Gnews Agent
БесплатноНе проверенA persistent news intelligence MCP server that enables AI agents to fetch, store, deduplicate, embed, and semantically query news from Google News across 141 co
Описание
A persistent news intelligence MCP server that enables AI agents to fetch, store, deduplicate, embed, and semantically query news from Google News across 141 countries and 41 languages.
README
Persistent, semantic news intelligence layer for AI agents — built on top of GNews (106k+ monthly PyPI downloads, 141 countries, 41 languages).
The journalism layer your AI agent is missing. Fetch published news from Reuters, BBC, AP, TechCrunch, and the 141-country Google News graph; dedup it; embed it; store it persistently; and query it semantically — over a Python API, a CLI, or an MCP server that drops straight into Claude.
Table of Contents
Installation
pip install gnews-agent
Optional extras:
pip install "gnews-agent[openai]" # OpenAI embedding backend
pip install "gnews-agent[fulltext]" # full-article extraction via trafilatura
pip install "gnews-agent[lance]" # LanceDB vector backend
pip install "gnews-agent[qdrant]" # Qdrant server backend
pip install "gnews-agent[evals]" # DeepEval + Langfuse (v2)
Verify the install:
gnews-agent --version
gnews-agent stats # → {"total_articles": 0, ...}
Usage
The library exposes the same six capabilities through every surface:
ingest, search, timeline, brief, sentiment, stats. Pick the
surface that matches how the rest of your system already works.
CLI
gnews-agent ingest "OpenAI" --method get_news
gnews-agent search "GPT-5 safety" --days 7 --limit 5
gnews-agent brief "OpenAI this week" --days 7
gnews-agent sentiment "Tesla" --days 14 --timeline
gnews-agent timeline "OpenAI" --days 30
gnews-agent stats
gnews-agent serve --transport stdio
Every command emits JSON to stdout. Use --no-pretty for one-line output
(pipe through jq or feed straight into another agent).
MCP server
gnews-agent serve exposes five tools — search_news, get_brief,
get_sentiment, get_timeline, monitor_topic — and three resources —
news://latest/{topic}, news://sentiment/{topic},
news://timeline/{topic}. Works in any MCP client.
Claude Code (CLI):
claude mcp add gnews-agent -- gnews-agent serve --transport stdio
Then ask Claude:
"Use gnews-agent to ingest the latest reporting on OpenAI, then give me a cited brief on what changed this week."
Claude Desktop / Cursor / Windsurf:
Add this block to ~/Library/Application Support/Claude/claude_desktop_config.json
(macOS) or the platform equivalent:
{
"mcpServers": {
"gnews-agent": {
"command": "gnews-agent",
"args": ["serve", "--transport", "stdio"],
"env": {
"ANTHROPIC_API_KEY": "sk-ant-...",
"GNEWS_AGENT_LLM_PROVIDER": "anthropic",
"GNEWS_AGENT_LLM_MODEL": "claude-3-5-haiku-latest"
}
}
}
}
Restart the client. If gnews-agent isn't on $PATH, use the absolute
path from which gnews-agent.
HTTP transport (LangGraph, custom agents):
gnews-agent serve --transport http --port 8000
Claude Code skill
The /gnews skill wraps the MCP server with prompt scaffolding and a
citation-formatted output template.
/plugin marketplace add ranahaani/gnews-agent
/gnews OpenAI this week
/gnews Pakistan economy sentiment
/gnews Tesla vs Rivian coverage last 30 days
Requires pip install gnews-agent on the same machine.
