Apify MCP Server
com.apify由 apify.com 发布官方发布者v0.21.4更新于 Nov 7, 2026
Extract data from any website with thousands of scrapers, crawlers, and automations on Apify Store ⚡
概览
托管式 Apify MCP 服务器,让助手在 Apify Store 中查找、运行数千个抓取、爬虫与自动化 Actor,并读取结果。
- 可以做什么
- 搜索 Apify Store,并在运行前查看 Actor 的输入结构、README 与价格
- 运行 Actor、查看运行状态与日志、中止运行,并读取数据集条目或键值存储记录
- 搜索并获取 Apify 与 Crawlee 文档页面
- 通过内置 Actor 工具进行网页搜索,并把页面内容抓取为 Markdown、文本或 HTML
- 管理已保存的任务、计划、构建与版本,并向 Apify API 发送请求
- 把单个 Actor 或某个 Actor 自带的 MCP 工具作为工具提供给助手
- 适用场景
- 适合助手需要大规模实时网页数据的场景:抓取网站、搜索结果、社交媒体、地图或电商商品列表,或为 RAG 爬取页面,而无需为每个站点单独安装服务器。
- 运行要求
- 远程端点 mcp.apify.com,使用 OAuth 登录,或在 Authorization 请求头中以 Bearer 形式提供 Apify API 令牌。本地 stdio 版本通过 npx 运行,需要 Node.js 22 或更高版本以及 APIFY_TOKEN。多数工具需要 Apify 账户,少数只读工具无需账户。
安装
在 SourceWeft 中
- 打开 控制台中的 Apify MCP Server,将其添加到工作区。
- 连接 所需的 凭据。它们会被私密存储,绝不会在公开页面上展示。
- 为需要使用其工具的对话启用该服务。
Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。
交给智能体安装
把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。
阅读 https://sourceweft.com/mcp/com.apify%2Fapify-mcp-server/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。其他 MCP 客户端
把它添加到你客户端的 mcpServers 配置中。 客户端会在首次连接时完成 OAuth 登录。
{
"mcpServers": {
"apify": {
"type": "http",
"url": "https://mcp.apify.com/"
}
}
}README
[Get the config for any MCP client]
[npm version] [npm downloads] [CI status] [MIT license]
[GitHub stars] [Apify Discord]
Apify MCP server
Connect your agent to the largest marketplace of tools for AI.
The official Apify Model Context Protocol (MCP) server gives AI agents web scraping, data extraction, and browser automation through thousands of ready-made Actors from Apify Store, at https://mcp.apify.com.
Apify is the marketplace of ready-to-run tools for AI agents. One connection to the Apify MCP server gives your agent thousands of tools to choose from, for jobs like web fetch, SERP monitoring, lead generation and enrichment, and pulling data from e-commerce sites and social media. The server loads only what each task needs.
Your agent searches Apify Store, checks an Actor's input and pricing, runs it, and reads the structured results, so you don't install a separate MCP server for every site. Connect to the hosted server with OAuth, or run it locally over stdio with the @apify/actors-mcp-server npm package.
Contents
- Quickstart
- Set up your client
- Remote (hosted) or local MCP server
- How an agent uses Apify Actors
- Tools, resources, and prompts
- Choose which tools load
- UI mode configuration
- Example prompts
- Pricing and limits
- Telemetry
- Troubleshooting and limitations
- FAQ
- Development
- Contributing
- Privacy and license
- Learn more
🚀 Quickstart
- Open the MCP configurator, pick your client, and choose the tools you want.
- Copy the generated configuration, deeplink, or command into your client.
- Sign in to Apify in the browser window that opens. If you don't have an account, you can create a free one there.
The hosted endpoint is https://mcp.apify.com. If your client can't use OAuth, send your Apify API token in an Authorization: Bearer <APIFY_TOKEN> header instead. Treat the token like a password and keep it out of repositories.
Using a coding agent such as Claude Code, Codex, Cursor, or GitHub Copilot? An official Apify plugin installs this MCP server together with Apify agent skills in one step.
🤖 Set up your client
The configurator generates the exact setup for each supported client, including Claude Code, ChatGPT, Cursor, VS Code, GitHub Copilot CLI, Claude, Claude Desktop, Codex, OpenCode, Kiro, and more. The snippets below cover the most common cases.
Claude Code
Claude Code opens the Apify sign-in page the first time it uses the server. To install the Apify plugin with Apify agent skills instead, run /plugin marketplace add apify/apify-claude-code-plugin, then /plugin install apify@apify and /reload-plugins.
