8 days ago
We design and operate proprietary signal systems that turn noisy market, macro, and media data into structured, calibrated intelligence — exposed through web dashboards, a Signals API, and a public MCP server any AI assistant can reason over directly. The eight pillars
Every product above reads from the same nightly signal pipeline (00:05–04:05 UTC) organised into eight analytic pillars:
Composite risk monitor — 0–100 regime score with AR / turbulence / GDELT decomposition, extended by a 4-way liquidity gate.
Financial turbulence — cross-asset covariance regime with Markov transition probabilities.
Systemic fragility — three-tier Absorption Ratio alerts plus per-asset PC1 / PC2 eigenvector history.
Media sentiment — GDELT-derived tone, volume, and outliers across 27+ assets plus a global geopolitical tension gauge.
Global liquidity — GLI composite with policy / private-sector / cross-border sub-indices and regional breakdown.
Statistical arbitrage — 550+ security scanner for oversold and overbought mean-reversion candidates.
AI-generated intelligence — cross-pillar briefings and narrative commentary, clearly flagged as synthesized vs deterministic.
Supporting analytics — multi-year asset-class returns and a RAG stablecoin scorecard.
Server Config
{
"mcpServers": {
"finturb-analytics": {
"command": "npx",
"args": [
"-y",
"mcp-remote",
"https://mcp-mkic.pythonanywhere.com/mcp",
"--header",
"Authorization: Bearer ${FINTURB_TOKEN}"
],
"env": {
"FINTURB_TOKEN": "<YOUR_TOKEN>"
}
}
}
}