# Context.dev

```json
{
  "name": "Context.dev",
  "slug": "context_dev",
  "url": "https://composio.dev/toolkits/context_dev",
  "markdown_url": "https://composio.dev/toolkits/context_dev.md",
  "logo_url": "https://logos.composio.dev/api/context_dev",
  "categories": [
    "data & analytics"
  ],
  "is_composio_managed": false,
  "updated_at": "2026-10-04T14:47:37.453Z"
}
```

![Context.dev logo](https://logos.composio.dev/api/context_dev)

## Description

Securely connect your AI agents and chatbots (Claude, ChatGPT, Cursor, etc) with Context.dev MCP or direct API to scrape web pages, extract structured data, monitor brand mentions, and gather market intelligence through natural language.

## Summary

Context.dev is a web data API platform for scraping, extraction, brand intelligence, monitoring, and structured web data.
Use it to turn public web pages into clean, AI-ready data without building brittle scrapers.

## Categories

- data & analytics

## Toolkit Details

- Tools: 11

## Images

- Logo: https://logos.composio.dev/api/context_dev

## Authentication

- **Api Key**
  - Type: `api_key`
  - Description: Api Key authentication for Context.dev.
  - Setup:
    - Configure Api Key credentials for Context.dev.
    - Use the credentials when creating an auth config in Composio.

## Suggested Prompts

- Extract pricing data from competitor pages
- Monitor brand mentions across target websites
- Scrape structured data from product pages

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `CONTEXT_DEV_EXTRACT_STRUCTURED_WEB_DATA` | Extract Structured Web Data | Crawl relevant pages from a website and return data matching a caller-provided JSON Schema and extraction instructions. This is a higher-cost metered call; use SCRAPE_WEBPAGE_MARKDOWN when Markdown is sufficient. The verified one-page call consumed 10 Context.dev credits, and cost increases with pages analyzed. |
| `CONTEXT_DEV_GET_BRAND` | Get Brand | Retrieve enriched brand identity, logos, colors, industry, and description using exactly one domain, name, work email, ticker, direct URL, or transaction descriptor. Use SEARCH_BRANDS for inexpensive discovery; this full enrichment normally consumes 10 Context.dev credits. |
| `CONTEXT_DEV_GET_MONITOR_LIMITS` | Get Monitor Limits | Return the connected account's plan and current monitor usage versus its monitor limit. |
| `CONTEXT_DEV_GET_WEBDB_USAGE` | Get WebDB Usage | Return WebDB credit balance, period consumption, row count, storage, and per-collection usage for an optional time range. |
| `CONTEXT_DEV_GET_WEBSITE_STYLEGUIDE` | Get Website Styleguide | Extract a website's colors, typography, spacing, shadows, font assets, and common component styles from either a domain or one direct URL. A successful extraction normally consumes 10 Context.dev credits. |
| `CONTEXT_DEV_LIST_BATCHES` | List Batches | List and filter the connected account's asynchronous web batches from newest to oldest, returning one cursor-controlled page. |
| `CONTEXT_DEV_LIST_MONITORS` | List Monitors | List and filter the connected organization's web monitors, returning one cursor-controlled page. |
| `CONTEXT_DEV_LIST_WEBDB_COLLECTIONS` | List WebDB Collections | List the connected account's WebDB collections and return one cursor-controlled page, including each collection's sources, extraction configuration, status, usage, and timestamps. |
| `CONTEXT_DEV_PARSE_FILE` | Parse File | Convert an uploaded document, image, source file, or data file into LLM-usable Markdown. |
| `CONTEXT_DEV_SCRAPE_WEBPAGE_MARKDOWN` | Scrape Webpage to Markdown | Render one public URL and return its main or CSS-selected content as Markdown. This free-tier tool does not perform paid browser actions. A successful scrape normally consumes one Context.dev credit. |
| `CONTEXT_DEV_SEARCH_BRANDS` | Search Brands | Prefix-search Context.dev's existing brand index by company name or domain and return up to 10 lightweight matches. |

## Supported Triggers

None listed.

## Installation and MCP Setup

### Path 1: SDK Installation

#### Path 1, Step 1: Install Composio

Install the Composio SDK, the OpenAI provider, and the OpenAI SDK
```python
pip install composio composio_openai openai
```

```typescript
npm install @composio/core @composio/openai openai
```

#### Path 1, Step 2: Create a Composio session

Initialize Composio with the OpenAI Responses provider and create a session scoped to Context.dev
```python
import json
from openai import OpenAI
from composio import Composio
from composio_openai import OpenAIResponsesProvider

composio = Composio(provider=OpenAIResponsesProvider())
client = OpenAI()

session = composio.create(user_id="your-user-id", toolkits=["context_dev"])
tools = session.tools()
```

```typescript
import OpenAI from "openai";
import { Composio } from "@composio/core";
import { OpenAIResponsesProvider } from "@composio/openai";

const composio = new Composio({ provider: new OpenAIResponsesProvider() });
const client = new OpenAI();

const session = await composio.create("your-user-id", { toolkits: ["context_dev"] });
const tools = await session.tools();
```

