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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

Real-time global intelligence across 30+ domains with 132 MCP tools, a live ops-center dashboard, a CLI, and a Qdrant vector store for enterprise-grade semantic search across accumulated intelligence. All data comes from free, public APIs: no paid subscriptions required.

Built for AI agents that need world awareness: market conditions, geopolitical risk, military posture, supply chain disruptions, cyber threats, and more — all queryable via the Model Context Protocol. The vector store enables natural language queries like "military activity near Taiwan" or "cyber threats targeting healthcare" across all historical data.


What You Get

Domain

Tools

Data Sources

Financial Markets

7

Yahoo Finance, CoinGecko, Alternative.me, Mempool

Forex & Currency

3

ECB/Frankfurter (8 major pairs, timeseries, cross rates)

Bonds & Yields

2

FRED, Yahoo Finance (yield curve, bond ETFs, spread analysis)

Earnings

2

Yahoo Finance (mega-cap calendar, surprise history)

SEC Filings

3

SEC EDGAR (full-text search, company filings, 8-K material events)

Company Enrichment

1

Yahoo Finance + GDELT + SEC + GitHub (composite profile)

Macro Composite

1

Weighted 6-signal market verdict (Fear&Greed, VIX, sectors, DXY, BTC, yields)

Economic Indicators

6

AAA fuel prices, EIA energy, FRED macro, World Bank

Central Banks

1

15 central bank policy rates

BTC Technicals

1

SMA 50/200, golden/death cross, Mayer Multiple

Natural Disasters

2

USGS earthquakes, NASA FIRMS wildfires

Environmental

2

NASA EONET, GDACS disaster alerts

Climate

1

Open-Meteo temperature/precipitation anomalies

Conflict & Security

4

ACLED events, UCDP, unrest detection, humanitarian data

Military & Defense

6

adsb.lol, OpenSky, hexdb.io, surge detection, theater posture, aircraft batch

Infrastructure

5

Cloudflare Radar, submarine cables, cascade analysis, cloud status, RIPEstat BGP/RPKI

Maritime

2

NGA navigation warnings, vessel snapshots

Aviation

2

FAA airport delays, domestic flight snapshot

News & Media

3

119 RSS feeds (4-tier), GDELT, trending keywords

Intelligence Analysis

8

Signal convergence, focal points, instability index, risk scores, escalation

NLP Intelligence

4

Entity extraction, event classification, news clustering, keyword spikes

Strategic Synthesis

4

Strategic posture, world brief, fleet report, population exposure

Geospatial

11

Military bases, ports, pipelines, nuclear facilities, cables, datacenters, spaceports, minerals, exchanges, trade routes, cloud regions

AI & Technology

4

arXiv papers, HuggingFace models, Hacker News, GitHub trending

Cyber Threats

1

URLhaus, Feodotracker, CISA KEV, SANS

Health

1

WHO DON, ProMED, CIDRAP disease outbreaks

Space Weather

1

NOAA SWPC (Kp index, solar flares, alerts)

Social & Sanctions

3

Reddit velocity, OFAC SDN list, nuclear test site monitoring

Country Intelligence

3

Country brief, country stocks, financial centers

Prediction Markets

1

Polymarket event contracts

Elections

1

Global election calendar with risk scoring

Displacement

1

UNHCR refugee/IDP data

Shipping

1

Dry bulk shipping stress index

Government

1

USAspending.gov federal contracts

Traffic

2

Road traffic flow, real-time incidents

Cross-Domain Alerts

2

Alert digest, weekly trends

Monitoring

2

Webcams, server health/status

Vector Search

5

Qdrant semantic search, similarity, timeline, stats

Cross-Domain Analytics

3

Correlation, domain summary, trend detection

Reports

1

PDF/HTML multi-domain intelligence reports

Daily Digest

1

Cited markdown morning brief: top events, headlines, trends, and timeline

AOI Geofences

10

User-defined areas of interest in three shapes (circle, polygon, corridor): define/list/update/delete, a cited multi-domain brief, hotspot escalation scoring, and enter/leave change detection for a user's own area. News is scoped to the place the area sits in (OSM Nominatim reverse geocoding, no key), not to the area's name

