Context7
Up-to-date docs for AI agents
作者提供的说明(英文原文)
Compare LLM API and cloud compute pricing, estimate workload costs, pick a model within budget.
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。
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 …”。
适用于网页版、桌面版和手机版 Claude:
https://optimtoken-mcp.optimnow.io/mcp在终端中运行这条命令
claude mcp add --transport http ai-pricing-hub https://optimtoken-mcp.optimnow.io/mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"ai-pricing-hub": {
"url": "https://optimtoken-mcp.optimnow.io/mcp"
}
}
}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": {
"ai-pricing-hub": {
"type": "http",
"url": "https://optimtoken-mcp.optimnow.io/mcp"
}
}
}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。
ChatGPT 只能连接互联网上的服务器:
https://optimtoken-mcp.optimnow.io/mcp菜单名称可能因套餐和版本不同而略有差异。
你的选择通过 Cookie 保存在这台设备上,无需账户。
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。
我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。
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
注册名称已通过 GitHub 账户 OptimNow 验证,该账户拥有此仓库
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
尚未检查;我们会轮流检查各个端点
尚未检查;我们会轮流检查各个端点
尚未检查;我们会在检查端点时读取工具列表
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 1 项适用的基础检查中通过了 1 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。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
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(0.4.2)于30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
Up-to-date docs for AI agents
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
Built by OptimNow. Ask an AI assistant what a model or an
instance actually costs, and get a dated, sourced figure instead of a number the
model remembers from its training data.
The server is hosted, so there is nothing to install.
https://optimtoken-mcp.optimnow.io/mcp
Paste it exactly as written, with /mcp and no trailing slash. The widgets render only for that form: the host checks a hash of the URL you entered.
| Client | How to add it |
|---|---|
claude mcp add --transport http optimtoken https://optimtoken-mcp.optimnow.io/mcp | |
| Settings → Connectors → Add custom connector, paste the URL above | |
| Settings → Connectors → Add, paste the URL. Comparisons render as interactive widgets | |
| Add an HTTP MCP server entry pointing at the URL |
Then just ask:
*"We send 200k support tickets a month at about 1,500 input tokens each. Which model gives me the best quality per euro, and what would it cost?"*
Model prices change weekly, and a language model's idea of them is frozen at its training cutoff. Ask one what Claude or GPT costs and you get a confident answer that was true some months ago, with no date attached and no way to tell. The same applies to cloud instance rates, which additionally vary by region in ways nobody memorises.
This server replaces recall with a lookup:
| Tool | What it answers |
|---|---|
| `compare-llm-models` | "What is out there?" Browse and filter the catalogue on price, quality (Chatbot Arena ELO), efficiency and capabilities, with a self-hostability read from the licence. |
| `recommend-llm-model` | "Just tell me which one." A ranked top 3 for one workload under your constraints (budget, minimum ELO, required capability, self-hostability), each with a per-constraint satisfied or violated breakdown as the evidence. Over-constrained queries return the nearest misses, labelled as such. |
| `compare-models-side-by-side` | "How do these specific ones compare?" 2 to 4 named models across all 8 use case profiles at a chosen monthly volume, list and optimized cost for each. |
| `estimate-llm-cost` | "What will this cost us per month?" Per-request and monthly cost for your own volume, token shape, cache hit rate and batch eligibility. |
| `compare-compute-pricing` | "What should we run it on?" Compute instance rates across AWS, Azure, GCP, OCI, OVH, DigitalOcean and Alibaba, by region and category. |
All five are read-only and take no credentials. Nothing you send is stored.
Use case profiles ship with realistic token shapes, so you do not have to invent them: Support Ticket, Knowledge Q&A, Meeting Summary, Marketing Content, Coding Task, Invoice Processing, Call Summary, Agent Workflow.
optimtoken.optimnow.io is the single source of truth. When it cannot be reached, the server degrades in tiers rather than failing, and says which tier it used.
| Tool | Tier 1 | Tier 2 | Tier 3 |
|---|---|---|---|
| LLM tools | GET /api/llm-models | OpenRouter direct | embedded snapshot |
| Compute tool | GET /api/pricing?region= | not available | embedded snapshot (137 rows) |
Tiers 2 and 3 serve uncorrected prices, and that matters more than it sounds. An upstream feed once published a frontier model at half its real list price, which halves every monthly figure derived from it. So every response carries a provenance object with pricesVerified, and the lower tiers put a notice at the top of the answer. A fallback should never quietly downgrade correctness.
Tier 1 is accepted only when the catalogue reports that it is itself serving fresh upstream data. If the site is on its own fallback, it carries no corrections, and this server treats it accordingly.
Requires Node.js 24+.
npm install
npm run dev # Skybridge dev server + MCP inspector at localhost:3000 npm test # schema conformance, serialisation precision, data sources npm run build # widgets + server
The static fallback catalogue is refreshed by hand, not on a schedule:
npm run refresh-fallback
Because it is manual, check its dataAsOf before trusting a tier-3 response. An unrefreshed fallback ages silently.
ai-pricing-hub-mcp/
├─ server/src/index.ts # tool + widget registrations ├─ server/src/lib/optimtoken-api.ts # the one base URL constant, fetch and timeout discipline ├─ server/src/lib/ # ranking, efficiency scoring, provenance, normalisation ├─ server/src/data/ # static fallback pricing + region maps └─ web/src/widgets/ # React widgets rendered in the client
Built with Skybridge, deployed on Fly.io.
| OptimToken | The web app. Same catalogue, full UI, an AI advisor and a public JSON API. |
| AI ROI Calculator | Does the AI business case pay for itself. Same prices, plus harness costs and value modelling. |
| cloud-finops-skills | FinOps knowledge for AI agents: AWS, Azure, GCP, AI inference, SaaS. |
| finops-mcp-resources | MCP servers, tutorials and client guides for cloud cost work. |
Released under the MIT License.
Prices served by this server come from third-party sources and are provided as is, without warranty. Verify against vendor pricing pages before committing spend.
Questions about your own AI or cloud bill? Talk to OptimNow.