mcpbeat

Gdelt MCP Server

io.github.cyanheads/gdelt-mcp-server
answering

Gdelt MCP Server is answering right now. Last checked 5 min ago. 186 installs a week from npm. It exposes 9 tools. Last commit 24 Jul 2026.

Search and analyze global news coverage and US TV transcripts via the GDELT Project APIs.

Installs per day peak 506 · avg 46 · -46% w/w
a month agotoday
Uptime history 40 hours of history · worst hour 75%
40 hours agonow
100.0%
Uptime 24h
91 of 91 checks
9
Tools
read from the server
370 ms
Response time
average over 24h
186
Installs / week
npm and PyPI

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 5 min ago.

run in your terminal
claude mcp add gdelt-mcp-server --transport http https://gdelt.caseyjhand.com/mcp
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "gdelt-mcp-server": {
      "url": "https://gdelt.caseyjhand.com/mcp"
    }
  }
}
~/.codex/config.toml
[mcp_servers.gdelt-mcp-server]
url = "https://gdelt.caseyjhand.com/mcp"
.cursor/mcp.json
{
  "mcpServers": {
    "gdelt-mcp-server": {
      "url": "https://gdelt.caseyjhand.com/mcp"
    }
  }
}
.vscode/mcp.json
{
  "mcpServers": {
    "gdelt-mcp-server": {
      "url": "https://gdelt.caseyjhand.com/mcp"
    }
  }
}

Available tools 9

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

gdelt
gdelt_get_coverage_breakdown
Break down news coverage volume over time by source language or source country, returning a multi-series time series (one series per language or country). Shows which countries or languages drove early vs. late coverage — useful for tracing how a story propagated geographically or across language communities. Returns up to 10 series by total volume and aggregates the rest into an "Other" bucket, naming every series it folded in there under otherSeriesLabels — pass any of those labels back as the series input to get that series complete, ranked or not. Values are normalized: each point is the topic's share of media output, not an absolute article count. Small media markets with concentrated coverage therefore rank above large markets with diverse output — a high value means the topic dominated that source's coverage, not that it published the most articles. Use breakdownBy "country" with the signal-detection chain to map geographic attention, or "language" to detect non-English media surges.
gdelt_get_coverage_timeline
Retrieve a time series showing when news coverage of a topic spiked, or how average tone shifted over time. Use mode "volume" for normalized coverage intensity (% of all global coverage per timestep). Use mode "volume_with_articles" for the same signal plus the top articles that drove each spike — this is the primary signal-detection mode: a single call reveals both the spike and its cause, avoiding a follow-up gdelt_search_articles call. Use mode "tone" for average sentiment score per timestep (negative = hostile/fearful, positive = celebratory). Date resolution is automatically chosen based on timespan: hours for short windows, days for longer ones. In volume_with_articles mode the text surface shows the first 3 article links per timestep next to that timestep's true article count; name a timestep's date in points to render its full list. Note: DOC API covers only the last 3 months.
gdelt_get_tone_distribution
Get the tonal distribution of articles matching a query as a histogram (bins approximately -30 to +30). Unlike a single average tone score, the histogram reveals whether coverage is uniformly negative, bimodal (some articles extremely positive and some extremely negative), or clustered near neutral. Each bin includes representative article URLs. Distinct from gdelt_get_coverage_timeline (mode: tone) — this is a snapshot distribution across all matching articles, not a time series. Use gdelt_get_coverage_timeline with mode "tone" to see how sentiment shifted over time.
gdelt_get_tv_clips
Retrieve the top matching TV news clips (up to 3,000) for a query from the Internet Archive's Television News Archive. Each clip includes show name, station, air timestamp, a 15-second transcript excerpt, and a direct link to view the full one-minute clip. Use after gdelt_search_tv to read the actual transcript content driving a coverage spike. 3,000 is a hard per-call ceiling and GDELT offers no cursor: when a query fills it, split the run into narrower startDatetime/endDatetime windows — the response hands back the exact windows to use. Archive coverage spans 2009–October 2024.
gdelt_get_tv_context
Get the top co-occurring words and phrases from TV news clips matching a query — the vocabulary framing a topic on television. Returns the most frequent non-stopword terms from matching clips, with relative frequency scores (0–100, where 100 = the query term itself). Use to understand narrative framing, identify related concepts mentioned alongside a topic, or generate follow-up search terms. TV data spans 2009–October 2024.
gdelt_get_tv_trending
Retrieve trending topics, keywords, and phrases currently dominating US television news across national networks. No query required — returns the top memes of the present news cycle. Updated every 15 minutes. Note: the GDELT TV archive feed stopped updating around October 2024; results from this endpoint reflect that most-recent archived data rather than a live feed.
gdelt_list_tv_stations
List all television stations available for TV search with their market, network, monitoring start date, and monitoring end date. Stations with an end date within the last 24 hours are flagged as active; stations with earlier end dates are discontinued. Use before querying to verify a station was active during the target time period, or to discover valid station IDs for the stations parameter in other TV tools. Most station monitoring ended October 2024 when the Internet Archive TV feed stopped updating.
gdelt_search_articles
Search the last 3 months of global news coverage (65+ languages) using the GDELT DOC API. Returns up to 250 articles with URL, title, source domain, language, country, publication date, and social image URL. Query supports full GDELT syntax: phrases ("bird flu"), boolean OR ((flu OR pandemic)), source country (sourcecountry:china), source language (sourcelang:spanish), domain (domain:who.int), GKG theme (theme:DISEASE_OUTBREAK), tone filter (tone<-5 for negative), proximity (near20:"flu virus"), and repeat (repeat3:"outbreak"). 250 is a hard per-call ceiling and GDELT offers no cursor: when a query fills it, split the run into narrower startDatetime/endDatetime windows — the response hands back the exact windows to use. Note: this API covers only the most recent 3 months — use gdelt_search_tv for historical TV transcripts back to 2009.
gdelt_search_tv
Search US television news closed captions (2009–October 2024, 150+ stations) for spoken mentions of a query. Returns a normalized per-station time series showing relative airtime devoted to the topic. Use the stations parameter to select networks (e.g. ["CNN", "FOXNEWS", "MSNBC"]) — the TV API requires at least one station, supplied either there or as a station: selector inside query. TV query also supports in-query operators: station:CNN, network:CBS, market:"National", show:"Anderson Cooper 360", context:"vaccine". Important: most station monitoring ended October 2024 — use gdelt_list_tv_stations to verify active date ranges before querying recent events.

