LangChain

The langchain-context package exposes Context.dev operations as LangChain BaseTool classes. Use individual tools directly or give an agent a focused toolkit for live web research, scraping, crawling, extraction, document parsing, brand intelligence, monitors, and batch jobs.

View Context.dev for LangChain

Inspect the package source, examples, tests, and releases.

Prerequisites

Python 3.10 through 3.14
A Context.dev account with an API key and credits for tool calls

Install and configure

Install the package

pip install -U langchain-context

Set your API key

Copy a secret key from the Context.dev dashboard, then set it in your server environment:

export CONTEXT_API_KEY="ctxt_secret_your_key"

Tools read CONTEXT_API_KEY automatically. You can also pass api_key to a tool or toolkit when your application already manages secrets securely.

Keep CONTEXT_API_KEY in your server environment. Do not commit it or expose it in browser code.

Use a tool directly

Every Context.dev operation supports LangChain’s synchronous invoke interface:

from langchain_context import ContextScrape, ContextSearch

search = ContextSearch()
results = search.invoke(
    {
        "query": "latest official Stripe product announcements",
        "includeDomains": ["stripe.com"],
        "numResults": 10,
    }
)

scrape = ContextScrape()
page = scrape.invoke({"url": "https://stripe.com/newsroom"})

To read a YouTube video, pass its URL to ContextScrape. The returned Markdown includes the timestamped transcript when one is available.

Give tools to an agent

ContextToolkit is safe by default: it includes read operations and removes browser actions from scraping tools. Pass its result to any LangChain agent that accepts a list of tools.

from langchain_context import ContextToolkit

context_tools = ContextToolkit(
    groups=("web", "brand"),
).get_tools()

Choose only the groups the agent needs:

Group	Includes
`web`	Search, Markdown and HTML scraping, YouTube transcripts, crawling, extraction, screenshots, sitemaps, and document parsing
`brand`	Brand profiles, style guides, fonts, and industry classification
`monitors`	Read existing monitors, runs, changes, and credit usage
`batches`	Read existing batch jobs and results

Use a focused toolkit when you do not need every group:

from langchain_context import ContextBrandToolkit, ContextWebToolkit

web_tools = ContextWebToolkit().get_tools()
brand_tools = ContextBrandToolkit().get_tools()

Enable side effects explicitly

Monitor and batch mutations are excluded unless you opt in. Browser actions are also removed from scraping tools by default.

from langchain_context import ContextToolkit

tools = ContextToolkit(
    include_write_tools=True,
    allow_browser_actions=True,
).get_tools()

Enable these options only for an agent that should create, update, run, cancel, or delete Context.dev resources or interact with third-party webpages.

Use async tools

Every tool also supports LangChain’s asynchronous ainvoke interface:

from langchain_context import ContextSearch

result = await ContextSearch().ainvoke(
    {"query": "latest Context.dev product announcements"}
)

Troubleshooting

Symptom	Fix
`CONTEXT_API_KEY` is missing	Set the environment variable before starting the application, or pass `api_key` securely.
Context.dev returns an authentication error	Replace the key with an active secret key from the Context.dev dashboard.
A mutating tool is not available	Set `include_write_tools=True` only when the agent should change monitors or batches.
Scraping does not expose browser actions	Set `allow_browser_actions=True` only when interactive browsing is required.
Calls fail for insufficient credits	Review usage in the Context.dev dashboard.

Reference

PyPI package

Install the current release and review its Python requirements.

Package source

Read the complete tool catalog, examples, and test suite.

LangChain tools

Learn how tools are defined, invoked, and attached to agents.

Context.dev API reference

Review the underlying API operations and request schemas.

AI chat

Frameworks

No-code tools

View Context.dev for LangChain

Prerequisites

Install and configure

Use a tool directly

Give tools to an agent

Enable side effects explicitly

Use async tools

Troubleshooting

Reference

PyPI package

Package source

LangChain tools

Context.dev API reference

View Context.dev for LangChain

​Prerequisites

​Install and configure

​Use a tool directly

​Give tools to an agent

​Enable side effects explicitly

​Use async tools

​Troubleshooting

​Reference

PyPI package

Package source

LangChain tools

Context.dev API reference

Prerequisites

Install and configure

Use a tool directly

Give tools to an agent

Enable side effects explicitly

Use async tools

Troubleshooting

Reference