Finturb Investment Signals

Created By
ai-intellicore2 months 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.
Overview

FinTurb

FinTurb Analytics MCP Server

Institutional-grade risk analytics for AI assistants.

MCP License Website Tools Resources


Overview

FinTurb Analytics is a remote Model Context Protocol (MCP) server that exposes institutional-grade quantitative risk analytics — composite risk regimes, three-tier systemic fragility alerts, Markov regime transition probabilities, GDELT-derived media sentiment across 27+ assets, a global liquidity index with regional decomposition, and a statistical arbitrage scanner covering 550+ securities — as structured tools any MCP-compliant AI assistant can call autonomously during a conversation.

Quick start

Server URL:    https://mcp-mkic.pythonanywhere.com/mcp
Transport:     Streamable HTTP (SSE-compatible)
Auth:          None required — IP-based rate limiting
Free tier:     50 calls / 48 hours
Premium:       https://www.finturb.com/subscribe

No account, no API key, no installation — paste the URL into any MCP-compatible client and start asking questions.

Setup

ClientGuide
Claude.ai (web)docs/setup-claude.md
ChatGPT (Developer Mode)docs/setup-chatgpt.md
Claude Desktop (macOS / Windows)docs/setup-claude-desktop.md
Claude Code (CLI)docs/setup-claude-code.md

Output contract

Every tool response follows the same shape so an AI can reason from the summary line alone, verify numbers in the structured body, and decide how much to trust the response from the provenance flag.

{
  "summary":         "3-way risk 18.4/100 — regime normal (1d). 4-way 27.0/100 …",
  "generation_mode": "deterministic",
  "...": "structured fields",
  "file_modified":   "2026-04-14T03:41:01Z"
}
  • summary — one-line human-readable headline.
  • generation_modedeterministic for pure data reads, synthesized for payloads containing LLM-generated text or multi-pillar synthesis.
  • file_modified — ISO timestamp of the underlying data file so callers can assess freshness at the point of use.

Tool reference

Full machine-readable list in tools.json; detailed descriptions in docs/tool-reference.md.

Composite risk monitor

ToolOne-liner
get_risk_scoreComposite risk score (0–100) with regime, decomposition, and 4-way liquidity-gated extension.
get_risk_historyDaily risk score, regime label, and duration for the last N days.
get_conditional_returnsHistorical return statistics by regime per core asset (5d / 21d horizons).
get_interaction_table2×2×2 conditional returns table across three signal dimensions for a given asset.

Financial turbulence

ToolOne-liner
get_turbulence_scoreDaily and 10-day rolling turbulence percentiles with regime labels.
get_transition_probabilitiesMarkov transition matrices for daily and rolling turbulence states.
get_signal_datesHistorical bearish (Type A) and bullish (Type B) signal dates with outcomes.

Systemic fragility

ToolOne-liner
get_absorption_ratioThree-tier fragility alert system (30d Watch / 60d Warning / 90d Crisis).
get_fragility_loadings30-day fragility history tail — aggregate time series.
get_pc_loadings_historyPer-asset PC1/PC2 eigenvector loadings across 30/60/90-day windows.

Media sentiment

ToolOne-liner
get_media_sentimentPer-asset tone, volume, and composite signal (27+ assets).
get_sentiment_heatmapFull sentiment ranking across every tracked asset.
get_sentiment_alertsOnly assets with
get_geopolitical_toneGoldstein-scale global geopolitical tension indicator.

Global liquidity

ToolOne-liner
get_global_liquidityGLI (0–100) composite with PLI / PSI / XFI sub-indices and cycle phase.
get_liquidity_historyMonthly GLI + sub-indices time series with cycle phase per observation.
get_regional_liquidityPer-region liquidity readings (US, Eurozone, China, Japan, UK).

Statistical arbitrage

ToolOne-liner
get_oversold_opportunitiesOversold candidates ranked by composite opportunity score.
get_overbought_opportunitiesOverbought candidates ranked by composite opportunity score.
get_ticker_metricsFull 16-field quantitative profile for any of 550+ tickers.
get_stat_arb_summaryUniverse-wide oversold/overbought counts plus top 5 each direction.

AI-generated intelligence (synthesized)

ToolOne-liner
get_market_briefingOne-call cross-pillar synthesis.
get_gpt_commentaryGPT-4o narrative commentary on transitions and daily asset moves.
get_signal_strategistDashboard-grade snapshot with 4-way liquidity gate.

Supporting analytics

ToolOne-liner
get_periodic_returnsAnnual returns for 20 asset classes (2018–present).
get_stablecoin_scorecardRAG assessment across 10 dimensions per major stablecoin.

Resources

Compliant clients (Claude Desktop, Claude Code, Cursor) can pin these documents into the conversation context so the model doesn't need to re-issue tool calls.

  • finturb://daily/risk-snapshot — today's composite risk score + 4-way liquidity-gated extension (deterministic)
  • finturb://daily/market-brief — today's cross-pillar market briefing (synthesized)
  • finturb://methodology/overview — static reference covering the eight pillars, data sources, and the output contract

Example conversations

Three worked examples live in examples/:

Rate limits

TierQuotaNotes
Anonymous50 calls / 48 hIP-based, no account required.
PremiumUnlimitedBearer token. Subscribe.
InstitutionalUnlimitedCustom arrangements — contact tk@intellicore.ai.

Data freshness

All FinTurb analytics are refreshed daily on a scheduled pipeline running between 00:05 and 04:05 UTC, drawing from established primary sources — market data, macro statistics, and open-source news datasets. Most signals reflect the previous market close (T+0); a small number carry a one-day publication lag or mixed recency where the underlying macro series are published weekly to quarterly. Every MCP tool response carries a file_modified ISO timestamp so callers can verify freshness at the point of use. Signal methodologies and inputs are proprietary to AI IntelliCore Limited.

About AI IntelliCore

AI IntelliCore Limited is a Cyprus-registered quantitative analytics firm building institutional-grade risk intelligence for AI-native workflows. Learn more at finturb.com and riskregime.com.

Support

License

Proprietary. See LICENSE for terms.


© 2026 AI IntelliCore Limited. FinTurb and the AI IntelliCore logo are trademarks of AI IntelliCore Limited. The Model Context Protocol is a trademark of Anthropic PBC.

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>"
      }
    }
  }
}
Project Info
Created At
2 months ago
Updated At
a month ago
Author Name
ai-intellicore
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