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marc-shade

Threat Intelligence MCP Server

by marc-shade

Phoenix Intelligence Dashboard

World Intelligence MCP Server

MCP Python 3.11+ License

Echtzeit-Intelligenz für die ganze Welt über 30+ Domänen mit 120 MCP-Tools, einem Live-Ops-Center-Dashboard, einer CLI und einem Qdrant-Vektorstore für unternehmensweite semantische Suche über gesammelte Intelligenzdaten. Alle Daten stammen aus kostenlosen, öffentlichen APIs: keine kostenpflichtigen Abonnements erforderlich.

Entwickelt für KI-Agenten, die Weltwissen benötigen: Marktbedingungen, geopolitische Risiken, militärische Lage, Störungen in Lieferketten, Cyber-Bedrohungen und mehr – alles abfragbar über das Model Context Protocol. Der Vektorstore ermöglicht natürlichsprachliche Abfragen wie "militärische Aktivität nahe Taiwan" oder "Cyber-Bedrohungen gegen das Gesundheitswesen" über alle historischen Daten.


Was Sie erhalten

Domäne

Tools

Datenquellen

Finanzmärkte

7

Yahoo Finance, CoinGecko, Alternative.me, Mempool

Forex & Währungen

3

ECB/Frankfurter (8 Hauptwährungspaare, Zeitreihen, Kreuzkurse)

Anleihen & Renditen

2

FRED, Yahoo Finance (Zinskurve, Anleihen-ETFs, Spread-Analyse)

Unternehmensgewinne

2

Yahoo Finance (Mega-Cap-Kalender, Überraschungshistorie)

SEC-Einreichungen

3

SEC EDGAR (Volltextsuche, Unternehmenseinreichungen, 8-K-Wesentliche Ereignisse)

Unternehmensanreicherung

1

Yahoo Finance + GDELT + SEC + GitHub (zusammengesetztes Profil)

Makro-Komposit

1

Gewichtetes 6-Signal-Markturteil (Fear&Greed, VIX, Sektoren, DXY, BTC, Renditen)

Wirtschaftsindikatoren

6

AAA-Kraftstoffpreise, EIA-Energie, FRED-Makro, Weltbank

Zentralbanken

1

15 Zentralbank-Leitzinsen

BTC-Technik

1

SMA 50/200, Golden/Death Cross, Mayer-Multiple

Naturkatastrophen

2

USGS-Erdbeben, NASA FIRMS-Waldbrände

Umwelt

2

NASA EONET, GDACS-Katastrophenwarnungen

Klima

1

Open-Meteo-Temperatur-/Niederschlagsanomalien

Konflikt & Sicherheit

4

ACLED-Ereignisse, UCDP, Unruheerkennung, humanitäre Daten

Militär & Verteidigung

6

adsb.lol, OpenSky, hexdb.io, Anstiegserkennung, Theater-Posture, Flugzeug-Batch

Infrastruktur

4

Cloudflare Radar, Unterseekabel, Kaskadenanalyse, Cloud-Status

Maritim

2

NGA-Schifffahrtswarnungen, Schiffs-Snapshots

Luftfahrt

2

FAA-Flughafenverspätungen, Inlandsflug-Snapshot

Nachrichten & Medien

3

119 RSS-Feeds (4-stufig), GDELT, Trend-Keywords

Intelligenzanalyse

8

Signal-Konvergenz, Brennpunkte, Instabilitätsindex, Risikowerte, Eskalation

NLP-Intelligenz

4

Entitätsextraktion, Ereignisklassifikation, Nachrichten-Clustering, Keyword-Spitzen

Strategische Synthese

4

Strategische Lage, Welt-Briefing, Flottenbericht, Bevölkerungs-Exposition

Geodaten

11

Militärstützpunkte, Häfen, Pipelines, Nuklearanlagen, Kabel, Rechenzentren, Raumhäfen, Mineralien, Börsen, Handelsrouten, Cloud-Regionen

KI & Technologie

4

arXiv-Papiere, HuggingFace-Modelle, Hacker News, GitHub-Trends

Cyber-Bedrohungen

1

URLhaus, Feodotracker, CISA KEV, SANS

Gesundheit

1

WHO DON, ProMED, CIDRAP-Krankheitsausbrüche

Weltraumwetter

1

NOAA SWPC (Kp-Index, Sonneneruptionen, Warnungen)

Soziales & Sanktionen

3

Reddit-Velocity, OFAC-SDN-Liste, Überwachung von Atomtestgeländen

Länder-Intelligenz

3

Länder-Briefing, Länderaktien, Finanzzentren

Prognosemärkte

1

Polymarket-Ereigniskontrakte

Wahlen

1

Globaler Wahlkalender mit Risikobewertung

Vertreibung

1

UNHCR-Flüchtlings-/Binnenvertriebenendaten

Schifffahrt

1

Trockenschüttgut-Schifffahrtsstressindex

Regierung

1

USAspending.gov-Bundesaufträge

Verkehr

2

Straßenverkehrsfluss, Echtzeit-Vorfälle

Domänenübergreifende Warnungen

2

Warnungs-Digest, Wochentrends

Überwachung

2

Webcams, Serverzustand/Status

Vektorsuche

5

Qdrant-semantische Suche, Ähnlichkeit, Zeitachse, Statistiken

Domänenübergreifende Analytik

3

Korrelation, Domänen-Zusammenfassung, Trend-Erkennung

Berichte

1

PDF/HTML-Mehrdomänen-Intelligenzberichte

Täglicher Digest

1

Zitierter Markdown-Morgenbrief: Top-Ereignisse, Schlagzeilen, Trends und Zeitachse

AOI-Geofences

5

Benutzerdefinierte Interessensgebiete: definieren/auflisten/löschen, ein zitierter Mehrdomänen-Brief und Hotspot-Eskalationsbewertung für das eigene Gebiet

Lagebrief

1

Zitierter Lagebewusstseins-Brief über MCP: begrenzte serverseitige Übersicht, synthetisiert über lokales Ollama, mit mechanisch zitiertem Fallback

Gesamt: 120 Tools in über 30 Intelligenz-Domänen.


Related MCP server: MCP Threat Intel Server

Schnellstart

Installation

git clone https://github.com/marc-shade/world-intel-mcp.git
cd world-intel-mcp
pip install -e .

