langchain-nestdaddy

Give your AI today's internet. Live web search, real-time breaking news from around the world and full page reading for LangChain agents and RAG pipelines, from NestDaddy's own index.

pip install -U langchain-nestdaddy
export NESTDADDY_API_KEY="your-key"   # free trial key: https://nestdaddy.com/mcp

Give an agent live search and news

from langchain.agents import create_agent
from langchain_nestdaddy import NestDaddyNewsSearch, NestDaddyReadPage, NestDaddySearch

agent = create_agent(
    "anthropic:claude-sonnet-5-5",
    tools=[NestDaddySearch(max_results=5), NestDaddyNewsSearch(days=7), NestDaddyReadPage()],
    system_prompt="Use news search for anything recent, web search for everything else. "
                  "Read a page in full before you explain its details.",
)

result = agent.invoke({"messages": [{"role": "user", "content": "What did the Fed decide this week?"}]})
print(result["messages"][-1].content)

Any chat model that supports tool calling works the same way.

Use the tools directly

from langchain_nestdaddy import NestDaddyNewsSearch, NestDaddySearch, NestDaddyReadPage

NestDaddySearch(max_results=3).invoke({"query": "model context protocol"})
# {'query': 'model context protocol', 'count': 3, 'results': [{'title': ..., 'url': ..., 'snippet': ...}]}

NestDaddyNewsSearch().invoke({"query": "interest rates", "country": "US", "days": 7})
# {'query': 'interest rates', 'count': 10, 'total': ..., 'results': [{'title': ..., 'source_domain': ...,
#   'published_timestamp': ..., 'summary': ...}]}

NestDaddyReadPage(max_chars=8000).invoke({"url": "https://example.com/some-article"})
# {'title': ..., 'final_url': ..., 'text': ...}

Local news works in the local language: NestDaddyNewsSearch().invoke({"query": "banjir Jakarta", "country": "ID"}).

RAG over today's news

from langchain_nestdaddy import NestDaddyNewsRetriever

retriever = NestDaddyNewsRetriever(k=5, days=3, full_text=True)
docs = retriever.invoke("chip export rules")

for d in docs:
    print(d.metadata["title"], d.metadata["url"], d.metadata["published_timestamp"])
    print(d.page_content[:300])

With full_text=True each article is read in full (one extra API call per article). If an article cannot be read, its summary is kept so you still get k documents.

Async

Every tool and the retriever support ainvoke; the retriever reads full articles in parallel.

docs = await NestDaddyNewsRetriever(k=5, full_text=True).ainvoke("AI regulation")

Errors

API errors raise NestDaddyAPIError with the HTTP status and a hint (a bad key points to the dashboard, a plan limit to the plans page). Your key is stored as a SecretStr and never printed.

Prefer MCP?

The same tools are available as a remote MCP server for Claude, Cursor, VS Code and n8n: https://mcp.nestdaddy.com/mcp. Setup: nestdaddy.com/mcp.

Development

pip install -e ".[test]"
pytest tests/unit_tests --disable-socket --allow-unix-socket   # offline
NESTDADDY_API_KEY=... pytest -m integration tests/integration_tests

MIT licensed.