Threat Intelligence MCP Server

World Intelligence MCP Server
Глобальная разведка в реальном времени в 30+ доменах с 120 MCP-инструментами, живой панелью операционного центра, CLI и векторным хранилищем Qdrant для корпоративного семантического поиска по накопленным разведданным. Все данные поступают из бесплатных публичных API: платные подписки не требуются.
Создан для ИИ-агентов, которым нужна осведомлённость о мире: рыночные условия, геополитические риски, военный потенциал, сбои в цепочках поставок, киберугрозы и многое другое — всё доступно через Model Context Protocol. Векторное хранилище обеспечивает запросы на естественном языке, такие как «военная активность у Тайваня» или «киберугрозы, нацеленные на здравоохранение», по всем историческим данным.
Что вы получаете
Домен | Инструменты | Источники данных |
Финансовые рынки | 7 | Yahoo Finance, CoinGecko, Alternative.me, Mempool |
Форекс и валюты | 3 | ECB/Frankfurter (8 основных пар, временные ряды, кросс-курсы) |
Облигации и доходность | 2 | FRED, Yahoo Finance (кривая доходности, облигационные ETF, анализ спредов) |
Прибыль компаний | 2 | Yahoo Finance (календарь мегакапитализации, история сюрпризов) |
Подачи в SEC | 3 | SEC EDGAR (полнотекстовый поиск, корпоративные подачи, материальные события 8-K) |
Обогащение данных о компаниях | 1 | Yahoo Finance + GDELT + SEC + GitHub (композитный профиль) |
Макрокомпозит | 1 | Взвешенный рыночный вердикт по 6 сигналам (Fear&Greed, VIX, сектора, DXY, BTC, доходность) |
Экономические индикаторы | 6 | Цены на топливо AAA, энергетика EIA, макро FRED, World Bank |
Центральные банки | 1 | 15 ставок центральных банков |
Технический анализ BTC | 1 | SMA 50/200, золотой/смертельный крест, множитель Майера |
Стихийные бедствия | 2 | Землетрясения USGS, пожары NASA FIRMS |
Окружающая среда | 2 | NASA EONET, оповещения о катастрофах GDACS |
Климат | 1 | Аномалии температуры/осадков Open-Meteo |
Конфликты и безопасность | 4 | События ACLED, UCDP, обнаружение беспорядков, гуманитарные данные |
Военные и оборона | 6 | adsb.lol, OpenSky, hexdb.io, обнаружение всплесков, театральная позиция, пакетная обработка воздушных судов |
Инфраструктура | 4 | Cloudflare Radar, подводные кабели, каскадный анализ, статус облаков |
Морской транспорт | 2 | Навигационные предупреждения NGA, снимки судов |
Авиация | 2 | Задержки в аэропортах FAA, снимок внутренних рейсов |
Новости и СМИ | 3 | 119 RSS-каналов (4 уровня), GDELT, трендовые ключевые слова |
Анализ разведданных | 8 | Конвергенция сигналов, фокусные точки, индекс нестабильности, оценки рисков, эскалация |
NLP-разведка | 4 | Извлечение сущностей, классификация событий, кластеризация новостей, всплески ключевых слов |
Стратегический синтез | 4 | Стратегическая позиция, мировой брифинг, отчёт о флоте, охват населения |
Геопространственные данные | 11 | Военные базы, порты, трубопроводы, ядерные объекты, кабели, дата-центры, космодромы, полезные ископаемые, биржи, торговые маршруты, облачные регионы |
ИИ и технологии | 4 | Статьи arXiv, модели HuggingFace, Hacker News, тренды GitHub |
Киберугрозы | 1 | URLhaus, Feodotracker, CISA KEV, SANS |
Здравоохранение | 1 | WHO DON, ProMED, вспышки заболеваний CIDRAP |
Космическая погода | 1 | NOAA SWPC (индекс Kp, солнечные вспышки, оповещения) |
Социальные сети и санкции | 3 | Скорость Reddit, список SDN OFAC, мониторинг ядерных испытаний |
Разведка по странам | 3 | Брифинг по стране, акции страны, финансовые центры |
Рынки прогнозов | 1 | Контракты на события Polymarket |