# Optional extras
pip install -e ".[dashboard]"  # Live ops-center dashboard
pip install -e ".[vector]"     # Qdrant vector store + FastEmbed
pip install -e ".[dev]"        # pytest, respx, coverage

Als MCP-Server ausführen

world-intel-mcp  # stdio mode for Claude Code, Cursor, etc.

Claude-Code-Konfiguration

Zu ~/.claude.json hinzufügen:

{
  "mcpServers": {
    "world-intel-mcp": {
      "command": "world-intel-mcp"
    }
  }
}

Dashboard

intel-dashboard              # http://localhost:8501
intel-dashboard --port 9000  # custom port

PDF/HTML-Berichte

pip install -e ".[pdf]"      # requires: brew install pango (macOS)
intel report                 # full PDF report → ~/.cache/world-intel-mcp/
intel report --format html   # HTML (no native deps needed)
intel report -o brief.pdf    # custom output path
intel report -s markets,cyber,earthquakes  # select sections

Kartenbasiertes Ops-Center: Leaflet-Karte mit umschaltbaren Ebenen (Erdbeben, Militär, Konflikte, Brände, Konvergenz, Nuklear, Infrastruktur), 47 Live-SSE-Feeds, HUD-Leiste, glasmorphische Panels, Circuit-Breaker-Zustand pro Quelle.

CLI

intel markets              # stock indices
intel earthquakes --min-mag 5.0
intel status               # cache + circuit breaker health

Architektur

server.py     (MCP stdio) ─┐                                               ┌─ VectorStore (Qdrant)
cli.py        (Click CLI)  ├─> sources/*.py ─> Fetcher ─> CircuitBreaker ─┤
dashboard.py  (SSE)        │    analysis/*.py                              └─ Cache (SQLite)
collector.py  (daemon)    ─┘
  • Fetcher: Zentralisierter asynchroner HTTP-Client (httpx). Wiederholungsversuche, Ratenbegrenzung pro Quelle, Fallback bei veralteten Daten. Speichert Ergebnisse bei neuen Abrufen automatisch im Vektorstore.

  • CircuitBreaker: Verfolgung pro Quelle. 3 aufeinanderfolgende Fehlschläge lösen für 5 Minuten aus. Jeder RSS-Feed erhält seinen eigenen Breaker.

  • Cache: SQLite-WAL-Modus-TTL-Cache. get() liefert Live-Daten, get_stale() liefert abgelaufene Daten als Fallback.

  • VectorStore: Qdrant + FastEmbed (BAAI/bge-small-en-v1.5, 384-dim). Asynchrone Hintergrund-Warteschlange für nicht blockierende Speicherung. Ermöglicht semantische Suche über alle gesammelten Intelligenzdaten.

  • Collector: Eigenständiger Daemon, der alle 46 Quellen parallel abruft und den Vektorstore befüllt. Einmalig oder als Daemon ausführbar (Standard: 5-Minuten-Intervall).

  • Quellen (sources/*.py): 30+ Module, jedes exportiert async def fetch_*(fetcher, **kwargs) -> dict.

  • Analyse (analysis/*.py): Domänenübergreifende Synthese – Signalaggregation, Instabilitätsindexierung, NLP, Unternehmensanreicherung, Makro-Komposit.

  • Konfiguration (config/*.py): Kuratierte Datensätze – 22 Hotspots, 70+ Stützpunkte, 40 Häfen, 24 Pipelines, 24 Nuklearanlagen, 34 Kabel, 48 Rechenzentren, 27 Raumhäfen, 82 Börsen.


MCP-Tools-Referenz

Finanzmärkte (7)

Tool

Beschreibung

intel_market_quotes

Aktienindexkurse (S&P 500, Dow, Nasdaq, FTSE, Nikkei)

intel_crypto_quotes

Top-Kryptopreise und Marktkapitalisierungen von CoinGecko

intel_stablecoin_status

Stablecoin-Peg-Gesundheit (USDT, USDC, DAI, FDUSD)

intel_etf_flows

Bitcoin-Spot-ETF-Preise und -Volumina

intel_sector_heatmap

Performance der US-Aktiensektoren (11 SPDR-ETFs)

intel_macro_signals

7 Makroindikatoren (Fear & Greed, VIX, DXY, Gold, 10Y, BTC)

intel_commodity_quotes

Rohstoff-Futures (Gold, Silber, Rohöl, Erdgas, Getreide)

Forex & Währungen (3)

Tool

Beschreibung

intel_forex_rates

Aktuelle FX-Kurse von der EZB. Nach Basis-/Zielwährungen filtern

intel_forex_timeseries

Historische FX-Kurse mit Trendanalyse (konfigurierbare Tage)

intel_major_crosses

Alle 8 Hauptpaare + Kreuzkurse + DXY-Stellvertreter

Anleihen & Renditen (2)

Tool

Beschreibung

intel_yield_curve

US-Treasury-Zinskurve (2Y-30Y), 2s10s/3m10y-Spreads, Inversionsflagge

intel_bond_indices

Anleihen-ETFs: AGG, TLT, HYG, LQD, TIP mit Kurs/Änderung

Gewinne (2)

Tool

Beschreibung

intel_earnings_calendar

Anstehende Gewinne für 20 Mega-Cap-Aktien mit EPS-Schätzungen

intel_earnings_surprise

Historische Gewinnüberraschungen (tatsächlich vs. Schätzung, Trend)

SEC-Einreichungen (3)

Tool

Beschreibung

intel_sec_filings

Volltextsuche über alle EDGAR-Einreichungen

intel_company_filings

Unternehmenseinreichungen nach Ticker (10-K, 10-Q, 8-K) mit CIK-Auflösung

intel_recent_8k

Aktuelle 8-K-wesentliche Ereignisse (M&A, Führungswechsel, Gewinne)

Unternehmensanreicherung (1)

Tool

Beschreibung

intel_company_profile

Zusammengesetztes Profil: Aktienkurs + Finanzdaten + Nachrichten + SEC + GitHub

Makro-Verbund (1)

Tool

Beschreibung

intel_macro_composite

Gewichteter Markt-Score (0-100) mit Urteil: RISK_ON bis STRONG_CAUTION

Wirtschaft (6)