ChatGPT
- Open ChatGPT Plugins, select +, then Add custom MCP server.
- Name it
Apify, enterhttps://mcp.apify.comas the server URL, and choose OAuth authentication. - Review the risk warning, select I understand and want to continue, then Create as a plugin.
- Sign in with Apify, review the tools, and install the plugin. No API token is needed.
- Start a new conversation, type
@, and select Apify.
In Business, Enterprise, and Edu workspaces, an admin or owner may need to create or publish the plugin. If the option is missing, ask your workspace admin. When the server's tools change, open the plugin and select Refresh.
The ChatGPT desktop app uses local MCP configuration shared with Codex instead: go to Settings > MCP servers > Add server, choose Streamable HTTP, and enter https://mcp.apify.com. See OpenAI's custom MCP server guide.
Cursor
Use the one-click install link from the configurator, or let the Apify CLI write the configuration, including your API token:
The same command works for claude-code, vscode, codex, kiro, and antigravity.
VS Code and GitHub Copilot
Use the one-click install link from the configurator, run apify mcp install vscode, or add https://mcp.apify.com as an HTTP server in your MCP configuration:
Claude
Apify is available as a Claude connector. Open Settings > Connectors, find Apify in the connector directory, and connect it. You can also select Add custom connector, name it Apify, and enter https://mcp.apify.com as the remote MCP server URL. Sign in with Apify when prompted. The same connector works on Claude.ai and in Claude Desktop. See the Claude guide.
Any other MCP client (JSON config)
Most clients that support remote servers and OAuth accept a configuration like this:
Local stdio (npx)
Requires Node.js 22 or later.
If you've run apify login, the server can also read the token saved by the Apify CLI. Run npx @apify/actors-mcp-server --help for all options.
The server is also listed in the Docker MCP catalog, and each release ships an MCP bundle file (apify-mcp-server.mcpb) for one-click installation in clients that support it.
Remote (hosted) or local MCP server
The hosted remote MCP server with OAuth is the recommended option. Use the local server when you want to run the MCP process on your own machine; Actors still run and store their results on the Apify platform in both modes. If your client supports only stdio, you can also bridge it to the hosted server with mcp-remote: npx mcp-remote https://mcp.apify.com.
How an agent uses Apify Actors
Actors are serverless programs on the Apify platform. Each one does a specific job, like scraping Google Maps, crawling a website for RAG, or collecting social media posts. The MCP server turns Actors into tools an agent can find and call without you configuring each one in advance.
A typical task follows four steps:
search-actorsfinds candidate Actors in Apify Store for the task.fetch-actor-detailsreturns the Actor's input schema, README, and pricing, plus its output schema on request.call-actorstarts the run and waits for it to finish, 30 seconds by default and up to 45. It returns the run status and storage IDs; the scraped items stay in the run's dataset.get-dataset-itemsreads the results from the run's dataset, withlimitandoffsetfor pagination.
The server adds get-dataset-items, get-key-value-store-record, get-actor-run, and abort-actor-run whenever call-actor or an Actor tool is loaded, so the agent can always read results and check on long runs that outlast the wait.
You can also expose a specific Actor as its own tool, for example apify/instagram-scraper. The server builds the tool's parameters from the Actor's input schema, so the agent knows exactly what to pass. A Server Actor with an API schema, such as apify/web-fetch, apify/web-search, or apify/rag-web-browser, gets a tool that sends one HTTP request to its API instead.
Actors that run their own MCP server. Some Actors are MCP servers themselves. fetch-actor-mcp-tool-list lists their tools, and call-actor-mcp-tool calls one. When such an Actor is loaded as a tool source and has no API schema, its tools are exposed under names in the form username--actor-name--tool-name; an Actor with an API schema, such as apify/web-search, gets its server tool instead, and call-actor-mcp-tool reaches its MCP tools. Apify Store also lists MCP-related Actors from independent creators; those are separate products with their own READMEs and pricing.
🛠️ Tools, resources, and prompts
Any Actor can be a tool, and agents discover new ones as they work. By default, the server loads the actors and docs categories, two Actor tools (Web Search and Web Fetch), and report-problem. Everything else is opt-in by category or by tool name.
Helper tools
Besides Actor tools, the server provides helper tools for the Apify platform:
- Actors: search Apify Store, list the Actors in your account, view their details, call tools on Actors that run MCP servers, send requests to Server Actors, and delete your own Actors.
- Documentation: search the Apify and Crawlee docs and fetch pages as context.
- Runs and storage: list runs, inspect them, read their logs, and read datasets and key-value stores.