#### Path 1, Step 3: Run Context.dev tools with your agent

Send a request, execute the Context.dev tool calls through the session, and print the final answer
```python
response = client.responses.create(
    model="gpt-5.6-sol",
    tools=tools,
    input=[{"role": "user", "content": "Extract structured pricing data from https://example.com/pricing"}],
)

while True:
    tool_calls = [o for o in response.output if o.type == "function_call"]
    if not tool_calls:
        break
    results = composio.provider.handle_tool_calls(response=response, session=session)
    response = client.responses.create(
        model="gpt-5.6-sol",
        tools=tools,
        previous_response_id=response.id,
        input=[
            {"type": "function_call_output", "call_id": call.call_id, "output": json.dumps(results[i])}
            for i, call in enumerate(tool_calls)
        ],
    )

print(response.output_text)
```

```typescript
let response = await client.responses.create({
  model: "gpt-5.6-sol",
  tools,
  input: [{ role: "user", content: "Extract structured pricing data from https://example.com/pricing" }],
});

while (response.output.some((o) => o.type === "function_call")) {
  const outputs = await composio.provider.handleToolCalls(session, response.output);
  response = await client.responses.create({
    model: "gpt-5.6-sol",
    tools,
    previous_response_id: response.id,
    input: outputs,
  });
}

console.log(response.output_text);
```

### Path 2: MCP Server Setup

#### Path 2, Step 1: Install Composio

Install the Composio SDK and your agent framework
```python
pip install composio claude-agent-sdk
```

```typescript
npm install @composio/core ai @ai-sdk/mcp @ai-sdk/openai
```

#### Path 2, Step 2: Create a session with MCP enabled

Create a session scoped to Context.dev and read its MCP URL and headers
```python
from composio import Composio

composio = Composio()
session = composio.create(user_id="your-user-id", toolkits=["context_dev"], mcp=True)
```

```typescript
import { Composio } from "@composio/core";

const composio = new Composio();
const { mcp } = await composio.create("your-user-id", {
  toolkits: ["context_dev"],
  mcp: true,
});
```

#### Path 2, Step 3: Connect your agent to the MCP server

Pass the session's MCP URL and headers to your agent and run a Context.dev request
```python
import asyncio
from claude_agent_sdk import ClaudeSDKClient, ClaudeAgentOptions, AssistantMessage, TextBlock

options = ClaudeAgentOptions(
    mcp_servers={
        "composio": {
            "type": "http",
            "url": session.mcp.url,
            "headers": session.mcp.headers,
        }
    },
    system_prompt="You are a helpful assistant with access to Context.dev tools.",
    tools=[],
    allowed_tools=["mcp__composio__*"],
)

async def main():
    async with ClaudeSDKClient(options=options) as client:
        await client.query("Extract structured pricing data from https://example.com/pricing")
        async for message in client.receive_response():
            if isinstance(message, AssistantMessage):
                for block in message.content:
                    if isinstance(block, TextBlock):
                        print(block.text)

asyncio.run(main())
```

```typescript
import { createMCPClient } from "@ai-sdk/mcp";
import { openai } from "@ai-sdk/openai";
import { generateText, stepCountIs } from "ai";

const client = await createMCPClient({
  transport: { type: "http", url: mcp.url, headers: mcp.headers },
});

const { text } = await generateText({
  model: openai("gpt-5.6-sol"),
  tools: await client.tools(),
  prompt: "Extract structured pricing data from https://example.com/pricing",
  stopWhen: stepCountIs(10),
});

console.log(text);
await client.close();
```

## Why Use Composio?

### 1. AI Native Context.dev Integration

- Supports both Context.dev MCP and direct API based integrations
- Structured, LLM-friendly schemas for reliable scraping, extraction, and monitoring tasks
- Rich coverage for turning web pages, brand signals, and public data into agent-ready context

### 2. Managed Auth

- Connect Context.dev with your API key once, then let Composio handle secure credential storage
- Use auth_configs.create() and connected_accounts.link() to configure and link Context.dev access without hard-coding secrets
- Manage per user and per environment credentials from one place

### 3. Agent Optimized Design

- Tools are tuned for AI agents, so scraping and extraction calls are easier for models to understand
- Comprehensive execution logs show what URL was scraped, what extraction ran, and on whose behalf
- Works with mcp.create() style MCP workflows as well as direct Tool Router sessions

### 4. Enterprise Grade Security

- Fine-grained RBAC helps you control which agents and users can access Context.dev
- Scoped, least privilege access for web data workflows, brand monitoring jobs, and extraction pipelines
- Full audit trail of agent actions to support review, debugging, and compliance

## Use Context.dev with any AI Agent Framework

Choose a framework you want to connect Context.dev with:

- [ChatGPT](https://composio.dev/toolkits/context_dev/framework/chatgpt)
- [Claude Cowork](https://composio.dev/toolkits/context_dev/framework/claude-cowork)
- [Hermes](https://composio.dev/toolkits/context_dev/framework/hermes-agent)
- [Atomic Agent](https://composio.dev/toolkits/context_dev/framework/atomic-agent)

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## Frequently Asked Questions

### Do I need my own developer credentials to use Context.dev with Composio?

Yes, Context.dev requires you to configure your own API key. Once set up, Composio handles secure credential storage and API request handling for you.

### Can I use multiple toolkits together?

Yes! Composio's Tool Router enables agents to use multiple toolkits. [Learn more](https://docs.composio.dev/tool-router/overview).

### Is Composio secure?

Composio is SOC 2 and ISO 27001 compliant with all data encrypted in transit and at rest. [Learn more](https://trust.composio.dev).

### What if the API changes?

Composio maintains and updates all toolkit integrations automatically, so your agents always work with the latest API versions.

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)