Endpoints

URLTransportStateLatencyChecked
https://gdelt.caseyjhand.com/mcp streamable-http answering 168 ms 5 min ago

Gdelt MCP Server — questions

Answers built from our own checks of this server.

What can Gdelt MCP Server do?
It exposes 9 tools, read directly from the server on our last check. Among them: gdelt_get_coverage_breakdown, gdelt_get_coverage_timeline, gdelt_get_tone_distribution, gdelt_get_tv_clips, gdelt_get_tv_context, gdelt_get_tv_trending and 3 more. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →
Is Gdelt MCP Server working right now?
We send a real MCP handshake every 15 minutes. Over the last 24 hours 91 of 91 checks got a reply (100.0%), average response time 370 ms. The bar chart above shows every period we have measured.
How do I connect Gdelt MCP Server?
Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.
Does Gdelt MCP Server need an API key?
No. Gdelt MCP Server completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 9 of them are readable on this page. This is what we observed, not what the docs claim.
How fast is Gdelt MCP Server?
It answers our handshake in 370 ms on average, which is faster than 37% of all working MCP servers we measure. The comparison comes from our own checks across the whole registry, every 15 minutes.
How many people use Gdelt MCP Server?
The npm package @cyanheads/gdelt-mcp-server was installed 186 times in the last week. Week over week that is -46%. We show installs rather than GitHub stars on purpose: a star is a bookmark, an install is someone actually running it.
Is Gdelt MCP Server open source?
Yes — it is published under the Apache-2.0 licence, written in TypeScript, 3 stars on GitHub and 3 open issues. The source link is on this page, so you can read exactly what it does with your data before you connect it.