Severe Weather

2

NWS active CAP alerts (US), Meteoalarm (39 EU countries)

Space Launches

1

Launch Library 2 upcoming launches

Volcanoes

1

Smithsonian GVP weekly activity report

Tropical Cyclones

2

NHC (Atlantic, E/C Pacific) + JTWC (NW Pacific, N Indian, S Hemisphere)

Situation Brief

1

Cited situational awareness brief over MCP: bounded server-side overview synthesized via local Ollama, with a mechanically-cited fallback

Total: 132 tools across 30+ intelligence domains.


Related MCP server: MCP Threat Intel Server

Quick Start

Install

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

Run as MCP Server

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

Claude Code Configuration

Add to ~/.claude.json:

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

Dashboard

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

PDF/HTML Reports

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

Map-first ops center: Leaflet map with toggle-able layers (quakes, military, conflict, fires, convergence, nuclear, infrastructure, your AOI geofences with last-sweep counts), 47 live SSE feeds, HUD bar, glassmorphic panels, per-source circuit breaker health.

CLI

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

Architecture

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: Centralized async HTTP client (httpx). Retries, per-source rate limiting, stale-data fallback. Auto-stores results in vector store on fresh fetches.

  • CircuitBreaker: Per-source tracking. 3 consecutive failures trips for 5 minutes. Each RSS feed gets its own breaker.

  • Cache: SQLite WAL-mode TTL cache. get() returns live data, get_stale() returns expired data for fallback.

  • VectorStore: Qdrant + FastEmbed (BAAI/bge-small-en-v1.5, 384-dim). Async background worker queue for non-blocking storage. Enables semantic search across all accumulated intelligence.

  • Collector: Standalone daemon that fetches all 51 sources in parallel and populates the vector store. Run once or as a daemon (default: 5-minute interval). Includes the AOI change sweep, so a running daemon continuously watches every defined geofence.

  • Sources (sources/*.py): 30+ modules, each exports async def fetch_*(fetcher, **kwargs) -> dict.

  • Analysis (analysis/*.py): Cross-domain synthesis — signal aggregation, instability indexing, NLP, company enrichment, macro composite.

  • Config (config/*.py): Curated datasets — 22 hotspots, 70+ bases, 40 ports, 24 pipelines, 24 nuclear facilities, 34 cables, 48 datacenters, 27 spaceports, 82 exchanges.


MCP Tools Reference

Financial Markets (7)

Tool

Description

intel_market_quotes

Stock index quotes (S&P 500, Dow, Nasdaq, FTSE, Nikkei)

intel_crypto_quotes

Top crypto prices and market caps from CoinGecko

intel_stablecoin_status

Stablecoin peg health (USDT, USDC, DAI, FDUSD)

intel_etf_flows

Bitcoin spot ETF prices and volumes

intel_sector_heatmap

US equity sector performance (11 SPDR ETFs)

intel_macro_signals

7 macro indicators (Fear & Greed, VIX, DXY, gold, 10Y, BTC)

intel_commodity_quotes

Commodity futures (gold, silver, crude, natgas, grains)

Forex & Currency (3)

Tool

Description

intel_forex_rates

Latest FX rates from ECB. Filter by base/target currencies

intel_forex_timeseries

Historical FX rate with trend analysis (configurable days)

intel_major_crosses

All 8 major pairs + cross rates + DXY proxy

Bonds & Yields (2)

Tool

Description

intel_yield_curve

US Treasury yield curve (2Y-30Y), 2s10s/3m10y spreads, inversion flag

intel_bond_indices

Bond ETFs: AGG, TLT, HYG, LQD, TIP with price/change

Earnings (2)

Tool

Description

intel_earnings_calendar

Upcoming earnings for 20 mega-cap stocks with EPS estimates

intel_earnings_surprise

Historical earnings surprise (actual vs estimate, trend)

