Context7
Up-to-date docs for AI agents
作者提供的说明(英文原文)
Your prompt library in any MCP client: list, fetch, save and version prompt templates.
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://neadlab.com/api/mcp在终端中运行这条命令
claude mcp add --transport http prompt-maker-studio https://neadlab.com/api/mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"prompt-maker-studio": {
"url": "https://neadlab.com/api/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": {
"prompt-maker-studio": {
"type": "http",
"url": "https://neadlab.com/api/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://neadlab.com/api/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。
服务器要求先登录,才会列出它的工具。
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 chrysogonus 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
在 1316 毫秒内响应(HTTP 401)
声明支持 OAuth 登录,你的 AI 应用可以带你去登录
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 3 项适用的基础检查中通过了 3 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(0.17.0)于前天进入注册中心。
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。
A self-hosted workspace for prompts you want to use again. Keep them organised, refine the wording, and test how they perform before your next edit.
Get started · Connect ChatGPT or Claude · Contribute
Find prompts with search, folders and favourites. Write reusable sections with {{variables}}, fill them in, and copy the result into any chat app. Saved versions let you compare edits and restore an earlier approach.
Choose Add existing prompts in the library and then Make reusable with AI, or Paste a prompt in the editor. AI turns unstructured text into XML-style sections and identifies variables with their original values filled in. Review and edit the variables, keep an input fixed, and copy either the template or filled prompt. Apply to the draft with Undo; Save keeps it. Example inputs are separate from template content and require an explicit choice.
Answer clarifying questions, then review a proposed draft section by section. See the wording changes before applying them; undo or save when you're ready.
Give a saved prompt test inputs and choose automatic checks, AI review or your own rating. Inspect model outputs and feedback, then compare runs to understand the effect of an edit. Keep your test cases reusable with CSV import and export.
*Screenshots use synthetic demo data, including illustrative AI outputs and scores.*
Every deployment also serves public pages for visitors who are not signed in: free tools to fill in templates, check a prompt, compare two versions and estimate tokens and cost (plus an optional free refiner on the server's AI connection), a gallery of ready-to-use prompt templates, practical guides, and an About page. They are server-rendered with structured data, a sitemap and /llms.txt, so search engines and AI assistants can find them.
Prompt management works without an AI connection. Prompt conversion, refinement, Try once and evaluation use your configured provider: OpenAI, Anthropic, Gemini, Ollama, vLLM or another OpenAI-compatible endpoint. Hosted calls may incur provider charges; operators can set monthly spending limits.
You'll need Git, Docker with Compose, Make and OpenSSL.
git clone https://github.com/chrysogonus/prompt-maker-studio.git
cd prompt-maker-studio make setup make up
Open [localhost:3000](http://localhost:3000) and create your account. Registration is open by default; set REGISTRATION_MODE=closed to admit only the first account. For AI features, connect a provider under Settings → AI connection, or use the operator's optional server default when configured.
make setup creates local configuration with a generated signing key. Browser API calls stay on the same origin through the frontend proxy. Run make down to stop the app. See the Docker guide for configuration and local email testing.
flowchart LR
Browser[Browser] --> Edge["Caddy · HTTPS"] MCP["ChatGPT / Claude / MCP client"] --> Edge Edge -->|Web app| UI["Next.js · React"] Edge -->|REST / MCP / OAuth| API[FastAPI] API --> DB[(SQLite)] API -.->|Import · refine · evaluate| AI["Configured AI provider"]
Caddy handles production HTTPS and routing. Locally, Next.js proxies /api to FastAPI. SQLite stores accounts, prompts, versions and evaluation history; REST and MCP share the same prompt services. AI calls are optional.
The stack: Python 3.12 with FastAPI and SQLAlchemy 2.1 on SQLite; Next.js 16, React 18 and TypeScript; Docker Compose with Caddy, plus Prometheus and Grafana for monitoring.
Early-stage, 0.x. APIs and database schemas may change between releases. Back up before upgrading; see the changelog. The 0.17.0 release record records publication, immutable image digests and verification for the latest release: LLM_WORKSPACE_ID sets the Anthropic workspace for the server default, and the backend and backup images move to a base with the fix for CVE-2026-109518, with no migrations. Each release record lists its own migrations and upgrade notes; follow them for every release you skip. Upgrades from before 0.5.0 must also follow the 0.5.0 upgrade checks, including rehearsing migrations on an isolated production-backup copy.
Apache 2.0. See NOTICE and third-party notices for attribution.