Trenduel Pulse - Track What's Trending

Politics

Entity ↕

Type ↕

Score ↕

24h Change ↕

Share of Voice ↕

Z-Score ↕

7-Day Trend

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Sports

Entity ↕

Type ↕

Score ↕

24h Change ↕

Share of Voice ↕

Z-Score ↕

7-Day Trend

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Entertainment

Entity ↕

Type ↕

Score ↕

24h Change ↕

Share of Voice ↕

Z-Score ↕

7-Day Trend

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Business

Entity ↕

Type ↕

Score ↕

24h Change ↕

Share of Voice ↕

Z-Score ↕

7-Day Trend

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Pop Culture

Entity ↕

Type ↕

Score ↕

24h Change ↕

Share of Voice ↕

Z-Score ↕

7-Day Trend

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Pipeline Run Audit Log

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Total Runs (7d)

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Successful

0

Failed

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Total API Calls

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API Testing Interface

Select Endpoint

Request

Query Parameters (JSON)

Response

Select an endpoint and click "Send Request"

API Documentation

Overview

The Political Trends Tracking API provides daily-tracked, graphable metrics for political entities including politicians, bills, movements, and ideas. All data is accurate and sourced from real news and social media APIs.

Base URL

https://your-domain.com

Endpoints

GET /entities

List all entities with optional filtering. Returns entity details including optimized thumbnail URLs.

Query Parameters:

active (boolean, optional) - Filter by active status
category (string, optional) - Filter by category (politics, sports, entertainment)

Response Fields:

id - Entity ID
name - Entity name
category - Category (politics, sports, entertainment)
entity_type - Type (politician, team, movie, etc.)
thumbnail_url - URL to 80x80px optimized thumbnail image (null if not available)
image_url - URL to full-size image
description - Entity description

GET /api/thumbnails/{entity_id}

Get optimized 80x80px thumbnail image for an entity. Thumbnails are square, center-cropped JPEGs optimized for fast loading in table views.

Path Parameters:

entity_id (integer, required) - Entity ID

Response:

JPEG image (80x80px, optimized for web)

Cache Headers:

Images are cached for 24 hours (Cache-Control: public, max-age=86400)

Usage in External Apps:

<img src="http://localhost:5000/api/thumbnails/5" alt="Entity" style="border-radius: 8px; width: 40px; height: 40px;">

POST /entities

Create a new political entity.

Request Body:

{
  "name": "Entity Name",
  "entity_type": "politician|bill|movement|idea",
  "aliases": ["Alias 1"],
  "tags": ["tag1"],
  "active": true
}

GET /metrics

Get daily metrics with flexible filtering.

Query Parameters:

entity_id (integer, optional) - Filter by entity ID
entity_type (string, optional) - Filter by entity type
metric (string, optional) - Filter by metric name
from (date, optional) - Start date (YYYY-MM-DD)
to (date, optional) - End date (YYYY-MM-DD)

GET /compare

Compare entities by a specific metric on a given date.

Query Parameters:

entity_type (string, required) - Entity type to compare
metric (string, required) - Metric name
date (date, required) - Date for comparison (YYYY-MM-DD)
limit (integer, optional) - Number of results (default: 10)

GET /sparkline

Get time-series data for charting.

Query Parameters:

entity_id (integer, required) - Entity ID
metric (string, required) - Metric name
days (integer, optional) - Number of days (default: 30)

GET /inbox

Get auto-discovered entity candidates from the inbox queue.

Query Parameters:

None - Returns all inbox candidates sorted by mention count

Response:

Array of candidate entities with mention counts and approval status.

POST /run-pipeline

Manually trigger the daily data ingestion pipeline.

Request Body:

None - No parameters required

Response:

{
  "status": "success",
  "date": "2025-11-04",
  "message": "Pipeline ran successfully for 2025-11-04"
}

Behavior:

Fetches data from NewsAPI and Reddit, normalizes metrics, auto-discovers new entities, and updates the database with today's metrics.

Metric Names

mentions_news - Number of news article mentions
mentions_social - Number of social media mentions
sentiment - Sentiment score (-1 to 1)
share_of_voice - Percentage of total mentions
z_score - Standardized score
delta_prev - Change from previous day
delta_base - Change from baseline

Use with Claude & AI Agents

This API is designed to be easily consumable by AI agents. Key features:

RESTful Design - Standard HTTP methods and JSON responses
Consistent Formatting - All dates in YYYY-MM-DD, all numbers as floats
No Authentication Required - Easy integration for prototyping
Error Messages - Clear, actionable error responses

Code Snippets

Python

import requests

# Get all entities with thumbnails
response = requests.get('http://localhost:5000/entities?category=politics')
entities = response.json()