Python library
Drop into any LangGraph, CrewAI, or vanilla Python pipeline.
from gnews_agent import NewsMemory
memory = NewsMemory() # SQLite + Chroma, persistent
memory.ingest("OpenAI", method="get_news") # fetch + dedup + embed + store
results = memory.search("GPT-5 safety", days=7) # semantic re-ranked by recency
timeline = memory.timeline("OpenAI", days=30) # SQL-only
brief = memory.brief("OpenAI this week", days=7) # cited LLM summary
sentiment = memory.sentiment("Tesla", days=14)
print(memory.stats())
NewsMemory accepts a NewsMemoryConfig for full control over paths,
embedder, vector backend, and LLM provider:
from gnews_agent import NewsMemory, NewsMemoryConfig
cfg = NewsMemoryConfig(
db_path="~/news/news.db",
vector_path="~/news/chroma",
embed_model="all-MiniLM-L6-v2",
llm_provider="anthropic",
llm_model="claude-3-5-haiku-latest",
)
memory = NewsMemory(config=cfg)
Configuration
search, ingest, timeline, and stats are keyless — they only need
GNews (free, no API key) and local storage. brief and sentiment are
LLM-powered and need a provider key.
| Variable | Used by | Notes |
|---|---|---|
OPENAI_API_KEY |
brief, sentiment, gnews-agent[openai] embeddings |
Pass via env or LLMConfig. |
ANTHROPIC_API_KEY |
brief, sentiment |
Recommended for higher TPM on the free tier. |
GROQ_API_KEY |
brief, sentiment |
Cheapest + fastest; tighter token-per-minute limits. |
GEMINI_API_KEY |
brief, sentiment |
|
GNEWS_AGENT_LLM_PROVIDER |
CLI default for --llm-provider |
anthropic / openai / groq / gemini / ollama. |
GNEWS_AGENT_LLM_MODEL |
CLI default for --llm-model |
Provider-qualified or bare model id. |
GNEWS_AGENT_HOME |
Docker entrypoint | Mounts /data for SQLite + Chroma persistence. |
Copy .env.example to .env and fill in only the keys
you need. Ollama runs locally with no key at all.
Docker
cd docker
docker compose up --build
# HTTP MCP listening on http://localhost:8000
The image pre-downloads all-MiniLM-L6-v2 at build time so the first
ingest doesn't pay the ~80MB cold-start.
Design notes
- Dedup key =
sha256(title_slug + "|" + publisher_norm). URL is excluded because Google News surfaces the same article under multiple URL variants (locale params, tracking suffixes, redirector vs resolved). Title-slug + publisher catches those without merging legitimately distinct outlets. - No semantic cosine dedup at ingestion. Reuters and BBC reporting
the same event are kept as separate rows. Cosine similarity is
reserved for query-time re-ranking inside
brief(). - Embedding model + dimension are recorded on every vector row. The
store refuses cross-model queries via
EmbeddingDimMismatchError. To switch from sentence-transformers to OpenAI embeddings, use a separatevector_pathor wipe the existing collection. - Story clustering is v2.
brief()ranks by recency + similarity and passes the top-N to the LLM, no clustering. - Webhook URL validation for
monitor_topic. RFC1918, loopback, link-local, and cloud-metadata IPs are refused. HTTPS required in MCP-exposed mode. - GNews ≥0.8.2 is required for the built-in 429 retry +
exponential backoff.
gnews-agentlayers per-topic 1s spacing and topic cooldown on top of that.
Status
- v0.1.0 — Library + CLI + MCP server + Claude Code skill scaffold. End-to-end ingest → search → brief works against a real LLM key. 83 unit + 24 integration tests pass.
- v2 deferred — DeepEval
FaithfulnessMetric, Langfuse tracing, CI eval gate, story clustering,get_entitiesMCP tool, Telegram/Slack/Email alert channels, LanceDB + Qdrant backends, multi-language summaries.
Pairs well with /last30days
/last30days searches what people say (Reddit, X, YouTube, TikTok,
Hacker News). gnews-agent searches what journalism reports
(Reuters, BBC, AP, TechCrunch). Different signals from different
sources:
/last30days OpenAI GPT-5 → social signal
/gnews OpenAI GPT-5 → published record
Install both and ask Claude to combine them for the full picture.
License
MIT — see LICENSE.
Установка Gnews Agent
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/ranahaani/gnews-agentFAQ
Gnews Agent MCP бесплатный?
Да, Gnews Agent MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Gnews Agent?
Нет, Gnews Agent работает без API-ключей и переменных окружения.
Gnews Agent — hosted или self-hosted?
Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.
Как установить Gnews Agent в Claude Desktop, Claude Code или Cursor?
Открой Gnews Agent на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
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