- Tasks and schedules: manage saved Actor tasks and their public landing pages, and schedules that run Actors and tasks automatically.
- Builds and versions: build Actors, read build logs, and create, read, change, copy, and delete versions from files.
- Apify API: search the API reference, inspect an operation, and send requests to read or change data.
Available tools
Legend for the Enabled by default column:
- ✅ In the default tool set.
- ⚡ Added automatically when
call-actor, an Actor tool, orget-actor-runis loaded, which is true in the default configuration. - ✅¹ Served by default only when telemetry is on and the client name doesn't contain
claude,anthropic, orlocal-agent-mode. Select it explicitly withtools=report-problemortools=devto serve it to any client; telemetry still has to be on.
The tasks category manages saved Actor tasks. It is unrelated to the MCP Tasks protocol. The tool reference has full descriptions of each tool.
Tool annotations
Every tool carries a title, a readOnlyHint, and an openWorldHint. readOnlyHint is true for tools that only read data. Actor tools get it only for Apify-maintained Actors with limited permissions and no inputs that accept secrets, writable storage, an MCP connector, or code; other Actor tools are marked destructive. openWorldHint is true for tools that reach outside the Apify platform, such as call-actor, and false for platform-only tools.
Prompts and resources
No prompts are registered yet, so prompts/list returns an empty list. resources/read accepts any Apify API GET URL (https://api.apify.com/v2/...) and returns the response body using the session's Apify token, inlined up to 256 KB. Your data isn't enumerated in resources/list; resources/templates/list lists the common shapes with their paging parameters.
Choose which tools load
The tools parameter takes categories, tool names, and Actor names, separated by commas. When you set it, the defaults are dropped and only what you list is loaded, plus the ⚡ run and storage tools whenever the list includes call-actor or an Actor. The easiest way to build a selection is the configurator.
Hosted server:
Local server:
To give an agent a single Actor, list only that Actor. The agent gets its tool plus the four ⚡ tools it needs to read the results:
Pin your tools in production. The default tool set can change between versions. Set
toolsexplicitly if you need a stable interface.
Backward compatibility with older configurations
apify/web-searchreplacedapify/rag-web-browserin the default tools. To keepapify--rag-web-browser, addapify/rag-web-browserto yourtoolslist, or settools=actors,docs,apify/rag-web-browser,apify/web-fetchfor the previous default categories and Actors.- The
actorsURL parameter and--actorsflag still work. They're merged intotools, so?actors=apify/web-fetchequals?tools=apify/web-fetch. enableAddingActors,enable-adding-actors, andenableActorAutoLoadingwere removed and are ignored. Dynamic Actor calls come fromcall-actor, which the defaultactorscategory includes.- The selectors
add-actor,experimental, andprevieware retired and load nothing. Usecall-actoror theactorscategory. get-actor-logwas renamed toget-actor-run-log, and thesourcecategory toversions. The old names load nothing.call-actorno longer calls tools on MCP server Actors: theactorName:toolNameform is rejected. Usecall-actor-mcp-toolwithactor,tool, andarguments.call-actorstill starts a run of an MCP server Actor that has an input schema; one without is refused. A selection that namescall-actoralone needscall-actor-mcp-tooladded.fetch-actor-detailsno longer lists an MCP server Actor's tools, andoutput.mcpToolsis ignored. Usefetch-actor-mcp-tool-list, which returns the definitions instructuredContent.tools. A selection that namesfetch-actor-detailsalone needsfetch-actor-mcp-tool-listadded.- A selected Actor with an API schema (a Server Actor) gets a tool that sends one HTTP request to its API, with
method,path, andqueryarguments, instead of a tool that starts a run. If the Actor is also an MCP server, the selection no longer loads its MCP tools: usecall-actor-mcp-tool.call-actorstill starts runs of the Actor when it has an input schema. A selectedapify/rag-web-browseris served this way too, withGET /search. apify--web-fetchsends one HTTP request to the Web Fetch Actor's API instead of starting a run, and returns the HTTP response. Its arguments aremethod,path,queryand, forPOST /,body, for example{"method": "GET", "path": "/", "query": {"url": "https://example.com", "formats": ["markdown", "links"]}}.apify--web-searchsends one HTTP request to the Web Search Actor's API instead of starting a run, and returns the HTTP response. Its arguments aremethod,path,queryand, forPOST /,body, for example{"method": "GET", "path": "/", "query": {"query": "AI agent payment protocols", "maxResults": 5}}.call-actorstill starts runs of the Actor, andcall-actor-mcp-toolcalls itssearchMCP tool.