SEC Filings (3)

Tool

Description

intel_sec_filings

Full-text search across all EDGAR filings

intel_company_filings

Company filings by ticker (10-K, 10-Q, 8-K) with CIK resolution

intel_recent_8k

Latest 8-K material events (M&A, exec changes, earnings)

Company Enrichment (1)

Tool

Description

intel_company_profile

Composite profile: stock quote + financials + news + SEC + GitHub

Macro Composite (1)

Tool

Description

intel_macro_composite

Weighted market score (0-100) with verdict: RISK_ON to STRONG_CAUTION

Economic (6)

Tool

Description

intel_gas_prices

Daily US retail gasoline, diesel, and E85 prices from AAA

intel_residential_natgas

US residential natural gas prices from EIA

intel_electricity_rates

US electricity retail rates by sector/state from EIA

intel_energy_prices

Brent/WTI crude oil and natural gas from EIA

intel_fred_series

FRED economic data (GDP, CPI, unemployment, rates)

intel_world_bank_indicators

World Bank development indicators by country

Central Banks (1)

Tool

Description

intel_central_bank_rates

Policy rates for 15 major central banks

BTC Technicals (1)

Tool

Description

intel_btc_technicals

Bitcoin SMA 50/200, golden/death cross, Mayer Multiple

Natural Disasters (2)

Tool

Description

intel_earthquakes

USGS earthquakes (configurable magnitude/time/limit)

intel_wildfires

NASA FIRMS satellite fire hotspots (9 global regions)

Environmental (2)

Tool

Description

intel_environmental_events

NASA EONET natural events

intel_disaster_alerts

GDACS disaster alerts with severity scoring

Conflict & Security (4)

Tool

Description

intel_acled_events

ACLED armed conflict events

intel_ucdp_events

Uppsala Conflict Data Program events

intel_unrest_events

Social unrest with Haversine dedup

intel_humanitarian_summary

HDX humanitarian crisis datasets

Military & Defense (6)

Tool

Description

intel_military_flights

Military aircraft via adsb.lol (OpenSky fallback)

intel_theater_posture

Activity across 5 theaters (EU, Indo-Pacific, ME, Arctic, Korea)

intel_aircraft_details

Aircraft lookup by ICAO24 hex (hexdb.io)

intel_aircraft_batch

Batch aircraft lookup (multiple hex codes)

intel_military_surge

Foreign aircraft concentration anomaly detection

intel_usni_fleet

USNI News naval fleet tracker

Infrastructure (4)

Tool

Description

intel_internet_outages

Cloudflare Radar internet disruptions

intel_cable_health

Submarine cable corridor health

intel_cascade_analysis

Infrastructure cascade simulation

intel_service_status

Cloud platform health (AWS, Azure, GCP, Cloudflare, GitHub)

Maritime (2)

Tool

Description

intel_nav_warnings

NGA maritime navigation warnings

intel_vessel_snapshot

Naval activity at 9 strategic waterways

Geospatial Datasets (10)

Tool

Description

intel_military_bases

70 military bases from 9 operators

intel_strategic_ports

40 strategic ports across 6 types

intel_pipelines

24 oil/gas/hydrogen pipelines

intel_nuclear_facilities

24 nuclear power/enrichment/research facilities

intel_undersea_cables

34 submarine communications cables

intel_ai_datacenters

48 AI/HPC datacenters worldwide

intel_spaceports

27 global spaceports

intel_critical_minerals

27 strategic mineral deposits

intel_stock_exchanges

82 stock exchanges worldwide

intel_trade_routes

Major trade routes and chokepoints

News & Media (3)

Tool

Description

intel_news_feed

119 global RSS feeds with 4-tier source ranking

intel_trending_keywords

Trending terms with spike detection

intel_gdelt_search

GDELT 2.0 global news search

Intelligence Analysis (8)