Выборы | 1 | Глобальный календарь выборов с оценкой рисков |
Перемещение населения | 1 | Данные UNHCR о беженцах/ВПЛ |
Судоходство | 1 | Индекс стресса сухогрузных перевозок |
Правительство | 1 | Федеральные контракты USAspending.gov |
Трафик | 2 | Поток дорожного движения, инциденты в реальном времени |
Междоменные оповещения | 2 | Сводка оповещений, еженедельные тренды |
Мониторинг | 2 | Веб-камеры, состояние/статус серверов |
Векторный поиск | 5 | Семантический поиск Qdrant, сходство, временная шкала, статистика |
Междоменная аналитика | 3 | Корреляция, сводка по доменам, обнаружение трендов |
Отчёты | 1 | Многодоменные отчёты PDF/HTML |
Ежедневный дайджест | 1 | Утренний брифинг в Markdown с цитатами: главные события, заголовки, тренды и временная шкала |
Геозоны AOI | 5 | Определяемые пользователем зоны интереса: определение/список/удаление, цитируемый многодоменный брифинг и оценка эскалации горячих точек для собственной зоны пользователя |
Ситуационный брифинг | 1 | Цитируемый брифинг ситуационной осведомлённости через MCP: ограниченный серверный обзор, синтезированный через локальный Ollama, с механически цитируемым запасным вариантом |
Итого: 120 инструментов в 30+ доменах разведки.
Related MCP server: MCP Threat Intel Server
Быстрый старт
Установка
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, coverageЗапуск как MCP-сервер
world-intel-mcp # stdio mode for Claude Code, Cursor, etc.Конфигурация Claude Code
Добавьте в ~/.claude.json:
{
"mcpServers": {
"world-intel-mcp": {
"command": "world-intel-mcp"
}
}
}Панель управления
intel-dashboard # http://localhost:8501
intel-dashboard --port 9000 # custom portОтчёты PDF/HTML
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 sectionsОперационный центр с картой в приоритете: карта Leaflet с переключаемыми слоями (землетрясения, военные, конфликты, пожары, конвергенция, ядерные объекты, инфраструктура), 47 живых SSE-каналов, HUD-панель, стекломорфные панели, состояние автоматического выключателя по каждому источнику.
CLI
intel markets # stock indices
intel earthquakes --min-mag 5.0
intel status # cache + circuit breaker healthАрхитектура
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: Централизованный асинхронный HTTP-клиент (httpx). Повторные попытки, ограничение скорости по источникам, запасной вариант с устаревшими данными. Автоматически сохраняет результаты в векторное хранилище при свежих запросах.
CircuitBreaker: Отслеживание по источникам. 3 последовательных сбоя отключают источник на 5 минут. Каждый RSS-канал получает собственный выключатель.
Cache: TTL-кэш SQLite в режиме WAL.
get()возвращает живые данные,get_stale()возвращает просроченные данные для запасного варианта.VectorStore: Qdrant + FastEmbed (BAAI/bge-small-en-v1.5, 384-мерный). Асинхронная фоновая очередь задач для неблокирующего хранения. Обеспечивает семантический поиск по всем накопленным разведданным.
Collector: Автономный демон, который параллельно получает все 46 источников и заполняет векторное хранилище. Запускается один раз или как демон (по умолчанию: интервал 5 минут).
Sources (
sources/*.py): 30+ модулей, каждый экспортируетasync def fetch_*(fetcher, **kwargs) -> dict.Analysis (
analysis/*.py): Междоменный синтез — агрегация сигналов, индексирование нестабильности, NLP, обогащение компаний, макрокомпозит.Config (
config/*.py): Курируемые наборы данных — 22 горячие точки, 70+ баз, 40 портов, 24 трубопровода, 24 ядерных объекта, 34 кабеля, 48 дата-центров, 27 космодромов, 82 биржи.
