Use Apify MCP from Claude Code
Bring Apify MCP context into engineering work while Type keeps app access attached to the teammate and workspace.
One governed connection your whole team and its AI agents can share, with approved actions and human review, so working in Apify MCP never means pasting credentials into a prompt.
Bring Apify MCP context into engineering work while Type keeps app access attached to the teammate and workspace.
Let coding agents ask for the right app action, preserve conversation context, and keep humans in the approval loop.
Use Type as the collaboration layer around OpenClaw and other LLM workflows that need app access.
AI-powered web scraping and automation platform. Run actors, scrape websites, and automate browser tasks via the official Apify MCP server.
Connect Apify MCP once, then decide which teammates can use it for threads, automations, skills, and coding work.
This tool calls the Actor "apify/rag-web-browser" and retrieves its output results. Use this tool instead of the "call-actor" if user requests this specific Actor. Actor description: Web browser for OpenAI Assistants, RAG pipelines, or AI agents, similar to a web browser in ChatGPT. It queries Google Search, scrapes the top N pages, and returns their content as Markdown for further processing by an LLM. It can also scrape individual URLs.Use this tool when user wants to GET or RETRIEVE actual data immediately (one-time data retrieval). This tool directly fetches and returns data - it does NOT just find tools. Examples of when to use: - User wants current/immediate data (e.g., "Get flight prices for tomorrow", "What's the weather today?") - User needs to fetch specific content now (e.g., "Fetch news articles from CNN", "Get product info from Amazon") - User has time indicators like "today", "current", "latest", "recent", "now" This is for general web scraping and immediate data needs. For repeated/scheduled scraping of specific platforms (e-commerce, social media), consider suggesting a specialized Actor from the Store for better performance and reliability.
Call any Actor from the Apify Store. WORKFLOW: 1. Use fetch-actor-details to get the Actor's input schema 2. Call this tool with the actor name and proper input based on the schema If the actor name is not in "username/name" format, use search-actors to resolve the correct Actor first. For MCP server Actors: - Use fetch-actor-details with output={ mcpTools: true } to list available tools - Call using format: "actorName:toolName" (e.g., "apify/actors-mcp-server:fetch-apify-docs") IMPORTANT: - Typically returns a datasetId and preview of output items - Use get-actor-output tool with the datasetId to fetch full results - Use dedicated Actor tools when available (e.g., apify-slash-rag-web-browser) for better experience There are two ways to run Actors: 1. Dedicated Actor tools (e.g., apify-slash-rag-web-browser): These are pre-configured tools, offering a simpler and more direct experience. 2. Generic call-actor tool (call-actor): Use this when a dedicated tool is not available or when you want to run any Actor dynamically. This tool is especially useful if you do not want to add specific tools or your client does not support dynamic tool registration. USAGE: - Always use dedicated tools when available (e.g., apify-slash-rag-web-browser) - Use the generic call-actor tool only if a dedicated tool does not exist for your Actor. - This tool supports async execution via the `async` parameter: - **When `async: false` or not provided** (default): Waits for completion and returns results immediately with dataset preview. Use this whenever the user asks for data or results. - **When `async: true`**: Starts the run and returns immediately with runId. Only use this when the user explicitly asks to run the Actor in the background or does not need immediate results. When UI mode is enabled, async is always enforced and the widget automatically tracks progress. EXAMPLES: - user_input: Get instagram posts using apify/instagram-scraper
Get detailed information about an Actor by its ID or full name (format: "username/name", e.g., "apify/rag-web-browser"). Use 'output' parameter with boolean flags to control returned information: - Default: All fields true except mcpTools - Selective: Set desired fields to true (e.g., output: { inputSchema: true }) - Common patterns: inputSchema only, description + readme, mcpTools for MCP Actors Use when querying Actor details, documentation, input requirements, or MCP tools. EXAMPLES: - What does apify/rag-web-browser do? - What is the input schema for apify/web-scraper? - What tools does apify/actors-mcp-server provide?
Fetch the full content of an Apify or Crawlee documentation page by its URL. Use this after finding a relevant page with the search-apify-docs tool. USAGE: - Use when you need the complete content of a specific docs page for detailed answers. USAGE EXAMPLES: - user_input: Fetch https://docs.apify.com/platform/actors/running#builds - user_input: Fetch https://docs.apify.com/academy - user_input: Fetch https://crawlee.dev/docs/guides/basic-concepts
Retrieve the output dataset items of a specific Actor run using its datasetId. You can select specific fields to return (supports dot notation like "crawl.statusCode") and paginate results with offset and limit. This tool is a simplified version of the get-dataset-items tool, focused on Actor run outputs. The results will include the dataset items from the specified dataset. If you provide fields, only those fields will be included (nested fields supported via dot notation). You can obtain the datasetId from an Actor run (e.g., after calling an Actor with the call-actor tool) or from the Apify Console (Runs → Run details → Dataset ID). USAGE: - Use when you need to read Actor output data (full items or selected fields), especially when preview does not include all fields. USAGE EXAMPLES: - user_input: Get data of my last Actor run - user_input: Get number_of_likes from my dataset - user_input: Return only crawl.statusCode and url from dataset aab123 Note: This tool is automatically included if the Apify MCP Server is configured with any Actor tools (e.g., "apify-slash-rag-web-browser") or tools that can interact with Actors (e.g., "call-actor", "add-actor").
Apify MCP exposes Apify Actors and platform resources through Model Context Protocol, enabling AI agents to discover and run Actors, access datasets and storage results, search Apify documentation, use hosted Streamable HTTP or local stdio transports, configure tools for MCP clients, authenticate with Apify API tokens or OAuth, and receive structured Actor output schemas.
Yes. Type lets an AI teammate use connected Apify MCP actions from a governed workspace context, so Claude Code work can reference the app without copying credentials into a local prompt.
Yes. Codex can collaborate through Type with app context, skills, and approved actions. The Apify MCP catalog entry includes public integration details and example capabilities where available.
Type exposes connected app capabilities to AI teammates and coding agents through Type's integration layer. Teams use it when they want shared app access, human review, and teammate-level permissions around agent work.
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