langchain-bowmark

LangChain tools for Bowmark. Bowmark turns websites into typed functions an AI agent can call: search, prices, availability, quotes, bookings, reading a page. Your agent looks up the functions it needs, writes a short script against them, and Bowmark runs it on the live sites and returns structured data. The agent never drives a browser itself.

Full guide: bowmark.ai/docs/langchain

Install

pip install langchain-bowmark

Create an API key at bowmark.ai/dashboard/keys and export it:

export BOWMARK_API_KEY="bmk_..."

Tools

BowmarkToolkit returns both, sharing one key.

Use with an agent

from langchain.agents import create_agent
from langchain_bowmark import BowmarkToolkit

agent = create_agent(
    "openai:gpt-5.6-luna",
    tools=BowmarkToolkit().get_tools(),
    system_prompt=(
        "You can act on live websites through Bowmark. Call bowmark_get_library with what "
        "the user wants to do, write a short script against the functions it returns, and "
        "execute it with bowmark_run. Answer from the run's result."
    ),
)

result = agent.invoke(
    {"messages": [{"role": "user", "content": "What is the top story on Hacker News right now?"}]}
)
print(result["messages"][-1].content)

Call the tools directly

from langchain_bowmark import BowmarkGetLibrary, BowmarkRun

print(BowmarkGetLibrary().invoke({"query": "read a web page"}))
print(BowmarkRun().invoke({"script": 'return (await bowmark.read.page("https://example.com")).title;'}))

Development

uv venv && uv pip install -e . --group test
pytest tests/unit_tests
BOWMARK_API_KEY=... pytest tests/integration_tests

License

MIT