Справочник MCP-инструментов
Финансовые рынки (7)
Инструмент | Описание |
| Котировки фондовых индексов (S&P 500, Dow, Nasdaq, FTSE, Nikkei) |
| Цены и рыночные капитализации ведущих криптовалют от CoinGecko |
| Состояние привязки стейблкоинов (USDT, USDC, DAI, FDUSD) |
| Цены и объёмы спотовых ETF на биткоин |
| Эффективность секторов акций США (11 ETF SPDR) |
| 7 макроиндикаторов (Fear & Greed, VIX, DXY, золото, 10Y, BTC) |
| Фьючерсы на сырьевые товары (золото, серебро, нефть, природный газ, зерновые) |
Форекс и валюты (3)
Инструмент | Описание |
| Последние курсы валют от ЕЦБ. Фильтрация по базовым/целевым валютам |
| Исторические курсы валют с анализом тренда (настраиваемое количество дней) |
| Все 8 основных пар + кросс-курсы + прокси DXY |
Облигации и доходность (2)
Инструмент | Описание |
| Кривая доходности казначейских облигаций США (2Y-30Y), спреды 2s10s/3m10y, флаг инверсии |
| Биржевые фонды облигаций: AGG, TLT, HYG, LQD, TIP с ценой/изменением |
Прибыль (2)
Инструмент | Описание |
| Предстоящие отчёты о прибыли для 20 акций с крупной капитализацией с оценками EPS |
| Исторические сюрпризы по прибыли (факт против прогноза, тренд) |
Документы SEC (3)
Инструмент | Описание |
| Полнотекстовый поиск по всем документам EDGAR |
| Документы компании по тикеру (10-K, 10-Q, 8-K) с определением CIK |
| Последние существенные события 8-K (M&A, кадровые изменения, прибыль) |
Обогащение данных о компаниях (1)
Инструмент | Описание |
| Комплексный профиль: котировка акций + финансовые показатели + новости + SEC + GitHub |
Макро-композит (1)
Инструмент | Описание |
| Взвешенный рыночный балл (0-100) с вердиктом: от RISK_ON до STRONG_CAUTION |
Экономика (6)
Инструмент | Описание |
| Ежедневные розничные цены на бензин, дизель и E85 в США от AAA |
| Цены на природный газ для жилых домов в США от EIA |
| Розничные тарифы на электроэнергию в США по секторам/штатам от EIA |
| Нефть Brent/WTI и природный газ от EIA |
| Экономические данные FRED (ВВП, ИПЦ, безработица, ставки) |
| Показатели развития Всемирного банка по странам |
Центральные банки (1)
Инструмент | Описание |
| Процентные ставки 15 крупнейших центральных банков |
Технические индикаторы BTC (1)
Инструмент | Описание |
| Bitcoin SMA 50/200, золотой/крест смерти, множитель Майера |
Стихийные бедствия (2)
Инструмент | Описание |
| Землетрясения USGS (настраиваемые магнитуда/время/лимит) |
| Спутниковые очаги пожаров NASA FIRMS (9 глобальных регионов) |
Окружающая среда (2)
Инструмент | Описание |
| Природные события NASA EONET |
| Оповещения о бедствиях GDACS с оценкой серьёзности |
Конфликты и безопасность (4)
Инструмент | Описание |
| События вооружённых конфликтов ACLED |
| События программы данных о конфликтах Уппсалы |
| Социальные волнения с дедупликацией по Хаверсину |
| Наборы данных о гуманитарных кризисах HDX |
Военные и оборона (6)
Инструмент | Описание |
| Военные самолёты через adsb.lol (запасной вариант OpenSky) |
| Активность в 5 зонах (ЕС, Индо-Тихоокеанский регион, Ближний Восток, Арктика, Корея) |
| Поиск самолёта по ICAO24 hex (hexdb.io) |
| Пакетный поиск самолётов (несколько hex-кодов) |
| Обнаружение аномалий концентрации иностранных самолётов |
| Трекер военно-морского флота USNI News |
Инфраструктура (4)
Инструмент | Описание |
| Сбои интернета Cloudflare Radar |
| Состояние коридоров подводных кабелей |
| Симуляция каскадных сбоев инфраструктуры |
| Состояние облачных платформ (AWS, Azure, GCP, Cloudflare, GitHub) |
Морские (2)
Инструмент | Описание |
| Предупреждения о морской навигации NGA |
| Военно-морская активность в 9 стратегических водных путях |
Геопространственные наборы данных (10)
Инструмент | Описание |
| 70 военных баз от 9 операторов |
| 40 стратегических портов 6 типов |
| 24 нефте/газо/водородных трубопровода |
