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feat: add cross-domain analytics — correlation, domain summary, trend detection (109 tools)

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- intel_cross_correlate: finds related signals across all domains for a topic,
  groups by category, shows how events ripple across intelligence streams
- intel_domain_summary: per-category aggregate of stored intelligence with
  data point counts, unique sources, latest/earliest timestamps
- intel_trend_detection: compares recent vs baseline activity rates per
  category, identifies SURGE/ELEVATED/DECLINING/DROP patterns for early warning
- All three leverage accumulated Qdrant vector store data
- 109 tools total across 30+ domains
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Marc Shade
2026-03-08 10:15:53 -04:00
parent 094f37d443
commit 306173c0ec
4 changed files with 400 additions and 3 deletions
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README.md
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@@ -6,7 +6,7 @@
[![Python 3.11+](https://img.shields.io/badge/Python-3.11%2B-green)](https://python.org)
[![License](https://img.shields.io/badge/License-MIT-yellow)](LICENSE)
Real-time global intelligence across **30+ domains** with **106 MCP tools**, a live ops-center dashboard, a CLI, and a **Qdrant vector store** for enterprise-grade semantic search across accumulated intelligence. All data comes from free, public APIs — no paid subscriptions required.
Real-time global intelligence across **30+ domains** with **109 MCP tools**, a live ops-center dashboard, a CLI, and a **Qdrant vector store** for enterprise-grade semantic search across accumulated intelligence. All data comes from free, public APIs — no paid subscriptions required.
Built for AI agents that need world awareness: market conditions, geopolitical risk, military posture, supply chain disruptions, cyber threats, and more — all queryable via the Model Context Protocol. The vector store enables natural language queries like *"military activity near Taiwan"* or *"cyber threats targeting healthcare"* across all historical data.
@@ -54,9 +54,10 @@ Built for AI agents that need world awareness: market conditions, geopolitical r
| **Cross-Domain** | 2 | Alert digest, weekly trends |
| **Vector Search** | 5 | Qdrant semantic search, similarity, timeline, collection |
| **Cross-Domain Analytics** | 3 | Correlation, domain summary, trend detection |
| **Data Collection** | 1 | On-demand collector trigger |
**Total: 106 tools** across 30+ intelligence domains.
**Total: 109 tools** across 30+ intelligence domains.
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@@ -333,6 +334,13 @@ collector.py (daemon) ──┘
| `intel_vector_stats` | Vector store collection statistics |
| `intel_collect` | Trigger an on-demand collection cycle |
### Cross-Domain Analytics (3)
| Tool | Description |
|------|-------------|
| `intel_cross_correlate` | Find correlated signals across all domains for a given topic |
| `intel_domain_summary` | Per-category summary of stored intelligence (counts, sources, recency) |
| `intel_trend_detection` | Detect activity surges/drops by comparing recent vs baseline periods |
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## Vector Store