pydantic-ai-specstream

SpecStream is the live web data engine for teams and agents. One platform to build, search, extract, enrich, map, and monitor data across the entire web.

Ask for any dataset in plain words, and SpecStream builds it from the entire live web: every match found, extracted and enriched into structured records, then monitored for change. It runs through the API and MCP, and inside Sheets, CRMs, Slack, n8n, Zapier and the other tools teams already use.

Source URL and read time on every value.

Three products:

1. Search API: GET /v1/web-search, $5 per 1,000 searches of up to 10 results. The most accurate web search API in the world (scores and method: https://specstream.ai/benchmarks).
2. Extract API: POST /v1/extract, up to 20 URLs a call (web pages, PDF, Word, Excel), $0.80 per 1,000 pages. A page with no text is not charged.
3. Deep Search: Ask in plain words. Get every match on the live web, in structured rows. Priced per row.

Install

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

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

Use it as a capability

from pydantic_ai import Agent
from pydantic_ai_specstream import SpecStreamCapability

agent = Agent('openai:gpt-5', capabilities=[SpecStreamCapability()])

result = agent.run_sync('Who won the 2025 Nobel Prize in Physics? Read the announcement page and quote one line.')
print(result.output)

The example needs SPECSTREAM_API_KEY and a model, here pip install "pydantic-ai-slim[openai]" with OPENAI_API_KEY. Any Pydantic AI model works.

SpecStreamCapability gives the agent the specstream_search and specstream_extract tools and instructions for when to call each. A call the API refuses as bad input goes back to the model as a ModelRetry, so the model corrects it. Every other failure raises SpecStreamError.

It also loads from an agent spec:

# agent.yaml
model: openai:gpt-5
capabilities:
  - SpecStreamCapability:
      passages: true

from pydantic_ai import Agent
from pydantic_ai_specstream import SpecStreamCapability

agent = Agent.from_file('agent.yaml', custom_capability_types=[SpecStreamCapability])

Tools and toolset

Each function takes api_key (default: the SPECSTREAM_API_KEY environment variable), base_url and a shared httpx.AsyncClient as client. A failed call raises SpecStreamError with the API message.

MIT licensed.