Tool

Description

intel_signal_convergence

Geographic convergence of multi-domain signals

intel_focal_points

Multi-signal focal point detection

intel_signal_summary

Country-level signal aggregation

intel_temporal_anomalies

Activity deviations from baselines

intel_instability_index

Country Instability Index v2 (0-100)

intel_risk_scores

ACLED-based conflict risk scoring

intel_hotspot_escalation

Escalation scores for 22 intel hotspots

intel_country_dossier

Comprehensive country intelligence dossier

NLP Intelligence (4)

Tool

Description

intel_extract_entities

Named entity extraction (countries, leaders, orgs, CVEs, APTs)

intel_classify_event

Event classification into 14 threat categories

intel_news_clusters

Topic clustering by Jaccard similarity

intel_keyword_spikes

Keyword spike detection with Welford's algorithm

Strategic Synthesis (4)

Tool

Description

intel_strategic_posture

Composite global risk from 9 weighted domains

intel_world_brief

Structured daily intelligence summary

intel_fleet_report

Naval fleet activity report with readiness scoring

intel_population_exposure

Population at risk near active events (105-city dataset)

Climate (1)

Tool

Description

intel_climate_anomalies

Open-Meteo temperature/precipitation anomalies

Prediction Markets (1)

Tool

Description

intel_prediction_markets

Polymarket prediction contracts

Elections (1)

Tool

Description

intel_election_calendar

Global election calendar with risk scoring

Displacement (1)

Tool

Description

intel_displacement_summary

UNHCR refugee/IDP statistics

Aviation (2)

Tool

Description

intel_airport_delays

FAA airport delay status

intel_aviation_domestic

Global air traffic snapshot from OpenSky

Cyber Threats (1)

Tool

Description

intel_cyber_threats

Aggregated cyber intel (URLhaus, CISA KEV, SANS)

Space Weather (1)

Tool

Description

intel_space_weather

Solar activity (Kp index, X-ray flux, SWPC alerts)

AI & Technology (4)

Tool

Description

intel_ai_releases

arXiv AI papers, HuggingFace models

intel_hacker_news

Hacker News top stories

intel_trending_repos

GitHub trending repositories

intel_arxiv_papers

arXiv paper search

Health (1)

Tool

Description

intel_disease_outbreaks

WHO DON, ProMED, CIDRAP outbreaks

Social & Sanctions (3)

Tool

Description

intel_social_signals

Reddit geopolitical discussion velocity

intel_sanctions_search

OFAC SDN list search

intel_nuclear_monitor

Seismic monitoring near nuclear test sites

Shipping & Trade (1)

Tool

Description

intel_shipping_index

Dry bulk shipping stress index

Government (1)

Tool

Description

intel_usa_spending

USAspending.gov federal contracts

Country Intelligence (3)

Tool

Description

intel_country_brief

Quick country situation summary

intel_country_stocks

Stock exchanges and listings by country

intel_financial_centers

Global financial centers ranking

Extended Geospatial (1)

Tool

Description

intel_cloud_regions

Cloud provider regions worldwide

Traffic (2)

Tool

Description

intel_traffic_flow

Road traffic flow data

intel_traffic_incidents

Real-time traffic incidents

Cross-Domain Alerts (2)

Tool

Description

intel_alert_digest

Cross-domain alert aggregation

intel_weekly_trends

Weekly trend analysis

Monitoring (2)

Tool

Description

intel_webcams

Public webcam locations and live previews

intel_status

Server health, cache stats, circuit breaker status

Vector Search (5)

Tool

Description

intel_semantic_search

Natural language search across all accumulated intelligence

intel_similar_events

Find events similar to a given data point

intel_timeline

Chronological view of intelligence for a domain/category

intel_vector_stats

Vector store collection statistics

intel_collect

Trigger an on-demand collection cycle

Cross-Domain Analytics (3)

Tool

Description

intel_cross_correlate

Find correlated signals across all domains for a given topic

intel_domain_summary

Per-category summary of stored intelligence (counts, sources, recency)

intel_trend_detection

Detect activity surges/drops by comparing recent vs baseline periods

Reports (1)

Tool

Description

intel_generate_report

Generate a PDF or HTML intelligence report covering 18 domains in parallel

AOI Geofences (5)