| 24 ядерных объекта: энергетика/обогащение/исследования |
| 34 подводных коммуникационных кабеля |
| 48 центров обработки данных ИИ/ВПК по всему миру |
| 27 космодромов по всему миру |
| 27 месторождений стратегических полезных ископаемых |
| 82 фондовые биржи по всему миру |
| Основные торговые маршруты и узкие места |
Новости и СМИ (3)
Инструмент | Описание |
| 119 глобальных RSS-лент с 4-уровневым рейтингом источников |
| Трендовые термины с обнаружением всплесков |
| Глобальный поиск новостей GDELT 2.0 |
Анализ разведданных (8)
Инструмент | Описание |
| Географическая конвергенция многодоменных сигналов |
| Обнаружение фокальных точек множественных сигналов |
| Агрегация сигналов на уровне стран |
| Отклонения активности от базовых уровней |
| Индекс нестабильности стран v2 (0-100) |
| Оценка риска конфликтов на основе ACLED |
| Оценки эскалации для 22 разведывательных горячих точек |
| Комплексное разведывательное досье по странам |
NLP-аналитика (4)
Инструмент | Описание |
| Извлечение именованных сущностей (страны, лидеры, организации, CVE, APT) |
| Классификация событий по 14 категориям угроз |
| Кластеризация тем по сходству Жаккара |
| Обнаружение всплесков ключевых слов с алгоритмом Уэлфорда |
Стратегический синтез (4)
Инструмент | Описание |
| Композитный глобальный риск из 9 взвешенных доменов |
| Структурированная ежедневная сводка разведданных |
| Отчёт об активности военно-морского флота с оценкой готовности |
| Население в зоне риска вблизи активных событий (набор данных по 105 городам) |
Климат (1)
Инструмент | Описание |
| Аномалии температуры/осадков Open-Meteo |
Рынки прогнозов (1)
Инструмент | Описание |
| Контракты прогнозов Polymarket |
Выборы (1)
Инструмент | Описание |
| Глобальный календарь выборов с оценкой риска |
Перемещение (1)
Инструмент | Описание |
| Статистика беженцев/ВПЛ УВКБ ООН |
Авиация (2)
Инструмент | Описание |
| Статус задержек в аэропортах FAA |
| Глобальный снимок воздушного движения от OpenSky |
Киберугрозы (1)
Инструмент | Описание |
| Агрегированные киберразведданные (URLhaus, CISA KEV, SANS) |
Космическая погода (1)
Инструмент | Описание |
| Солнечная активность (индекс Kp, рентгеновский поток, оповещения SWPC) |
ИИ и технологии (4)
Tool | Описание |
| Научные статьи arXiv по ИИ, модели HuggingFace |
| Лучшие истории Hacker News |
| Популярные репозитории GitHub |
| Поиск статей arXiv |
Здоровье (1)
Tool | Описание |
| Вспышки заболеваний: WHO DON, ProMED, CIDRAP |
Социальные сигналы и санкции (3)
Tool | Описание |
| Скорость геополитических обсуждений на Reddit |
| Поиск по списку SDN OFAC |
| Сейсмический мониторинг вблизи ядерных полигонов |
Судоходство и торговля (1)
Tool | Описание |
| Индекс стресса сухих балкерных перевозок |
Правительство (1)
Tool | Описание |
| Федеральные контракты USAspending.gov |
Страноведческая аналитика (3)
Tool | Описание |
| Краткая сводка ситуации по стране |
| Фондовые биржи и листинги по странам |
| Рейтинг мировых финансовых центров |
Расширенная геопространственная аналитика (1)
Tool | Описание |
| Регионы облачных провайдеров по всему миру |
Трафик (2)
Tool | Описание |
| Данные о дорожном трафике |
| Дорожные происшествия в реальном времени |
Междоменные оповещения (2)
Tool | Описание |
| Агрегация оповещений по всем доменам |
| Еженедельный анализ тенденций |
Мониторинг (2)
Tool | Описание |
| Публичные веб-камеры: расположение и прямые трансляции |
| Состояние сервера, статистика кэша, статус автоматического выключателя |
Векторный поиск (5)
Tool | Описание |
| Поиск на естественном языке по всем накопленным разведданным |
| Поиск событий, похожих на заданную точку данных |
| Хронологический обзор разведданных по домену/категории |
| Статистика коллекций векторного хранилища |
| Запуск цикла сбора по требованию |
Междоменная аналитика (3)
Tool | Описание |