Tool

Beschreibung

intel_gas_prices

Tägliche US-Benzin-, Diesel- und E85-Preise von AAA

intel_residential_natgas

US-Erdgaspreise für Privathaushalte von der EIA

intel_electricity_rates

US-Stromtarife nach Sektor/Bundesstaat von der EIA

intel_energy_prices

Brent/WTI-Rohöl und Erdgas von der EIA

intel_fred_series

FRED-Wirtschaftsdaten (BIP, VPI, Arbeitslosigkeit, Zinsen)

intel_world_bank_indicators

Entwicklungsindikatoren der Weltbank nach Ländern

Zentralbanken (1)

Tool

Beschreibung

intel_central_bank_rates

Leitzinsen für 15 große Zentralbanken

BTC-Technik (1)

Tool

Beschreibung

intel_btc_technicals

Bitcoin SMA 50/200, Golden/Death Cross, Mayer-Multiple

Naturkatastrophen (2)

Tool

Beschreibung

intel_earthquakes

USGS-Erdbeben (konfigurierbare Magnitude/Zeit/Limit)

intel_wildfires

NASA-FIRMS-Satellitenfeuer-Hotspots (9 globale Regionen)

Umwelt (2)

Tool

Beschreibung

intel_environmental_events

NASA-EONET-Naturereignisse

intel_disaster_alerts

GDACS-Katastrophenwarnungen mit Schweregradbewertung

Konflikt & Sicherheit (4)

Tool

Beschreibung

intel_acled_events

ACLED-Bewaffnete-Konflikt-Ereignisse

intel_ucdp_events

Ereignisse des Uppsala Conflict Data Program

intel_unrest_events

Soziale Unruhen mit Haversine-Deduplizierung

intel_humanitarian_summary

HDX-Datensätze zu humanitären Krisen

Militär & Verteidigung (6)

Tool

Beschreibung

intel_military_flights

Militärflugzeuge über adsb.lol (OpenSky-Fallback)

intel_theater_posture

Aktivität in 5 Einsatzgebieten (EU, Indopazifik, Naher Osten, Arktis, Korea)

intel_aircraft_details

Flugzeugsuche nach ICAO24-Hex (hexdb.io)

intel_aircraft_batch

Stapel-Flugzeugsuche (mehrere Hex-Codes)

intel_military_surge

Erkennung von Anomalien bei Konzentration ausländischer Flugzeuge

intel_usni_fleet

USNI-News-Tracker für Marineflotten

Infrastruktur (4)

Tool

Beschreibung

intel_internet_outages

Cloudflare-Radar-Internetstörungen

intel_cable_health

Zustand der Unterseekabel-Korridore

intel_cascade_analysis

Kaskadensimulation der Infrastruktur

intel_service_status

Cloud-Plattform-Status (AWS, Azure, GCP, Cloudflare, GitHub)

Schifffahrt (2)

Tool

Beschreibung

intel_nav_warnings

NGA-Seenavigationswarnungen

intel_vessel_snapshot

Marineaktivität an 9 strategischen Wasserstraßen

Geodaten-Datensätze (10)

Tool

Beschreibung

intel_military_bases

70 Militärstützpunkte von 9 Betreibern

intel_strategic_ports

40 strategische Häfen in 6 Typen

intel_pipelines

24 Öl-/Gas-/Wasserstoffpipelines

intel_nuclear_facilities

24 Kernkraft-/Anreicherungs-/Forschungseinrichtungen

intel_undersea_cables

34 Unterseekommunikationskabel

intel_ai_datacenters

48 KI-/HPC-Rechenzentren weltweit

intel_spaceports

27 globale Weltraumbahnhöfe

intel_critical_minerals

27 strategische Mineralvorkommen

intel_stock_exchanges

82 Börsen weltweit

intel_trade_routes

Wichtige Handelsrouten und Engpässe

Nachrichten & Medien (3)

Tool

Beschreibung

intel_news_feed

119 globale RSS-Feeds mit 4-stufigem Quellenranking

intel_trending_keywords

Trendbegriffe mit Spike-Erkennung

intel_gdelt_search

GDELT-2.0-Weltnachrichtensuche

Intelligence-Analyse (8)

Tool

Beschreibung

intel_signal_convergence

Geografische Konvergenz von Multidomänen-Signalen

intel_focal_points

Erkennung von Brennpunkten bei mehreren Signalen

intel_signal_summary

Signalaggregation auf Länderebene

intel_temporal_anomalies

Abweichungen der Aktivität von Basiswerten

intel_instability_index

Länder-Instabilitätsindex v2 (0-100)

intel_risk_scores

ACLED-basierte Konfliktrisikobewertung

intel_hotspot_escalation

Eskalationswerte für 22 Intel-Hotspots

intel_country_dossier

Umfassendes Länder-Intelligence-Dossier

NLP-Intelligence (4)

Tool

Beschreibung

intel_extract_entities

Extraktion benannter Entitäten (Länder, Führungspersönlichkeiten, Organisationen, CVEs, APTs)

intel_classify_event

Ereignisklassifizierung in 14 Bedrohungskategorien

intel_news_clusters

Themen-Clustering nach Jaccard-Ähnlichkeit

intel_keyword_spikes

Keyword-Spike-Erkennung mit dem Welford-Algorithmus

Strategische Synthese (4)

Tool

Beschreibung

intel_strategic_posture

Zusammengesetztes globales Risiko aus 9 gewichteten Domänen

intel_world_brief

Strukturierte tägliche Intelligence-Zusammenfassung

intel_fleet_report

Bericht über Marineflottenaktivitäten mit Bereitschaftsbewertung

intel_population_exposure

Bevölkerung in Gefahr in der Nähe aktiver Ereignisse (Datensatz mit 105 Städten)

Klima (1)

Tool

Beschreibung

intel_climate_anomalies

Open-Meteo-Temperatur-/Niederschlagsanomalien

Prognosemärkte (1)

Tool

Beschreibung

intel_prediction_markets

Polymarket-Prognosekontrakte

Wahlen (1)

Tool

Beschreibung

intel_election_calendar

Globaler Wahlkalender mit Risikobewertung

Vertreibung (1)

Tool

Beschreibung

intel_displacement_summary

UNHCR-Flüchtlings-/Binnenvertriebenen-Statistiken

Luftfahrt (2)