# Display entity names and thumbnails
for entity in entities[:5]:
    print(f"{entity['name']}: {entity['thumbnail_url']}")

# Get metrics for specific entity
params = {
    'entity_id': 1,
    'metric': 'mentions_news',
    'from': '2025-11-01',
    'to': '2025-11-04'
}
response = requests.get('http://localhost:5000/metrics', params=params)
metrics = response.json()

# Get sparkline data
params = {
    'entity_id': 1,
    'metric': 'mentions_news',
    'days': 30
}
response = requests.get('http://localhost:5000/sparkline', params=params)
sparkline = response.json()

JavaScript / Node.js

// Get all entities
const entities = await fetch('http://localhost:5000/entities')
  .then(r => r.json());

// Get metrics for specific entity
const params = new URLSearchParams({
  entity_id: 1,
  metric: 'mentions_news',
  from: '2025-11-01',
  to: '2025-11-04'
});
const metrics = await fetch(`http://localhost:5000/metrics?${params}`)
  .then(r => r.json());

// Get sparkline data
const sparklineParams = new URLSearchParams({
  entity_id: 1,
  metric: 'mentions_news',
  days: 30
});
const sparkline = await fetch(`http://localhost:5000/sparkline?${sparklineParams}`)
  .then(r => r.json());

cURL

# Get all entities
curl http://localhost:5000/entities

# Get metrics with filters
curl "http://localhost:5000/metrics?entity_id=1&metric=mentions_news&from=2025-11-01&to=2025-11-04"

# Compare entities
curl "http://localhost:5000/compare?entity_type=politician&metric=mentions_news&date=2025-11-04&limit=10"

# Run daily pipeline
curl -X POST http://localhost:5000/run-pipeline

Claude / AI Agent Integration

// MCP Server Implementation (TypeScript)
import { Server } from "@modelcontextprotocol/sdk/server/index.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";

const API_BASE = "http://localhost:5000";

const server = new Server({
  name: "political-trends",
  version: "1.0.0"
}, {
  capabilities: {
    tools: {}
  }
});

// Tool: Get entity metrics
server.setRequestHandler("tools/list", async () => ({
  tools: [{
    name: "get_political_trends",
    description: "Get political entity metrics and trends",
    inputSchema: {
      type: "object",
      properties: {
        entity_id: { type: "number" },
        metric: { 
          type: "string",
          enum: ["mentions_news", "mentions_social", "sentiment"]
        },
        days: { type: "number", default: 30 }
      },
      required: ["entity_id", "metric"]
    }
  },
  {
    name: "compare_entities",
    description: "Compare multiple entities by metric",
    inputSchema: {
      type: "object",
      properties: {
        entity_type: { type: "string" },
        metric: { type: "string" },
        date: { type: "string" },
        limit: { type: "number", default: 10 }
      },
      required: ["entity_type", "metric", "date"]
    }
  }]
}));

server.setRequestHandler("tools/call", async (request) => {
  if (request.params.name === "get_political_trends") {
    const { entity_id, metric, days = 30 } = request.params.arguments;
    const url = `${API_BASE}/sparkline?entity_id=${entity_id}&metric=${metric}&days=${days}`;
    const response = await fetch(url);
    return { content: [{ type: "text", text: JSON.stringify(await response.json()) }] };
  }
  
  if (request.params.name === "compare_entities") {
    const { entity_type, metric, date, limit = 10 } = request.params.arguments;
    const url = `${API_BASE}/compare?entity_type=${entity_type}&metric=${metric}&date=${date}&limit=${limit}`;
    const response = await fetch(url);
    return { content: [{ type: "text", text: JSON.stringify(await response.json()) }] };
  }
});

// Start server
const transport = new StdioServerTransport();
await server.connect(transport);

Politics

Sports

Entertainment

Business

Pop Culture

Pipeline Run Audit Log

0

0

0

0

Pipeline Run Details

API Testing Interface

Select Endpoint

Request

Response

API Documentation

Overview

Base URL

Endpoints

GET /entities

GET /api/thumbnails/{entity_id}

POST /entities

GET /metrics

GET /compare

GET /sparkline

GET /inbox

POST /run-pipeline

Metric Names

Use with Claude & AI Agents

Code Snippets

Python

JavaScript / Node.js

cURL

Claude / AI Agent Integration

📊 Scoring Methodology

🔍 In Plain English

What We Track:

What the Scores Mean:

⚙️ Technical Details

Data Sources:

Metrics Collection:

Analytics Calculations:

Update Schedule:

✅ Data Quality

Entity Details

Official Links

7-Day Trend

Current Scores

Recent News Stories