| Поиск коррелированных сигналов по всем доменам для заданной темы |
| Сводка по категориям накопленных разведданных (количество, источники, актуальность) |
| Обнаружение всплесков/спадов активности путём сравнения недавнего и базового периодов |
Отчёты (1)
Tool | Описание |
| Генерация PDF или HTML отчёта по разведданным, охватывающего 18 доменов параллельно |
Геозоны AOI (5)
Tool | Описание |
| Определение именованной области интереса: точка + радиус в км (1–2000) |
| Список всех пользовательских AOI |
| Удаление пользовательской AOI по имени |
| Краткая сводка с цитатами для AOI: землетрясения, военные полёты, лесные пожары, конфликтные события, авиация, ближайшая инфраструктура и упоминания в новостях, всё отфильтровано по радиусу AOI |
| Оценка эскалации горячих точек (тот же движок, что и для 22 встроенных горячих точек), применённая к пользовательской AOI |
Ситуационная сводка (1)
Tool | Описание |
| Краткая сводка ситуационной осведомлённости с цитатами, генерируемая по запросу через MCP: ограниченный серверный обзор (землетрясения, военные полёты, конфликтные события ACLED, лесные пожары, киберугрозы, вспышки заболеваний, новости, космическая погода, стратегическая позиция, дайджест оповещений), синтезируется через локальную Ollama или механически цитируемый запасной вариант, когда Ollama недоступна |
Наблюдение за своей территорией (геозоны/AOI)
Результаты по статической инфраструктуре (базы, порты, ядерные объекты, кабели, дата-центры, космодромы) основаны на курируемых стратегических наборах данных этого репозитория, которые являются глобальными и намеренно разрежёнными, а не исчерпывающими локальными реестрами. Тихая сводка AOI означает, что ничего из этих курируемых наборов не попадает в радиус, а не то, что в вашем районе нет инфраструктуры.
28 из 120 инструментов принимают какой-либо географический параметр, но до семейства AOI только intel_signal_convergence принимал настоящую точку-плюс-радиус, intel_military_flights принимал bbox, а оценка эскалации горячих точек была ограничена 22 жёстко заданными INTEL_HOTSPOTS. Инструменты intel_aoi_* позволяют вам назвать свою собственную область (город, приграничный регион, объект) и получить ту же цитируемую многодоменную обработку.
Определите AOI один раз, затем запрашивайте сводку и оценку по требованию:
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 фильтрует каждый гео-совместимый домен по радиусу 50 км вокруг Питтсбурга: землетрясения, военные полёты (bbox, производный от радиуса), лесные пожары (сопоставленные по регионам, поскольку у NASA FIRMS нет запроса точка+радиус), конфликтные события ACLED, выборка ближайшего авиационного трафика, ближайшая статическая инфраструктура (военные базы, порты, трубопроводы, ядерные объекты, подводные кабели, дата-центры, космодромы) с расстояниями в км, а также упоминания в заголовках новостей о «Питтсбурге». Каждый элемент в ответе содержит цитату [n] в нумерованный список sources, а data_gaps указывает на любой домен, который не удалось ограничить AOI (например, лесные пожары, когда AOI выходит за пределы зон покрытия NASA FIRMS, или конфликтные события, когда учётные данные ACLED не настроены), вместо того чтобы молча опускать его.
intel_aoi_escalation запускает тот же движок оценки базовой/военной/конфликтной/социальной нестабильности, который питает intel_hotspot_escalation для 22 встроенных горячих точек, но ограничен радиусом вашей AOI вместо фиксированного окна в 2 градуса.
AOI сохраняются в отдельной таблице внутри той же базы данных кэша SQLite, которую уже использует сервер (по умолчанию ~/.cache/world-intel-mcp/cache.db или $WORLD_INTEL_CACHE_DB), поэтому запланированный агент может наблюдать за любой именованной областью между перезапусками, используя intel_aoi_list / intel_aoi_delete для управления ими.
