AletaIndex/aletaindex-fin-narratives

๐Ÿ’ฐ Finance & Fintech๐ŸŸข Verified Active
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๐Ÿ โ˜๏ธ ๐ŸŽ๐ŸชŸ๐Ÿง - Financial narrative intelligence for AI agents. Tracks how financial stories evolve across 109 tickers โ€” clustering news into structured narratives, measuring sentiment momentum, and mapping narrative risk across portfolios. Install via Smithery or uvx narrative-intelligence-mcp.

Quick Install

One-Click IDE Configuration
claude_desktop_config.json
{
  "mcpServers": {
    "aletaindex-aletaindex-fin-narratives": {
      "command": "npx",
      "args": [
        "-y",
        "aletaindex-aletaindex-fin-narratives"
      ]
    }
  }
}
Or

Using an AI coding agent (Claude Code, Cursor, etc.)? Copy a ready-made prompt that tells it to fetch the setup instructions and install this server for you.

Documentation Overview

AletaIndex Narrative Intelligence API

PyPI Python License: MIT Smithery Glama

Give your AI agent a financial narrative brain.

AletaIndex tracks how financial stories evolve across thousands of news sources in real time โ€” clustering articles into structured narratives, measuring sentiment momentum, and mapping narrative risk across portfolios. Available for 109 tickers across all major sectors.

Instead of raw news feeds or simple sentiment scores, your agent gets narrative-level intelligence: what the market is talking about, how strongly, and whether it's shifting.

Dominant Narrative Evolution โ€” TSLA 180-day view showing 5 persistent narrative threads, article volume, and daily return overlay


What Your Agent Can Do

๐Ÿ’ก For best results, paste this at the start of your conversation:

You have access to the Aleta Index MCP, which provides narrative intelligence
derived from institutional news sources.

When analyzing stocks, prioritize the narrative layer: global narratives,
daily topics, sentiment scores, mention counts, sentiment trends, and
behavioral patterns. The narrative layer aggregates signal across hundreds
of sources and contains sufficient information for analysis โ€” avoid reading
individual article bodies unless specifically necessary.
You: "What narratives are driving NVDA right now? Any sentiment shifts?"

Agent: NVDA is currently dominated by two narratives:
  1. "AI Infrastructure Supercycle" โ€” 47 articles, sentiment +0.68, trending up
  2. "Export Control Headwinds" โ€” 23 articles, sentiment -0.41, stable

  Sentiment on "Export Control Headwinds" has improved +0.12 over the past week,
  suggesting the market is pricing in less risk from the latest policy signals.

No prompt engineering required. The agent knows how to query the data automatically.


Three Ways to Integrate

Option A โ€” MCP Server via PyPI (Local install, recommended)

One-line config via uvx. Works with Claude Code, Claude Desktop, Cursor, Windsurf, and any MCP-compatible agent. โ†’ MCP Quickstart

Option B โ€” MCP Directories (Zero install)

One click on Smithery or Glama. Works with Claude, Cursor, Windsurf, and any MCP-compatible agent โ€” no local setup required. โ†’ Add on Smithery ยท Add on Glama

Option C โ€” REST API

Direct HTTP calls. Works with any language or framework. โ†’ API Reference


Pricing

TierTickersHistoryCreditsPrice
Free Trial10 tickers90 days500 (one-time)Free, 7 days
PlusAll 109 tickers180 days2,500/month$99/mo
ScaleAll 109 tickersFull historyCustomCustom โ€” contact us

Free tickers: TSLA NVDA AAPL MSFT AMZN GOOGL META AMD NFLX JPM

โ†’ Get your API key


Quick Example

import requests
from datetime import date, timedelta

API_KEY  = "nk_your_key_here"
BASE_URL = "https://aletaindex-narrative.com"

to_date   = date.today()
from_date = to_date - timedelta(days=6)  # 7-day window (inclusive)

resp = requests.get(
    f"{BASE_URL}/v1/narratives/comprehensive",
    headers={"X-API-Key": API_KEY},
    params={
        "tickers":   "NVDA",
        "from_date": from_date.isoformat(),
        "to_date":   to_date.isoformat(),
    },
)

data = resp.json()
for narrative in data["results"][0]["global_narratives"]:
    sentiment = narrative["sentiment"]
    print(narrative["title"], "-", sentiment["sentiment_label"], f"({sentiment['avg_sentiment']:.2f})")

Example response (truncated):

{
  "results": [
    {
      "ticker": "NVDA",
      "global_narratives": [
        {
          "narrative_id": 142,
          "title": "AI Infrastructure Supercycle",
          "dominance_score": 0.847,
          "is_active": true,
          "daily_topics": [
            {
              "event_date": "2026-05-10",
              "article_count": 14,
              "sentiment": {
                "avg_sentiment": 0.71,
                "sentiment_label": "Positive",
                "trajectory": "Escalating"
              }
            }
          ]
        },
        {
          "narrative_id": 89,
          "title": "Export Control Headwinds",
          "dominance_score": 0.312,
          "is_active": true,
          "daily_topics": [
            {
              "event_date": "2026-05-10",
              "article_count": 6,
              "sentiment": {
                "avg_sentiment": -0.38,
                "sentiment_label": "Negative",
                "trajectory": "Stable"
              }
            }
          ]
        }
      ]
    }
  ]
}

Documentation

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Last checked: 7/28/2026, 10:45:16 AM

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