DOGE, HYPE, ZEC, ENA) across Binance, Bybit, OKX, Hyperliquid:
Tool | What it answers |
| One normalized snapshot: funding + its trailing 2-year percentile, OI, volume, CVD, order-book imbalance, liquidations, basis, drivers. "Is ETH positioning stretched?" |
| Current funding ranked against its own trailing 2-year window (0–100) + same-sign streak. |
| Cross-exchange liquidation notional estimates for a window: USD, long/short split. |
| Consolidated cross-exchange candles (5m…1d) with per-candle delta (taker buy − taker sell), for ATR, ranges, CVD and RV math. |
| Measured forward-return history after a stated condition — base rates instead of folklore. "What happened historically after funding above the 90th percentile?" |
| Time series of any numeric state field from the 15-minute archive — the trend view behind the snapshot. |
| Volume-profile levels per UTC day from the consolidated tape: POC, value area high/low, value-area width and its rank, a multi-day composite and naked POCs. "Is price inside yesterday's value area?" |
| Large aggressive orders (fills sharing venue, side and timestamp summed into one trade): per-side totals plus the biggest prints with venue, price and USD size. "Were the whale market orders buying or selling?" |
| Order-book wall events from the 1-minute footprint: absorbed and pulled walls with peak, executed and closing size in USD, plus thin-book minutes. "Were bid walls pulled before this drop?" |
| Stacked footprint imbalances from the consolidated tape: diagonal buy and sell runs per candle (1m…1h) with price band and USD size. "Where did aggressive buyers stack up on BTC this morning?" |
Data: funding rates, open interest, cumulative volume delta (CVD), order-book depth, liquidations, OHLCV candles with per-candle delta, volume-profile levels, large aggressive orders, order-book wall events, stacked footprint imbalances.
Honesty model: every metric carries a coverage entry (venues, window
depth, freshness); thin history answers with disclosed depth instead of
made-up numbers; conditional outcomes go history_silent below the evidence
floor; every response self-declares its age. Reports history, not predictions.
Related MCP server: crypto-quant-signal-mcp
Connect
Claude (web/desktop): Settings → Connectors → Add custom connector →
https://api.markettrace.ai/mcp → authorize (email magic link).
Every client signs in the same way: it opens a browser, you enter your email, and a sign-in link arrives. Open it on the same device and in the same browser where you started.
Claude Code (adding the server does not sign you in, so run both):
claude mcp add --transport http markettrace https://api.markettrace.ai/mcp
claude mcp login markettraceCodex:
codex mcp add markettrace --url https://api.markettrace.ai/mcp
codex mcp login markettraceCursor: add this to ~/.cursor/mcp.json (or use Add to Cursor on
https://markettrace.ai/agents) and sign in when Cursor asks:
{
"mcpServers": {
"markettrace": { "url": "https://api.markettrace.ai/mcp" }
}
}Stdio-only clients (via the standard OAuth-capable bridge):
npx -y mcp-remote https://api.markettrace.ai/mcpMore client configs in examples/mcp-configs.md.
Local stdio bridge (this repo)
mcp_server.py is a zero-dependency stdio bridge: it starts
and answers introspection (initialize, tools/list) with no credentials —
the bundled tools.json is a snapshot of the hosted server's
own contract. Tool calls are proxied to the hosted endpoint when
MARKETTRACE_BEARER is set; without it they return a pointer to the hosted
OAuth endpoint instead of data. It holds no methodology — just a client.
Refresh the contract: tools.json is a {version, generated_at, tools} snapshot of the live server's tools/list — regenerate it by capturing that response and stamping the current contract version (mirrors feed.version in get_market_state).
python3 mcp_server.py # Python 3.9+, no dependenciesOr with Docker:
docker build -t markettrace-bridge . && docker run -i markettrace-bridgeThings to ask
"What's the market state for BTC — is positioning stretched?"
"What happened historically after funding above the 90th percentile?"
"How did open interest build over the last 3 days?"
"How much got liquidated on ETH in the last hour — longs or shorts?"
"Where are the key volume levels on BTC — any untested POCs nearby?"
"Did a large resting order get absorbed on SOL in the last hour?"
Terms
Informational market data only — not financial advice. Privacy Policy · Terms of Service · Contact: support@markettrace.ai
The bridge in this repo is MIT-licensed (LICENSE); the hosted service is governed by the Terms above.
This server cannot be deployed
Maintenance
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