Tool

Beschreibung

intel_airport_delays

FAA-Flughafenverspätungsstatus

intel_aviation_domestic

Globaler Luftverkehrs-Schnappschuss von OpenSky

Cyber-Bedrohungen (1)

Tool

Beschreibung

intel_cyber_threats

Aggregierte Cyber-Intelligence (URLhaus, CISA KEV, SANS)

Weltraumwetter (1)

Tool

Beschreibung

intel_space_weather

Sonnenaktivität (Kp-Index, Röntgenfluss, SWPC-Warnungen)

KI & Technologie (4)

Tool

Beschreibung

intel_ai_releases

arXiv-KI-Papiere, HuggingFace-Modelle

intel_hacker_news

Hacker News Top-Storys

intel_trending_repos

GitHub-Trending-Repositories

intel_arxiv_papers

arXiv-Papiersuche

Gesundheit (1)

Tool

Beschreibung

intel_disease_outbreaks

WHO DON, ProMED, CIDRAP-Ausbrüche

Soziales & Sanktionen (3)

Tool

Beschreibung

intel_social_signals

Geschwindigkeit geopolitischer Diskussionen auf Reddit

intel_sanctions_search

Suche in der OFAC-SDN-Liste

intel_nuclear_monitor

Seismische Überwachung in der Nähe von Atomtestgeländen

Schifffahrt & Handel (1)

Tool

Beschreibung

intel_shipping_index

Trockenmassengut-Schifffahrtsstressindex

Regierung (1)

Tool

Beschreibung

intel_usa_spending

USAspending.gov-Bundesverträge

Länderinformationen (3)

Tool

Beschreibung

intel_country_brief

Kurze Länderlageübersicht

intel_country_stocks

Börsen und Listings nach Ländern

intel_financial_centers

Ranking globaler Finanzzentren

Erweiterte Geodaten (1)

Tool

Beschreibung

intel_cloud_regions

Cloud-Anbieterregionen weltweit

Verkehr (2)

Tool

Beschreibung

intel_traffic_flow

Straßenverkehrsflussdaten

intel_traffic_incidents

Echtzeit-Verkehrsvorfälle

Domänenübergreifende Warnungen (2)

Tool

Beschreibung

intel_alert_digest

Zusammenfassung domänenübergreifender Warnungen

intel_weekly_trends

Wöchentliche Trendanalyse

Überwachung (2)

Tool

Beschreibung

intel_webcams

Öffentliche Webcam-Standorte und Live-Vorschauen

intel_status

Serverzustand, Cache-Statistiken, Circuit-Breaker-Status

Vektorsuche (5)

Tool

Beschreibung

intel_semantic_search

Suche in natürlicher Sprache über alle gesammelten Informationen

intel_similar_events

Ähnliche Ereignisse zu einem bestimmten Datenpunkt finden

intel_timeline

Chronologische Ansicht der Informationen für eine Domäne/Kategorie

intel_vector_stats

Statistiken zur Vektor-Store-Sammlung

intel_collect

Einen bedarfsgesteuerten Sammelzyklus auslösen

Domänenübergreifende Analytik (3)

Tool

Beschreibung

intel_cross_correlate

Korrelierte Signale über alle Domänen für ein bestimmtes Thema finden

intel_domain_summary

Zusammenfassung der gespeicherten Informationen pro Kategorie (Anzahl, Quellen, Aktualität)

intel_trend_detection

Aktivitätsspitzen/-abfälle erkennen durch Vergleich aktueller mit Basisperioden

Berichte (1)

Tool

Beschreibung

intel_generate_report

Erzeugt einen PDF- oder HTML-Intelligenzbericht, der 18 Domänen parallel abdeckt

AOI-Geofences (5)

Tool

Beschreibung

intel_aoi_define

Definiert einen benannten Interessensbereich: Punkt + Radius in km (1-2000)

intel_aoi_list

Listet alle benutzerdefinierten AOIs auf

intel_aoi_delete

Löscht einen benutzerdefinierten AOI nach Namen

intel_aoi_brief

Zitierter Kurzbericht für einen AOI: Erdbeben, Militärflüge, Waldbrände, Konfliktereignisse, Luftfahrt, nahe Infrastruktur und Nachrichtenerwähnungen, alle auf den Radius des AOI gefiltert

intel_aoi_escalation

Hotspot-Eskalationsbewertung (gleiche Engine wie die 22 integrierten Hotspots), angewendet auf einen Benutzer-AOI

Situationsbericht (1)

Tool

Beschreibung

intel_situation_brief

Zitierter Lagebewusstseinsbericht, auf Abruf über MCP generiert: eine begrenzte serverseitige Übersicht (Erdbeben, Militärflüge, ACLED-Konfliktereignisse, Waldbrände, Cyber-Bedrohungen, Krankheitsausbrüche, Nachrichten, Weltraumwetter, strategische Haltung, Warnungsübersicht), synthetisiert über lokales Ollama oder einen mechanisch zitierten Fallback, wenn Ollama nicht erreichbar ist


Beobachten Sie Ihr eigenes Gebiet (Geofences/AOIs)

Statische Infrastrukturergebnisse (Stützpunkte, Häfen, Nuklearanlagen, Kabel, Rechenzentren, Raumhäfen) stützen sich auf die kuratierten strategischen Datensätze dieses Repos, die global und bewusst spärlich sind, nicht auf erschöpfende lokale Register. Ein ruhiger AOI-Bericht bedeutet, dass nichts aus diesen kuratierten Sätzen in Reichweite ist, nicht dass Ihr Gebiet keine Infrastruktur hat.

28 der 120 Tools akzeptieren einen geografischen Parameter, aber vor der AOI-Familie akzeptierte nur intel_signal_convergence einen echten Punkt-plus-Radius, intel_military_flights nahm eine Bbox, und die Hotspot-Eskalationsbewertung war auf die 22 fest codierten INTEL_HOTSPOTS beschränkt. Die intel_aoi_*-Tools ermöglichen es Ihnen, Ihr eigenes Gebiet zu benennen (eine Stadt, eine Grenzregion, eine Einrichtung) und dieselbe zitierte, domänenübergreifende Behandlung zu erhalten.

