langchain-specstream

Give your LangChain agent any list from the live web. Search tools hand an agent pages to read; SpecStream hands it the finished list. It asks in plain words – "dental clinics in Lisbon with online booking", "US startups that filed a $5M+ Form D this week" – and gets back every matching row, each with the page it was read from. The list starts only within a price you set in code, and the model can't raise it.

pip install -U langchain-specstream
export SPECSTREAM_API_KEY=ss_live_...   # Agents & API in your SpecStream workspace

A free account comes with $10 of work to use within 30 days and needs no card: specstream.ai.

An agent that can find lists

from langchain.agents import create_agent
from langchain_specstream import specstream_tools

agent = create_agent(
    "anthropic:claude-sonnet-5-5",
    tools=specstream_tools(max_price_usd=5),
)
agent.invoke({"messages": [{"role": "user", "content":
    "Find US startups that raised $5M or more in a Form D filed after October 8, 2026. Which industries lead?"}]})

The agent writes the request and picks how many rows. You decide what one list may cost.

What comes back

One flat row per match: the list's own columns, then where the row was read. This is a real row from the request above.

{
  "list_id": "fnd_gk5y3d0r97bvyz0t08zzh75kr6",
  "position": 26,
  "Organization": "RapidCanvas Inc",
  "Published address": "801 BARTON SPRINGS RD, AUSTIN, TEXAS, 78704",
  "Source industry classification": "Other Technology",
  "Amount sold (USD)": "28999988",
  "Funding filing date": "2026-10-14",
  "source_url": "https://www.sec.gov/Archives/edgar/data/2052031/000205203126000006/primary_doc.xml",
  "checked_at": "2026-10-14T19:56:02.016693Z",
  "list_link": "https://specstream.ai/workspace/collections/fnd_gk5y3d0r97bvyz0t08zzh75kr6"
}

Columns follow the request. Ask for "breweries in Portland, Oregon that host events, with their website" and the rows carry the brewery and its website instead. A fact a source doesn't publish comes back empty, never guessed.

The two tools

When the price is above your maximum, nothing runs: the tool returns the price, so the agent can ask for fewer rows or tell the user. When a request is too vague to price ("clinics"), it returns how SpecStream read it, so the agent can add the place or the conditions.

Use the classes directly when you want different settings per tool:

from langchain_specstream import SpecStreamFindList, SpecStreamGetListResults

find = SpecStreamFindList(max_price_usd=20, wait_seconds=600)
results = SpecStreamGetListResults()

As a retriever

from langchain_specstream import SpecStreamRetriever

retriever = SpecStreamRetriever(max_price_usd=3, max_results=25)
docs = retriever.invoke("Breweries in Portland, Oregon that host events, with their website")

docs[0].page_content          # "Business location: Occidental Brewing Company\nPublished business website: http://occidentalbeers.com ..."
docs[0].metadata["source_url"]  # the page that row was read from

One document per row, its facts as text and its source in the metadata, so a chain can cite every claim. Above the maximum, the retriever raises SpecStreamError and nothing runs.

Money, plainly

• max_price_usd lives on the tool, in your code. The model never sees it and can't change it.
• You pay for rows that match. Candidates SpecStream couldn't confirm are left out and aren't billed.
• A retried step asking for the same list within the hour gets the list it already started, not a second bill.
• Rates and plans: specstream.ai/pricing.

When to reach for it

When the answer is many things that meet conditions: companies in a city, clinics with a service, funding filings, open grants, tenders, repositories, people in a role. For a single fact or a summary of one page, a search tool fits better.

More

• SpecStream docs and the LangChain page
• Agents outside LangChain: the MCP server at https://api.specstream.ai/mcp
• The Python SDK for everything else in the API
• Questions: support@specstream.ai

MIT licensed. Made by SpecStream, the live web data engine for teams and agents.