Tool

Description

intel_aoi_define

Define a named area of interest: point + radius in km (1-2000)

intel_aoi_list

List all user-defined AOIs

intel_aoi_delete

Delete a user-defined AOI by name

intel_aoi_brief

Cited brief for an AOI: earthquakes, military flights, wildfires, conflict events, aviation, nearby infrastructure, and news mentions, all filtered to the AOI's radius

intel_aoi_escalation

Hotspot escalation scoring (same engine as the 22 built-in hotspots) applied to a user AOI

Situation Brief (1)

Tool

Description

intel_situation_brief

Cited situational awareness brief, generated on demand over MCP: a bounded server-side overview (earthquakes, military flights, ACLED conflict events, wildfires, cyber threats, disease outbreaks, news, space weather, strategic posture, alert digest), synthesized via local Ollama or a mechanically-cited fallback when Ollama is unreachable


Watching your own area (geofences/AOIs)

Static infrastructure results (bases, ports, nuclear, cables, datacenters, spaceports) draw on this repo's curated strategic datasets, which are global and deliberately sparse, not exhaustive local registries. A quiet AOI brief means nothing from those curated sets is in range, not that your area has no infrastructure.

Before the AOI family, only intel_signal_convergence accepted a real point-plus-radius, intel_military_flights took a bbox, and hotspot escalation scoring was restricted to the 22 hardcoded INTEL_HOTSPOTS. The intel_aoi_* tools let you name your own area (a city, a border region, a facility) and get the same cited, multi-domain treatment. Geofences survive the antimeridian (a Bering Strait or Fiji AOI queries both sides of the dateline), and pipelines/undersea cables are matched as line features via great-circle segment distance, not just by their endpoints.

Define an AOI once, then brief, score, edit, and watch it. Three shapes: a circle (point + radius), a polygon (3-64 vertices, for a border region or strait a radius cannot express), or a corridor (a waypoint route + width, for a shipping lane or supply road):

intel_aoi_define(name="Pittsburgh", lat=40.4406, lon=-79.9959, radius_km=50)
intel_aoi_define_polygon(name="Taiwan Strait", vertices=[[22.5, 118.0], [22.5, 121.5], [26.5, 122.0], [26.5, 118.5]])
intel_aoi_define_corridor(name="Suez Approach", waypoints=[[29.9, 32.55], [27.5, 34.0], [24.0, 36.0]], width_km=80)
intel_aoi_brief(name="Taiwan Strait")
intel_aoi_escalation(name="Pittsburgh")
intel_aoi_update(name="Pittsburgh", radius_km=100)   # resize/rename in place
intel_aoi_changes(name="Suez Approach")  # what entered/left since last sweep
intel_aoi_digest()  # one-call sweep across ALL your areas

The same nine operations are available from the terminal: intel aoi define|define-polygon|define-corridor|list|update|delete|brief|escalation|changes.

Membership is exact for the shape (an event inside a polygon's bounding circle but outside the polygon is excluded); corridor distances are measured to the route. Line-feature infrastructure (pipelines, undersea cables) matches the bounding circle for non-circle shapes, disclosed in data_gaps.

intel_aoi_changes is the alerting primitive: the first call records a baseline, and every later call reports what entered and left the fence per domain, with failed fetches reported as data_gaps rather than counted as departures.

intel_aoi_brief filters every geo-capable domain to the 50 km radius around Pittsburgh: earthquakes, military flights (bbox derived from the radius), wildfires (region-mapped, since NASA FIRMS has no point+radius query), ACLED conflict events, a sample of nearby aviation traffic, nearby static infrastructure (military bases, ports, pipelines, nuclear facilities, undersea cables, datacenters, spaceports) with distances in km, and news headline mentions of "Pittsburgh". Every item in the response carries a [n] citation into a numbered sources list, and data_gaps names any domain that couldn't be scoped to the AOI (for example, wildfires when the AOI falls outside NASA FIRMS's coverage regions, or conflict events when ACLED credentials aren't configured) instead of silently omitting it.

intel_aoi_escalation runs the same baseline/military/conflict/social- unrest scoring engine that powers intel_hotspot_escalation for the 22 built-in hotspots, but scoped to your AOI's own radius instead of a fixed 2-degree window.