Definieren Sie einen AOI einmal, und erstellen Sie dann auf Abruf einen Bericht und eine Bewertung:

intel_aoi_define(name="Pittsburgh", lat=40.4406, lon=-79.9959, radius_km=50)
intel_aoi_brief(name="Pittsburgh")
intel_aoi_escalation(name="Pittsburgh")

intel_aoi_brief filtert jede geofähige Domäne auf den 50-km-Radius um Pittsburgh: Erdbeben, Militärflüge (Bbox aus dem Radius abgeleitet), Waldbrände (regionbezogen, da NASA FIRMS keine Punkt+Radius-Abfrage hat), ACLED-Konfliktereignisse, eine Stichprobe des nahen Luftverkehrs, nahe statische Infrastruktur (Militärstützpunkte, Häfen, Pipelines, Nuklearanlagen, Unterseekabel, Rechenzentren, Raumhäfen) mit Entfernungen in km und Nachrichtenschlagzeilen, die "Pittsburgh" erwähnen. Jedes Element in der Antwort trägt eine [n]-Zitation in eine nummerierte sources-Liste, und data_gaps nennt jede Domäne, die nicht auf den AOI eingegrenzt werden konnte (z. B. Waldbrände, wenn der AOI außerhalb der Abdeckungsregionen von NASA FIRMS liegt, oder Konfliktereignisse, wenn ACLED-Anmeldeinformationen nicht konfiguriert sind), anstatt sie stillschweigend wegzulassen.

intel_aoi_escalation verwendet dieselbe Basis-/Militär-/Konflikt-/soziale Unruhen-Bewertungsengine, die intel_hotspot_escalation für die 22 integrierten Hotspots antreibt, jedoch auf den eigenen Radius Ihres AOI beschränkt statt auf ein festes 2-Grad-Fenster.

AOIs werden in einer eigenen Tabelle in derselben SQLite-Cache-Datenbank gespeichert, die der Server bereits verwendet (standardmäßig ~/.cache/world-intel-mcp/cache.db oder $WORLD_INTEL_CACHE_DB), sodass ein geplanter Agent jedes benannte Gebiet über Neustarts hinweg mit intel_aoi_list / intel_aoi_delete überwachen und verwalten kann.


Vektor-Store

Der optionale Qdrant-Vektor-Store sammelt im Laufe der Zeit Informationen für die semantische Abfrage. Alle über den Fetcher abgerufenen Daten werden automatisch eingebettet und gespeichert.

Einrichtung

# Install Qdrant (Docker)
docker run -p 6333:6333 qdrant/qdrant

# Install vector dependencies
pip install -e ".[vector]"

# Run the collector daemon (populates vector store 24/7)
intel-collector --daemon              # every 5 minutes
intel-collector --daemon --interval 120  # every 2 minutes
intel-collector --sources markets,cyber  # specific domains only
intel-collector                        # single collection cycle

Als macOS-launchd-Dienst ausführen

scripts/collector-daemon.sh verwaltet den Collector als launchd-Agent, sodass er Neustarts übersteht. Es füllt com.agentic.intel-collector.plist.template mit dem eigenen Pfad dieses Checkouts aus (aufgelöst aus dem eigenen Speicherort des Skripts, sodass es aus jedem Klon funktioniert) und installiert das Ergebnis in ~/Library/LaunchAgents/.

scripts/collector-daemon.sh start    # install + load the launchd job
scripts/collector-daemon.sh status   # check state and log info
scripts/collector-daemon.sh logs     # tail stdout (logs err for stderr)
scripts/collector-daemon.sh stop     # unload the launchd job
scripts/collector-daemon.sh restart
scripts/collector-daemon.sh render   # print the filled-in plist without installing it

Beispiele für die semantische Suche

Sobald Daten gesammelt wurden, können KI-Agenten domänenübergreifend abfragen:

  • "militärische Aktivität in der Nähe der Taiwanstraße" — findet Militärflüge, Marinewarnungen, Daten zur Lage im Einsatzgebiet

  • "Cyber-Bedrohungen gegen das Gesundheitswesen" — findet URLhaus-, CISA-KEV-Einträge im Zusammenhang mit dem Gesundheitswesen

  • "Wirtschaftsindikatoren, die auf eine Rezession hindeuten" — findet Zinskurveninversionen, Makrosignale, FRED-Daten

Der Vektor-Store verwendet FastEmbed (ONNX-basiert, BAAI/bge-small-en-v1.5) für Einbettungen — keine GPU erforderlich, ~3 Sekunden Kaltstart.


Umgebungsvariablen

Variable

Erforderlich

Beschreibung

ACLED_ACCESS_TOKEN

Nein

ACLED-Konfliktereignisse

NASA_FIRMS_API_KEY

Nein

Satelliten-Waldbranddaten

EIA_API_KEY

Nein

Energiepreisdaten

CLOUDFLARE_API_TOKEN

Nein

Internetausfalldaten

FRED_API_KEY

Nein

Makroökonomische Daten (auch für Zinskurve verwendet)

OPENSKY_CLIENT_ID

Nein

Fallback für Militärflüge

OPENSKY_CLIENT_SECRET

Nein

Fallback für Militärflüge

OLLAMA_API_URL

Nein

Ollama-Server für KI-generierte Berichte (Standard: http://localhost:11434)

OLLAMA_MODEL

Nein

Ollama-Modell für KI-generierte Berichte (Standard: llama3.2)

WORLD_INTEL_LOG_LEVEL

Nein

Protokollierungsgrad (Standard: INFO)

Alles andere verwendet kostenlose, nicht authentifizierte öffentliche APIs.


Entwicklung

pip install -e ".[dev]"
pytest                       # 251 tests (269 total, 18 live-network smoke tests deselected by default)
pytest --cov=world_intel_mcp # with coverage
pytest tests/test_forex.py -v # single module

Hinzufügen einer neuen Quelle

  1. Erstellen Sie sources/your_source.py mit async def fetch_your_data(fetcher: Fetcher, **kwargs) -> dict

  2. Verwenden Sie fetcher.get_json(url, source="your-source", cache_key=..., cache_ttl=300) — automatisches Caching, Wiederholungen, Circuit Breaking, Rate Limiting

  3. In server.py: fügen Sie Tool(...) zu TOOLS hinzu, fügen Sie case zu _dispatch() hinzu (verwenden Sie Inline-Import)

  4. Fügen Sie Tests mit respx hinzu, um HTTP zu mocken (siehe tests/test_forex.py für das Muster)

  5. Optional zu dashboard/app.py (SSE) und cli.py (Click) hinzufügen


Lizenz

MIT

Available Tools

11 tools
check_bulk_ipsC

Check multiple IP addresses against threat feeds in bulk.

