Context7
Up-to-date docs for AI agents
作者提供的说明(英文原文)
Rent GPUs at live prices and serve any Hugging Face model, with spend caps for AI agents.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
Authorization标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
这个地址需要在请求的 header 中放入密钥,而添加连接器的菜单无法设置。请改用 Claude Code、Cursor 或 VS Code。
在终端中运行这条命令
claude mcp add --transport http arrakis https://arrakis.goodailabs.com/mcp --header 'Authorization: Bearer {token}'运行前请先填写空着的值。
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"arrakis": {
"url": "https://arrakis.goodailabs.com/mcp",
"headers": {
"Authorization": "Bearer {token}"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"arrakis": {
"type": "http",
"url": "https://arrakis.goodailabs.com/mcp",
"headers": {
"Authorization": "Bearer {token}"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个地址需要在请求的 header 中放入密钥,而添加连接器的菜单无法设置。请改用 Claude Code、Cursor 或 VS Code。
你的选择通过 Cookie 保存在这台设备上,无需账户。
Authorization 机密 HTTP header这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
工具名称和描述与服务器在 2026年11月6日 报告的完全一致。这些内容由作者撰写,不是我们写的;我们以纯文本形式显示。
search_gpusSearch GPU machines you can rent now at live prices: B300, B200, H200, RTX PRO 6000, RTX 5090, H100 and more. Free; changes nothing. Use it before rent_gpu and to answer what a GPU costs right now. Rows come best first: what the GPU can do (capability, H100 = 1.0), its price and
get_market_summaryLive market summary by GPU family: cheapest price per GPU-hour, GPUs available and machines. Free; needs no token; changes nothing.
get_partner_earningsFor partners (agents and people who bring customers to Arrakis): your partner codes with the link and a message to share, what each earns you (a share of what the customers you bring pay), the customers your codes brought (each with what they paid and earned you, and your link ta
join_partner_programJoin the Arrakis partner program and get your own partner code, link and a message to share. The account earns a share of what the customers it brings pay, as cash (paid through Stripe to the person or company you act for, once they set up payouts in the console) or Arrakis credi
get_balanceThe account balance (what it can pay now, what the running machines cost per hour, when the money runs out, whether rentals are paused and whether auto-recharge tops it up from a saved card) and this token's spend cap: the limit, what is committed, what is left, the longest renta
rent_gpuRent one machine found by search_gpus, for work you run yourself over SSH (training, fine-tuning, batch jobs). To serve a model, use plan_deploy then deploy_model instead: one call sets up the machine, the engine and an OpenAI-compatible endpoint. COSTS MONEY: price per GPU-hour
plan_deployWhat serving a Hugging Face model takes, before anything is rented: the GPU memory it needs and the machines it fits on right now, best value first, each with its hourly price and a rough speed. Free; rents and changes nothing. Call it first whenever the person wants a model runn
deploy_modelServe any model from Hugging Face on a machine of the person's, like a hosted inference API but on their own GPU: vLLM or SGLang for text models, vLLM-Omni or SGLang for image and video models (FLUX, Qwen-Image, Wan), vLLM-Omni for speech and music, llama.cpp for a GGUF file (own
list_imagesImages a machine can boot, for rent_gpu's template_id: the Arrakis images (PyTorch, CUDA toolkit, Ubuntu; SSH, login banner and tools built in) and the account's saved ones, with download size. Any other public image works through rent_gpu's image. Free; changes nothing.
list_instancesEvery machine on the account with its state, price per hour, SSH command, removal time and any notice from its host. Check it at the start of a session: a machine left running keeps billing until its removal time. Free; changes nothing.
get_instanceOne machine now: state (PENDING or PROVISIONING while it boots, which is free; RUNNING when ssh_command works; then TERMINATED or FAILED), price per hour, ssh_command, removed_by, any notice from its host (host_notice and host_notice_at, host_down_since) and, once it ended, ended
get_eventsEvents on your machines, newest first: machine.ready (with its SSH command), machine.ended (reason says why: evicted when its host took it back or stopped working, otherwise stopped, removal_time, out_of_funds, paused or failed) and machine.notice (its host will take it back or r
terminate_instanceStop a machine now and delete it with everything on its disk; billing stops (the hour already started is paid). Copy results off first, for example with scp or rsync over its ssh_command. Cannot be undone; terminating a machine that already ended changes nothing.
instance_ssh_keysList, add or take off the SSH keys that can log in to a running machine. With only instance_id: the keys on it (fingerprint, comment, the saved key's name). add_ssh_key_ids / add_public_keys: more keys can log in (a teammate's, a new laptop's), at once. remove_fingerprints: those
schedule_removalChange when a machine is removed automatically (ISO 8601, UTC). It bills until then, and removal deletes the machine and its disk. Use it to end a rental early when the job will finish sooner, or, with a token that has no spend cap, to extend a long run. A token with a spend cap
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日
注册中心没有列出源代码仓库,因此无法将发布者(goodailabs.com)与代码对应起来
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
在 191 毫秒内响应(HTTP 200)
无需登录
已读取 15 个工具描述,未发现针对 AI 的隐藏指令
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 3 项适用的基础检查中通过了 2 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
你需要填写:Authorization
它在作者的云端运行。通过互联网连接,无需安装,但你发送的内容会经过作者的服务器。
GitHub 仓库最后更新于–,最新版本(0.1.0)于7天前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。
同一分类中有:Context7, Codebase Memory, Exa
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
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仓库中没有找到 README