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\n

@cyanheads/gdelt-mcp-server

\n

Search and analyze global news coverage and US television transcripts via the GDELT Project's real-time APIs via MCP. STDIO or Streamable HTTP.\n

9 Tools
\n

\n
\n\n
\n\n[![Version](https://img.shields.io/badge/Version-0.6.0-blue.svg?style=flat-square)](./CHANGELOG.md) [![License](https://img.shields.io/badge/License-Apache%202.0-orange.svg?style=flat-square)](./LICENSE) [![Docker](https://img.shields.io/badge/Docker-ghcr.io-2496ED?style=flat-square&logo=docker&logoColor=white)](https://github.com/users/cyanheads/packages/container/package/gdelt-mcp-server) [![MCP SDK](https://img.shields.io/badge/MCP%20SDK-^2.0.0-green.svg?style=flat-square)](https://modelcontextprotocol.io/) [![npm](https://img.shields.io/npm/v/@cyanheads/gdelt-mcp-server?style=flat-square&logo=npm&logoColor=white)](https://www.npmjs.com/package/@cyanheads/gdelt-mcp-server) [![TypeScript](https://img.shields.io/badge/TypeScript-^7.0.2-3178C6.svg?style=flat-square)](https://www.typescriptlang.org/) [![Bun](https://img.shields.io/badge/Bun-v1.4.0-blueviolet.svg?style=flat-square)](https://bun.sh/)\n\n
\n\n
\n\n[![Install in Claude Desktop](https://img.shields.io/badge/Install_in-Claude_Desktop-D97757?style=for-the-badge&logo=anthropic&logoColor=white)](https://github.com/cyanheads/gdelt-mcp-server/releases/latest/download/gdelt-mcp-server.mcpb) [![Install in Cursor](https://cursor.com/deeplink/mcp-install-dark.svg)](https://cursor.com/en/install-mcp?name=gdelt-mcp-server&config=eyJjb21tYW5kIjoibnB4IiwiYXJncyI6WyIteSIsIkBjeWFuaGVhZHMvZ2RlbHQtbWNwLXNlcnZlciJdfQ==) [![Install in VS Code](https://img.shields.io/badge/VS_Code-Install_Server-0098FF?style=for-the-badge&logo=visualstudiocode&logoColor=white)](https://vscode.dev/redirect?url=vscode:mcp/install?%7B%22name%22%3A%22gdelt-mcp-server%22%2C%22command%22%3A%22npx%22%2C%22args%22%3A%5B%22-y%22%2C%22%40cyanheads%2Fgdelt-mcp-server%22%5D%7D)\n\n[![Framework](https://img.shields.io/badge/Built%20on-@cyanheads/mcp--ts--core-67E8F9?style=flat-square)](https://www.npmjs.com/package/@cyanheads/mcp-ts-core)\n\n
\n\n
\n\n**Public Hosted Server:** [https://gdelt.caseyjhand.com/mcp](https://gdelt.caseyjhand.com/mcp)\n\n
\n\n---\n\n## Overview\n\nNews and television coverage analysis from the GDELT Project's DOC and TV APIs — the last 3 months of global news in 65+ languages, and US TV transcripts from 2009 through October 2024 across 150+ stations. Search articles and clips, track coverage spikes, analyze tone, and trace how a story propagated across languages and countries. Runs as a stdio process, a local Streamable HTTP server, or the public hosted endpoint above.\n\n### Tools\n\n| Tool | Description |\n|:---|:---|\n| `gdelt_search_articles` | Search the last 3 months of global news coverage (65+ languages) with full-text and filter operators. Fetches up to 250 articles, returns as many as fit a 48,000-byte response, and hands back the date windows to re-query for the rest. |\n| `gdelt_get_coverage_timeline` | Retrieve a time series of coverage volume or average tone for a query. `volume_with_articles` mode includes top articles per spike timestep, with `points` to render a timestep's full article list. |\n| `gdelt_get_tone_distribution` | Get a tone histogram (bins ~−30 to +30) showing whether coverage is uniformly negative, bimodal, or clustered near neutral. |\n| `gdelt_get_coverage_breakdown` | Break down coverage volume by source language or source country — a multi-series time series showing geographic propagation. Values are normalized shares of media output, not article counts. |\n| `gdelt_search_themes` | Find GKG theme identifiers for the `theme:` operator the DOC tools accept — `drought` finds `NATURAL_DISASTER_DROUGHT`, `cyberattack` finds `CYBER_ATTACK` — ranked by the count GDELT's theme lookup lists. |\n| `gdelt_search_tv` | Search US television news closed captions (2009–Oct 2024) and return per-station airtime time series. |\n| `gdelt_get_tv_clips` | Retrieve matching TV clips with transcript excerpts and Internet Archive viewing links — up to 3,000 fetched, as many as fit a 48,000-byte response returned — and the date windows to re-query for the rest. |\n| `gdelt_get_tv_context` | Get the most frequent co-occurring words and phrases from TV clips matching a query. |\n| `gdelt_list_tv_stations` | List TV stations with market, network, and monitoring date ranges — all of them, or filtered by station ID, network, or market — to verify station availability before querying. |\n\n## Capability reference\n\n### `gdelt_search_articles` tool\n\n- Full GDELT query syntax: phrases, boolean OR, exclusion, filter operators (`sourcecountry:`, `sourcelang:`, `domain:`, `theme:`, `tone<`/`tone>`), proximity (`near20:`) and repetition (`repeat3:`) — `gdelt_search_themes` finds the identifiers `theme:` takes\n- Configurable sort (`relevance`, `dateDesc`, `dateAsc`, `toneDesc`, `toneAsc`, `hybridRel`) and fetch count, up to 250 per call\n- Returns URL, title, publication date, domain, language, source country, and social image URL\n- Each response carries as many fetched articles as fit a 48,000-byte budget on each surface; the rest are counted in `withheldCount`, and the notice says how to reach them — never by raising `maxRecords`\n- `continuationWindows` on a page cut under `dateDesc`/`dateAsc` holds one window resuming from the last returned article — or skipping past its second when resuming there cannot reach a new article; under the other sorts, and whenever `maxRecords` sits at its 250 ceiling, it holds the queried window halved and overlapping by a second so nothing falls through the seam. Articles on a boundary second can come back twice — de-duplicate by `url`\n- Articles GDELT returns from outside an explicit `startDatetime`/`endDatetime` window are dropped, and the notice counts them\n- 250 is a hard per-call ceiling, not a page size — GDELT exposes no cursor, so narrowing the date window is the only way past it\n\n---\n\n### `gdelt_get_coverage_timeline` tool\n\n- Three modes: `volume` (normalized % per timestep), `volume_with_articles` (volume plus top articles per spike — signal detection in one call), `tone` (average sentiment per timestep)\n- Every article reference is always in `structuredContent`; the text surface renders the first 3 links per timestep beside that timestep's true count, and `points: [\"\"]` renders named timesteps in full\n- Configurable smoothing (0–5 timesteps) and time range (`timespan`, or explicit `startDatetime`/`endDatetime`)\n- Date resolution (`15min`/`hour`/`day`) is inferred from the returned intervals, and omitted when fewer than two timesteps come back\n- A `points` date matching no timestep is rejected with the available timestep list, rather than silently ignored\n\n---\n\n### `gdelt_get_tone_distribution` tool\n\n- Histogram bins from approximately −30 to +30; each bin includes representative article URLs\n- Summary fields: `peakNegativeBin`, `peakPositiveBin`, `neutralPct` (% of articles in the −2 to +2 range)\n- A snapshot across all matching articles — distinct from the tone timeline (`gdelt_get_coverage_timeline` mode `tone`), which is a time series\n\n---\n\n### `gdelt_get_coverage_breakdown` tool\n\n- Breaks down by `language` or `country` into a multi-series time series\n- Top 10 series by total volume; the rest aggregate into `otherAggregated`, with every folded-in label named in `otherSeriesLabels`\n- Pass any label to `series: [\"