Args: ips: JSON array of IP addresses or comma-separated list

Returns: JSON with reputation results for all IPs

ParametersJSON Schema
NameRequiredDescriptionDefault
ipsYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It mentions bulk checking against threat feeds but lacks critical behavioral details: it doesn't specify rate limits, authentication needs, data sources, or what happens on errors. For a tool with no annotation coverage, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded, with the core purpose stated first. The 'Args' and 'Returns' sections add structure without redundancy. However, the 'Returns' section could be more concise, as the output schema exists, making some details unnecessary.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (bulk IP checking), no annotations, and an output schema present, the description is partially complete. It covers the basic purpose and parameter format but lacks usage guidelines, behavioral context, and error handling details. The output schema reduces the need to explain return values, but overall completeness is adequate with clear gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 0%, so the description must compensate. It adds value by explaining that 'ips' accepts a 'JSON array of IP addresses or comma-separated list', which clarifies the input format beyond the schema's 'type: string'. However, it doesn't detail validation rules, IP format requirements, or size limits, leaving some semantics unclear.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Check multiple IP addresses against threat feeds in bulk.' It specifies the verb ('check'), resource ('IP addresses'), and scope ('bulk'), distinguishing it from single-IP tools like 'check_ip_reputation'. However, it doesn't explicitly differentiate from other bulk tools like 'check_network_against_threats', keeping it from a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to prefer this over 'check_ip_reputation' for single IPs or how it differs from 'check_network_against_threats' for bulk checks. No exclusions or prerequisites are stated, leaving usage unclear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

check_hash_reputationA

Check a file hash (MD5/SHA1/SHA256) against threat intelligence.

Args: file_hash: File hash to check

Returns: JSON with reputation data

ParametersJSON Schema
NameRequiredDescriptionDefault
file_hashYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A3.5/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It mentions the tool checks against threat intelligence, but does not disclose behavioral traits such as rate limits, authentication needs, data sources, or error handling. This leaves significant gaps for a tool that likely queries external services.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded with the core purpose, followed by structured sections for args and returns. It avoids unnecessary details, though the 'Args' and 'Returns' headings could be integrated more seamlessly into the flow.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has an output schema (returns JSON with reputation data), the description does not need to explain return values. It covers the basic purpose and parameter semantics adequately, but could improve by adding more behavioral context (e.g., rate limits) to compensate for the lack of annotations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description adds meaning by specifying the parameter as a 'file hash' and listing supported hash types (MD5/SHA1/SHA256). However, it does not detail format constraints (e.g., length, case sensitivity) or provide examples, leaving some ambiguity beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('check') and resource ('file hash') against a target ('threat intelligence'). It distinguishes from siblings by specifying hash checking (vs. IPs, networks, feeds, etc.) and mentions supported hash types (MD5/SHA1/SHA256), making it unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for checking file hashes against threats, but does not explicitly state when to use this tool versus alternatives like check_ip_reputation or check_bulk_ips. It provides some context (e.g., hash types) but lacks explicit guidance on exclusions or prerequisites.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

check_ip_reputationC

Check an IP address against multiple threat intelligence sources.

Args: ip: IP address to check

Returns: JSON with reputation data from multiple sources

ParametersJSON Schema
NameRequiredDescriptionDefault
ipYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'multiple threat intelligence sources' but doesn't specify which sources, latency, rate limits, authentication needs, or error handling. For a tool that likely queries external APIs, this leaves critical operational details unclear.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose, followed by structured 'Args' and 'Returns' sections. It's efficient with minimal waste, though the 'Returns' section could be more specific about the JSON structure instead of just stating 'JSON with reputation data'.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (single parameter, threat intelligence query), the description covers the basics but lacks depth. The output schema exists, so return values needn't be detailed, but behavioral aspects like source reliability or rate limits are missing, making it adequate but incomplete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 0%, but the description explicitly documents the single parameter ('ip: IP address to check'), adding essential meaning beyond the bare schema. However, it doesn't provide format details (e.g., IPv4 vs. IPv6) or validation rules, so it only partially compensates for the schema gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Check an IP address against multiple threat intelligence sources.' It specifies the verb ('check') and resource ('IP address'), though it doesn't explicitly differentiate from sibling tools like 'check_bulk_ips' or 'check_hash_reputation' beyond the IP focus.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'check_bulk_ips' for multiple IPs or 'check_hash_reputation' for non-IP checks. It lacks context on prerequisites, limitations, or exclusions, leaving the agent to infer usage from tool names alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

check_network_against_threatsC

Check network scan results against threat intelligence.

Args: scan_results: JSON string from network scanner with device IPs

Returns: JSON with any matched threats

ParametersJSON Schema
NameRequiredDescriptionDefault
scan_resultsYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool checks against threat intelligence and returns JSON with matches, but lacks critical details: whether this is a read-only operation, if it requires authentication, rate limits, what happens on errors, or if it modifies any state (e.g., updates a cache). For a security tool with zero annotation coverage, this is a significant gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded: the first sentence states the core purpose, followed by structured 'Args' and 'Returns' sections. Each sentence earns its place by providing essential information without redundancy. Minor improvements could include integrating the sections more fluidly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (security analysis), no annotations, and an output schema exists (implied by 'Returns: JSON'), the description is moderately complete. It covers the basic operation and parameter semantics but lacks behavioral context (e.g., safety, performance) and usage guidelines. The output schema reduces the need to explain return values, but more context is needed for effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 0%, so the description must compensate. It adds meaning by specifying that 'scan_results' is a 'JSON string from network scanner with device IPs', which clarifies the parameter's format and content beyond the schema's generic 'string' type. However, it doesn't detail the exact JSON structure or provide examples, leaving some ambiguity.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Check network scan results against threat intelligence.' It specifies the verb ('check') and resource ('network scan results'), and distinguishes it from siblings like check_ip_reputation by focusing on bulk scan results rather than individual IPs. However, it doesn't explicitly differentiate from check_bulk_ips, which might be a similar sibling.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like check_bulk_ips or check_ip_reputation. It mentions 'scan results' but doesn't clarify prerequisites (e.g., requires prior network scanning) or exclusions (e.g., not for single IPs). This leaves the agent to infer usage from context alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

clear_threat_cacheB

Clear the threat intelligence cache to force fresh data fetch.

