MCP Servers

模型上下文协议服务器、框架、SDK 和模板的综合目录。

Public documentation and metadata for the FinTurb Analytics MCP server — 26 tools for institutional-grade financial risk analytics (risk regimes, systemic fragility, media sentiment, global liquidity, statistical arbitrage).

创建于 4/16/2026
更新于 about 4 hours ago
Repository documentation and setup instructions

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

| Client | Guide | |---|---| | 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

| Tool | One-liner | |---|---| | get_risk_score | Composite risk score (0–100) with regime, decomposition, and 4-way liquidity-gated extension. | | get_risk_history | Daily risk score, regime label, and duration for the last N days. | | get_conditional_returns | Historical return statistics by regime per core asset (5d / 21d horizons). | | get_interaction_table | 2×2×2 conditional returns table across three signal dimensions for a given asset. |

Financial turbulence

| Tool | One-liner | |---|---| | get_turbulence_score | Daily and 10-day rolling turbulence percentiles with regime labels. | | get_transition_probabilities | Markov transition matrices for daily and rolling turbulence states. | | get_signal_dates | Historical bearish (Type A) and bullish (Type B) signal dates with outcomes. |

Systemic fragility

| Tool | One-liner | |---|---| | get_absorption_ratio | Three-tier fragility alert system (30d Watch / 60d Warning / 90d Crisis). | | get_fragility_loadings | 30-day fragility history tail — aggregate time series. | | get_pc_loadings_history | Per-asset PC1/PC2 eigenvector loadings across 30/60/90-day windows. |

Media sentiment

| Tool | One-liner | |---|---| | get_media_sentiment | Per-asset tone, volume, and composite signal (27+ assets). | | get_sentiment_heatmap | Full sentiment ranking across every tracked asset. | | get_sentiment_alerts | Only assets with |z| > 2 — actionable outliers. | | get_geopolitical_tone | Goldstein-scale global geopolitical tension indicator. |

Global liquidity

| Tool | One-liner | |---|---| | get_global_liquidity | GLI (0–100) composite with PLI / PSI / XFI sub-indices and cycle phase. | | get_liquidity_history | Monthly GLI + sub-indices time series with cycle phase per observation. | | get_regional_liquidity | Per-region liquidity readings (US, Eurozone, China, Japan, UK). |

Statistical arbitrage

| Tool | One-liner | |---|---| | get_oversold_opportunities | Oversold candidates ranked by composite opportunity score. | | get_overbought_opportunities | Overbought candidates ranked by composite opportunity score. | | get_ticker_metrics | Full 16-field quantitative profile for any of 550+ tickers. | | get_stat_arb_summary | Universe-wide oversold/overbought counts plus top 5 each direction. |

AI-generated intelligence (synthesized)

| Tool | One-liner | |---|---| | get_market_briefing | One-call cross-pillar synthesis. | | get_gpt_commentary | GPT-4o narrative commentary on transitions and daily asset moves. | | get_signal_strategist | Dashboard-grade snapshot with 4-way liquidity gate. |

Supporting analytics

| Tool | One-liner | |---|---| | get_periodic_returns | Annual returns for 20 asset classes (2018–present). | | get_stablecoin_scorecard | RAG 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

| Tier | Quota | Notes | |---|---|---| | Anonymous | 50 calls / 48 h | IP-based, no account required. | | Premium | Unlimited | Bearer token. Subscribe. | | Institutional | Unlimited | Custom 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.

快速设置
此服务器的安装指南

安装命令 (包未发布)

git clone https://github.com/ai-intellicore/finturb-mcp
手动安装: 请查看 README 获取详细的设置说明和所需的其他依赖项。

Cursor 配置 (mcp.json)

{ "mcpServers": { "ai-intellicore-finturb-mcp": { "command": "git", "args": [ "clone", "https://github.com/ai-intellicore/finturb-mcp" ] } } }