AOIs persist in a dedicated table inside the same SQLite cache database the server already uses (~/.cache/world-intel-mcp/cache.db by default, or $WORLD_INTEL_CACHE_DB), so a scheduled agent can watch any named area across restarts with intel_aoi_list / intel_aoi_delete to manage them.


Vector Store

The optional Qdrant vector store accumulates intelligence over time for semantic retrieval. All data fetched through the Fetcher is automatically embedded and stored.

Setup

# 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
intel-collector --daemon --sources aoi --interval 900  # AOI watch only: sweep every geofence every 15 min

The aoi group runs intel_aoi_digest as a sweep: each cycle diffs every defined AOI against its stored snapshot and advances it, so the daemon interval is your geofence watch cadence. Change digests are logged and (when the vector store is enabled) stored for semantic search. Set WORLD_INTEL_AOI_WEBHOOK to get a POST whenever a sweep finds something entered or left a geofence (quiet sweeps never fire); with WORLD_INTEL_AOI_WEBHOOK_FORMAT=text the body is raw markdown with a Title header, which ntfy-style sinks render directly.

Running as a macOS launchd Service

scripts/collector-daemon.sh manages the collector as a launchd agent so it survives reboots. It fills in com.agentic.intel-collector.plist.template with this checkout's own path (resolved from the script's own location, so it works from any clone) and installs the result to ~/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

Semantic Search Examples

Once data accumulates, AI agents can query across all domains:

  • "military activity near Taiwan strait" — finds military flights, naval warnings, theater posture data

  • "cyber threats targeting healthcare" — finds URLhaus, CISA KEV entries related to healthcare

  • "economic indicators suggesting recession" — finds yield curve inversions, macro signals, FRED data

The vector store uses FastEmbed (ONNX-based, BAAI/bge-small-en-v1.5) for embeddings — no GPU required, ~3 second cold start.


Environment Variables

Variable

Required

Description

ACLED_ACCESS_TOKEN

No

ACLED conflict events

NASA_FIRMS_API_KEY

No

Satellite wildfire data

EIA_API_KEY

No

Energy price data

CLOUDFLARE_API_TOKEN

No

Internet outage data

FRED_API_KEY

No

Macro economic data (also used for yield curve)

OPENSKY_CLIENT_ID

No

Military flight fallback

OPENSKY_CLIENT_SECRET

No

Military flight fallback

OLLAMA_API_URL

No

Ollama server for AI-generated briefs (default: http://localhost:11434)

OLLAMA_MODEL

No

Ollama model for AI-generated briefs (default: llama3.2)

WORLD_INTEL_LOG_LEVEL

No

Logging level (default: INFO)

WORLD_INTEL_AOI_WEBHOOK

No

URL POSTed when an AOI sweep finds changes (collector daemon); quiet sweeps don't fire

WORLD_INTEL_AOI_WEBHOOK_FORMAT

No

json (default: title/totals/markdown payload) or text (raw markdown body + Title header, ntfy-style)

Everything else uses free, unauthenticated public APIs.


Development

pip install -e ".[dev]"
pytest                       # 900 tests (918 total, 18 live-network smoke tests deselected by default)
pytest --cov=world_intel_mcp # with coverage
pytest tests/test_forex.py -v # single module

Adding a New Source

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

  2. Use fetcher.get_json(url, source="your-source", cache_key=..., cache_ttl=300) — automatic caching, retries, circuit breaking, rate limiting

  3. In server.py: add Tool(...) to TOOLS, add case to _dispatch() (use inline import)

  4. Add tests using respx to mock HTTP (see tests/test_forex.py for pattern)

  5. Optionally add to dashboard/app.py (SSE) and cli.py (Click)


License

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

Resources

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