Returns: JSON confirmation

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

B3.2/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It states the action ('clear cache') and outcome ('force fresh data fetch'), but lacks critical behavioral details: it doesn't specify permissions required, whether this is destructive (e.g., deletes cached data), rate limits, or side effects on other tools. The mention of 'JSON confirmation' is vague about response structure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is highly concise and well-structured: two brief sentences that front-load the core action and mention the return type without redundancy. Every sentence adds value, with no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (0 parameters, output schema exists), the description is moderately complete. It covers the basic purpose and return format, but as a mutation tool with no annotations, it should ideally include more behavioral context (e.g., safety, permissions) to be fully helpful for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description doesn't add param details, which is appropriate, earning a baseline score of 4 for not introducing unnecessary information.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('Clear') and resource ('threat intelligence cache'), and distinguishes it from siblings by focusing on cache management rather than threat checking or data retrieval. However, it doesn't explicitly differentiate from all siblings (e.g., 'fetch_threat_feed' also involves data fetching).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides minimal guidance: it implies usage when fresh data is needed, but offers no explicit when/when-not rules, prerequisites, or alternatives. It doesn't compare with siblings like 'fetch_threat_feed' or 'get_threat_feeds' that might overlap in data freshness contexts.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

fetch_threat_feedB

Fetch and parse a specific threat intelligence feed.

Args: feed_name: Name of the feed (feodo_tracker, urlhaus_recent, etc.)

Returns: JSON with IOCs from the feed

ParametersJSON Schema
NameRequiredDescriptionDefault
feed_nameYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

B3.1/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool fetches and parses a feed, implying a read operation, but doesn't cover critical aspects like authentication needs, rate limits, error handling, or whether it caches results. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded, with the core purpose stated first. The 'Args' and 'Returns' sections are structured clearly, though they could be integrated more seamlessly. There's minimal waste, but it could be slightly more polished in flow.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has an output schema (returns JSON with IOCs), the description doesn't need to explain return values in detail. It covers the basic purpose and parameter semantics adequately. However, with no annotations and incomplete behavioral transparency, it could do more to address gaps like error cases or performance considerations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 0%, but the description compensates by explaining the 'feed_name' parameter: 'Name of the feed (feodo_tracker, urlhaus_recent, etc.)'. This adds meaning beyond the bare schema, providing examples and context. However, it doesn't detail all possible feed names or constraints, so it partially addresses the coverage gap but not fully.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Fetch and parse a specific threat intelligence feed.' It specifies the verb ('fetch and parse') and resource ('threat intelligence feed'), distinguishing it from siblings like 'check_ip_reputation' or 'get_recent_iocs' that focus on reputation checks or recent IOCs rather than fetching feeds. However, it doesn't explicitly differentiate from 'get_threat_feeds', which might be similar.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention siblings like 'get_threat_feeds' (which might list available feeds) or 'get_recent_iocs' (which might fetch recent IOCs without specifying a feed), leaving the agent to infer usage context. There's no explicit when/when-not or alternative recommendations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_cisa_kevA

Get CISA Known Exploited Vulnerabilities.

Args: days: Get vulnerabilities added in last N days (default: 30) vendor: Filter by vendor name (optional)

Returns: JSON with recent KEVs

ParametersJSON Schema
NameRequiredDescriptionDefault
daysNo
vendorNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A3.8/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool 'gets' data and returns JSON, but fails to describe critical behaviors such as whether this is a read-only operation (implied but not stated), any rate limits, authentication requirements, or what happens with invalid inputs (e.g., negative days). For a tool with no annotation coverage, this leaves significant gaps in understanding its operational traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and front-loaded with the core purpose, followed by clear sections for arguments and returns. Every sentence earns its place: the first states what the tool does, the next two explain parameters succinctly, and the last specifies the return format. There is zero waste, making it easy for an agent to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (2 parameters, no nested objects) and the presence of an output schema (which handles return values), the description is largely complete. It covers the purpose, parameters, and return format adequately. However, it lacks details on behavioral aspects like error handling or data freshness, which would be helpful since no annotations are provided to fill those gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description must compensate by explaining parameters, which it does effectively. It clarifies that 'days' retrieves vulnerabilities added in the last N days with a default of 30, and 'vendor' is an optional filter by vendor name. This adds meaningful context beyond the bare schema, covering both parameters' purposes and defaults, though it could benefit from examples or format details (e.g., vendor name casing).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('Get') and resource ('CISA Known Exploited Vulnerabilities'), making it immediately understandable. It distinguishes itself from sibling tools like 'get_recent_iocs' or 'get_threat_feeds' by focusing specifically on CISA's KEV database, which is a distinct dataset of known exploited vulnerabilities rather than general indicators or feeds.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage through the mention of filtering by days and vendor, suggesting it's for retrieving recent or vendor-specific vulnerabilities. However, it lacks explicit guidance on when to use this tool versus alternatives like 'get_recent_iocs' (which might overlap in recency) or 'check_network_against_threats' (which could involve KEV data), leaving the agent to infer context without clear exclusions or named alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_dashboard_summaryB

Get a summary of all threat intelligence for dashboard display.