UI mode configuration
The ui parameter controls MCP Apps widget tools. With UI mode on, the server adds search-actors-widget and fetch-actor-details-widget next to their base tools, which keep returning standard responses. By default (auto), UI mode turns on when the client supports MCP Apps.
Hosted server:
Local server, with a CLI flag or the UI_MODE environment variable:
💬 Example prompts
Ask in plain language. The agent finds a suitable Actor, checks its input and pricing, runs it, and reads the results. These prompts cover the most common jobs:
Follow-ups work too. "Show me the next 10 results from that run" makes the agent call get-dataset-items again with a higher offset. With the schedules category loaded, "Run that Google Maps search every Monday at 9 am" creates a schedule.
💰 Pricing and limits
- Connecting to the MCP server is free. Actor runs bill to your Apify account according to each Actor's pricing, which
fetch-actor-detailsshows before a run. The Apify free plan includes $5 of monthly platform usage. - To cap what a run can cost, pass
maxTotalChargeUsd(pay-per-event Actors) ormaxItems(pay-per-result Actors) in thecallOptionsofcall-actor.timeoutandmemorylimit the run's duration and memory, not its price. - The hosted server accepts up to 20 requests per second per account.
search-actorsreturns only free and pay-per-event Actors that pass the platform's agent-safety filters, so rental and pay-per-result Actors don't appear in search. Full-permission Actors need your one-time approval; until then,call-actorreturns an error with an approval link.- Some tools work without an Apify account:
search-actors,fetch-actor-details,search-apify-docs,fetch-apify-docs,apify-api-search, andapify-api-details. Select only those, for examplehttps://mcp.apify.com?tools=search-actors, and the hosted server accepts the connection without a token.
🪙 Agentic payments (experimental). Agents can pay for Actor runs without an Apify account. AGI sells a prepaid, spend-capped Apify API token for an x402, MPP, or Skyfire payment. The agent then uses it as a normal Bearer token against
mcp.apify.com, with any Actor. See the agentic payments documentation for supported methods and limits, and agi.apify.com/AGENTS.md for protocol details.
📡 Telemetry
The Apify MCP server collects telemetry about tool calls to help Apify understand usage patterns and improve the service. Telemetry is on by default. With telemetry on, Actor searches in Apify Store send the MCP session ID as _traceId, and tool-call events carry it as trace_id. search-actors also sends _useCase, a one-sentence reason for the search written by the model, which Apify uses to improve Store search results. The stdio transport also uses Sentry for error tracking, which helps the Apify team find and fix issues faster.
To opt out, including Sentry, set the telemetry-enabled URL parameter or the --telemetry-enabled CLI flag to false, or set TELEMETRY_ENABLED=false. CLI flags take precedence over environment variables.
🐛 Troubleshooting and limitations
- The local server won't start. Check your Node.js version: the package requires Node.js 22 or later.
- Authentication fails. Reconnect so the client repeats the OAuth flow, or switch to a Bearer token. For the local server, check that
APIFY_TOKENis set in the client's server configuration, not only in your shell. - Client features vary. Any MCP client can connect, but support for dynamic tool lists, OAuth, and MCP Apps differs between clients.
- Invalid Actor input. When
call-actorfails because of invalid input, the error includes the Actor's input schema so the agent can correct the input and retry.
How the server adapts Actor input schemas
The server adapts Actor input schemas so that more clients and models can use them:
- Descriptions longer than 500 characters are cut at the last complete sentence and marked
[Description truncated]. - Enums are kept in full up to 2,000 combined characters. Larger enums are replaced by a short note with example values.
- Required fields get a
REQUIREDprefix in their descriptions for frameworks that ignore the JSON Schemarequiredlist. - Nested properties are built for special inputs such as proxy configuration and request lists.
- Missing array item types are inferred from the item type, the prefill, the default value, or the editor type, in that order.
- Prefill and default values are copied into descriptions as examples, for clients that ignore JSON Schema
examples.
For more help, see the MCP documentation or open an issue.
❓ FAQ
What is an MCP server? An MCP server exposes tools and data to AI agents through the Model Context Protocol, an open standard supported by clients such as Claude, ChatGPT, and Cursor. The agent connects once and calls the server's tools when a task needs them. The Apify MCP server's tools are the Actors in Apify Store.
What is the Apify MCP server? It's the official Model Context Protocol server for Apify. It lets AI agents search Apify Store, run Actors for web scraping, data extraction, and browser automation, and read the structured results.