Векторное хранилище
Опциональное векторное хранилище Qdrant накапливает разведданные со временем для семантического поиска. Все данные, полученные через Fetcher, автоматически встраиваются и сохраняются.
Настройка
# 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 cycleЗапуск как службы launchd в macOS
scripts/collector-daemon.sh управляет коллектором как агентом launchd, чтобы он переживал перезагрузки. Он заполняет com.agentic.intel-collector.plist.template собственным путём этого чекаута (разрешённым из местоположения самого скрипта, так что он работает из любого клона) и устанавливает результат в ~/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 itПримеры семантического поиска
Когда данные накапливаются, ИИ-агенты могут запрашивать все домены:
«военная активность вблизи Тайваньского пролива» — находит военные полёты, военно-морские предупреждения, данные о театральной позиции
«киберугрозы, нацеленные на здравоохранение» — находит записи URLhaus, CISA KEV, связанные со здравоохранением
«экономические индикаторы, указывающие на рецессию» — находит инверсии кривой доходности, макросигналы, данные FRED
Векторное хранилище использует FastEmbed (на основе ONNX, BAAI/bge-small-en-v1.5) для встраиваний — не требуется GPU, холодный старт ~3 секунды.
Переменные окружения
Variable | Required | Description |
| Нет | Конфликтные события ACLED |
| Нет | Спутниковые данные о лесных пожарах |
| Нет | Данные о ценах на энергию |
| Нет | Данные об отключениях интернета |
| Нет | Макроэкономические данные (также используются для кривой доходности) |
| Нет | Запасной вариант для военных полётов |
| Нет | Запасной вариант для военных полётов |
| Нет | Сервер Ollama для ИИ-сводок (по умолчанию: |
| Нет | Модель Ollama для ИИ-сводок (по умолчанию: |
| Нет | Уровень журналирования (по умолчанию: INFO) |
Всё остальное использует бесплатные, неаутентифицированные публичные API.
Разработка
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 moduleДобавление нового источника
Создайте
sources/your_source.pyсasync def fetch_your_data(fetcher: Fetcher, **kwargs) -> dictИспользуйте
fetcher.get_json(url, source="your-source", cache_key=..., cache_ttl=300)— автоматическое кэширование, повторные попытки, размыкание цепи, ограничение скоростиВ
server.py: добавьтеTool(...)вTOOLS, добавьтеcaseв_dispatch()(используйте встроенный импорт)Добавьте тесты с использованием
respxдля имитации HTTP (см.tests/test_forex.pyдля примера)При желании добавьте в
dashboard/app.py(SSE) иcli.py(Click)
Лицензия
MIT
Available Tools
11 toolscheck_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
| Name | Required | Description | Default |
|---|---|---|---|
| ips | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
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.
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.
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.
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.
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.
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
| Name | Required | Description | Default |
|---|---|---|---|
| file_hash | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
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.
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.
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.
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.
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.
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
| Name | Required | Description | Default |
|---|---|---|---|
| ip | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
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.
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.
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.
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.
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.
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
| Name | Required | Description | Default |
|---|---|---|---|
| scan_results | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
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.
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.
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.
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.
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.
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
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
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.
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.
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.
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.
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.
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
| Name | Required | Description | Default |
|---|---|---|---|
| feed_name | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
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.
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.
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.
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.
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.
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
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | ||
| vendor | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
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.
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.
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.
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.
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.
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
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
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.
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.
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.
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.
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.
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
| Name | Required | Description | Default |
|---|---|---|---|
| ioc_type | No | ||
| limit | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
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.
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.
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.
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.
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.
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
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
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.
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.
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.
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.
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.
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
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
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.
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.
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.
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.
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.
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.
11 tool updates
- First observed
check_bulk_ips - First observed
check_hash_reputation - First observed
check_ip_reputation - First observed
check_network_against_threats - First observed
clear_threat_cache - First observed
fetch_threat_feed - First observed
get_cisa_kev - First observed
get_dashboard_summary - First observed
get_recent_iocs - First observed
get_threat_feeds - First observed
get_threat_stats
TDQS
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.
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.
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.
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.
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