Returns: JSON with aggregated threat data for visualization

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

B3.2/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool returns aggregated threat data for visualization, but doesn't cover critical aspects such as whether it's a read-only operation, potential rate limits, authentication requirements, data freshness, or any side effects. For a tool with no annotation coverage, this leaves key behavioral traits unspecified.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is highly concise and well-structured: two sentences that directly state the purpose and return format without any fluff. The first sentence explains what the tool does, and the second clarifies the output, making it front-loaded and efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 0 parameters, 100% schema coverage, and an output schema exists, the description doesn't need to detail inputs or return values. However, it lacks context on usage scenarios, behavioral traits, and differentiation from siblings, which are important for a tool in a server with multiple threat intelligence tools. The description is minimally adequate but has clear gaps in guidance and transparency.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter-specific information, which is appropriate here. A baseline of 4 is applied since there are no parameters to document, and the description doesn't introduce any confusion or redundancy regarding inputs.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Get a summary of all threat intelligence for dashboard display.' It specifies the verb ('Get') and resource ('summary of all threat intelligence'), and the context ('for dashboard display') provides additional clarity. However, it doesn't explicitly differentiate from sibling tools like 'get_threat_stats' or 'get_recent_iocs', which might also provide aggregated data, so it doesn't reach the highest score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It mentions 'dashboard display' as a context, but doesn't specify scenarios, prerequisites, or exclusions. With sibling tools like 'get_threat_stats' and 'get_recent_iocs' that might overlap, the lack of comparative guidance is a significant gap.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_recent_iocsB

Get recent IOCs (Indicators of Compromise) from ThreatFox.

Args: ioc_type: Filter by type (ip:port, domain, url, md5, sha256) limit: Maximum IOCs to return (default: 100, max: 500)

Returns: JSON with recent IOCs

ParametersJSON Schema
NameRequiredDescriptionDefault
ioc_typeNo
limitNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

B3.2/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that the tool returns 'JSON with recent IOCs' but doesn't specify details like pagination, rate limits, authentication requirements, or error handling. For a tool with potential security implications (IOCs), this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and front-loaded with the core purpose, followed by clear sections for 'Args' and 'Returns'. Every sentence earns its place by providing essential information without redundancy, making it efficient and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (2 parameters, no annotations, but with an output schema), the description is somewhat complete but has gaps. It covers parameters well and notes the return format, but lacks behavioral context (e.g., auth, rate limits) and doesn't leverage the output schema to detail the JSON structure, leaving room for improvement in overall completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It effectively explains both parameters: 'ioc_type' with its filter options (e.g., 'ip:port', 'domain') and 'limit' with its default and max values. This adds crucial meaning beyond the bare schema, though it could benefit from more detail on format constraints (e.g., URL encoding).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Get') and resource ('recent IOCs from ThreatFox'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'fetch_threat_feed' or 'get_threat_feeds', which might also retrieve threat data, leaving some ambiguity about when to choose this specific tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives like 'fetch_threat_feed' or 'get_threat_feeds'. The description lacks context about prerequisites, such as whether authentication is needed, or any explicit exclusions, leaving the agent to infer usage based on the tool name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_threat_feedsB

Get list of all available threat intelligence feeds.

Returns: JSON with available feeds and their descriptions

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

B3.1/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the return format ('JSON with available feeds and their descriptions'), which adds some context, but lacks details on permissions, rate limits, caching behavior, or whether this is a read-only operation. For a tool with zero annotation coverage, this is insufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is brief and front-loaded, stating the purpose in the first sentence and the return format in the second. Both sentences add value, with no wasted words. However, it could be slightly more structured by explicitly separating usage context from output details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has an output schema, the description doesn't need to explain return values in detail, which it acknowledges. However, with no annotations and multiple sibling tools, the description lacks context on behavioral traits and usage differentiation. It's minimally adequate but has clear gaps in guiding the agent effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate given the schema's completeness. A baseline of 4 is applied since there are no parameters to document.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Get' and resource 'list of all available threat intelligence feeds', making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'fetch_threat_feed' or 'get_recent_iocs', which might have overlapping functionality. The description is specific about what it returns but lacks sibling distinction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With siblings like 'fetch_threat_feed' and 'get_recent_iocs', there's no indication of whether this tool is for metadata listing, bulk retrieval, or other contexts. No prerequisites or exclusions are mentioned, leaving usage ambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_threat_statsB

Get statistics about loaded threat data and cache status.

Returns: JSON with threat intelligence statistics

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

B3.3/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It mentions 'cache status' which hints at behavioral aspects related to caching, but doesn't disclose details like whether this is a read-only operation, performance characteristics, or error handling. The description adds some context but lacks comprehensive behavioral traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is brief with two sentences, but the second sentence 'Returns: JSON with threat intelligence statistics' is redundant given the output schema exists. This wastes space without adding value, reducing efficiency.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (0 parameters, output schema provided), the description is mostly complete. It covers the purpose and hints at cache-related behavior, but could benefit from more usage guidance relative to siblings. The output schema handles return values, so no need to explain them in the description.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate here, and the baseline for 0 parameters is 4, as it avoids unnecessary repetition.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with the verb 'Get' and resource 'statistics about loaded threat data and cache status', making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'get_dashboard_summary' or 'get_threat_feeds', which might provide overlapping or related statistics.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With siblings like 'get_dashboard_summary' and 'get_threat_feeds' that might offer similar or complementary data, there's no indication of context, prerequisites, or exclusions to help an agent choose appropriately.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 11 tool updates
    • First observedcheck_bulk_ips
    • First observedcheck_hash_reputation
    • First observedcheck_ip_reputation
    • First observedcheck_network_against_threats
    • First observedclear_threat_cache
    • First observedfetch_threat_feed
    • First observedget_cisa_kev
    • First observedget_dashboard_summary
    • First observedget_recent_iocs
    • First observedget_threat_feeds
    • First observedget_threat_stats

TDQS

A3.7/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose with no ambiguity. The tools cover specific threat intelligence operations like checking IPs/hashes, fetching feeds, getting CISA KEVs, retrieving IOCs, and managing cache/stats, all with well-defined boundaries. There is no overlap that would cause misselection.

Naming Consistency5/5

Tool names follow a consistent verb_noun pattern throughout, such as check_bulk_ips, fetch_threat_feed, get_cisa_kev, and clear_threat_cache. All tools use snake_case with clear, descriptive names that align with their functions, making them predictable and readable.

Tool Count5/5

With 11 tools, the count is well-scoped for a threat intelligence server, covering essential operations like reputation checks, feed management, data retrieval, and cache control. Each tool earns its place without feeling excessive or insufficient for the domain.

Completeness5/5

The tool surface provides complete coverage for threat intelligence workflows, including checking various IOCs (IPs, hashes, networks), fetching and managing feeds, retrieving vulnerabilities and recent IOCs, and supporting dashboards and statistics. There are no obvious gaps that would hinder agent operations.

Maintenance

ActivityMaintained
ResponsivenessWithin a week

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