When is it a good MCP server for web scraping? When an agent needs data from many different sites. A typical case is Google Maps one day, Instagram or an online store the next. The agent picks a ready-made Actor for each site from Apify Store instead of you writing and maintaining a scraper. Each Actor works like a web scraping API for its site, and the Apify platform handles scaling, proxies, and storage of the results.
How does it compare to Playwright MCP? Playwright MCP drives a browser on your machine step by step, through clicks and page snapshots. The Apify MCP server runs Actors in the Apify cloud. Each Actor handles JavaScript rendering, proxies, and blocking for its site and returns structured results, so the agent asks for the data instead of operating a browser. Many agents use both.
Can ChatGPT or Claude scrape websites with it?
Yes. Connect ChatGPT, Claude, or Claude Code to https://mcp.apify.com, then ask in plain language. The model searches for a suitable Actor, runs it, and reads the results.
Is it free? Connecting is free, and some discovery tools work without an account. Actor runs bill to your Apify account at each Actor's price, and the free plan includes $5 of monthly platform usage.
Do I need an API token?
Not with the hosted server, because OAuth signs you in through the browser. The local server needs APIFY_TOKEN or an Apify CLI login.
Can I limit what the agent can do or spend?
Yes. Select tools with the tools parameter or expose a single Actor. To cap a run's cost, pass maxTotalChargeUsd for pay-per-event Actors or maxItems for pay-per-result Actors in call-actor options.
🔧 Development
This repository contains the open-source server package published to npm as @apify/actors-mcp-server. The hosted service at mcp.apify.com runs on this core logic from a separate private repository.
You need Node.js 22 or later and pnpm.
The development HTTP server doesn't read APIFY_TOKEN from the environment. Pass your token in an Authorization: Bearer header or a ?token= query parameter, for example from the MCP Inspector.
To publish a canary build of a pull request to pkg.pr.new, add the beta label to it.
DEVELOPMENT.md covers the project structure, tool loading phases, the Node.js version policy, and testing.
🤝 Contributing
Bug reports, feature requests, and documentation fixes are welcome. Open an issue with steps to reproduce a bug, or describe the problem a feature would solve and who runs into it. Send typos, broken links, and wrong commands straight to a pull request. For code, work only on an issue a maintainer has invited you to pick up; unsolicited pull requests are closed.
Read CONTRIBUTING.md before you start, including the rules for AI-assisted contributions.
🔒 Privacy and license
Requests and Actor inputs go to the Apify API to run the Actors you call. Apify doesn't share them with third parties beyond what running those Actors requires. See Apify legal documents for details on data collection and retention.
The project is licensed under the MIT license.
📚 Learn more
- MCP documentation: authentication, tool reference, and advanced configuration
- Apify for AI agents: choosing between MCP, plugins, agent skills, the CLI, and machine-readable docs
- Apify agent skills: guided multi-step workflows, installed with
npx skills add apify/agent-skills - Apify CLI: running and building Actors from a terminal
- Model Context Protocol
- MCP for beginners
- How to use MCP with Apify Actors
- Webinar: Building and monetizing MCP servers on Apify
来源:README.md,提交 8bde569
工具
0版本历史
19- v0.21.4最新Nov 7, 2026
- v0.21.3Nov 6, 2026
- v0.21.2Nov 5, 2026
- v0.20.2Nov 4, 2026
- v0.20.1Nov 3, 2026
- v0.20.0Oct 29, 2026
- v0.19.3Oct 21, 2026
- v0.19.1Oct 20, 2026
- v0.19.0Oct 19, 2026
- v0.18.4Oct 16, 2026
- v0.18.3Oct 15, 2026
- v0.18.2Oct 14, 2026
- v0.18.0Oct 13, 2026
- v0.17.4Oct 7, 2026
- v0.17.3Oct 6, 2026
- v0.17.2Oct 5, 2026
- v0.17.1Sep 30, 2026
- v0.16.0Sep 17, 2026
- v0.15.7Sep 16, 2026
评分
已满足适用检查项的 85%
该评分衡量此收录条目的完整程度,依据注册中心条目、端点与公开来源计算得出。它不是对服务器本身的评价,也不表示服务器安全或当前可用:可连通性是带日期的检查结果,评分也不包含安装量或用户评价。
- 近 30 天内可连通必需25 分
- 已声明认证方式必需10 分
- 已列出工具15 分
请让服务器在无凭据时响应 tools/list,或发布可在沙箱中无凭据启动的软件包。
- 描述必需15 分
- 图标10 分
- 文档15 分
- 许可证10 分
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