Context7
Up-to-date docs for AI agents
作者提供的说明(英文原文)
Modular MCP server for dynamic prompt generation and software development analysis tools
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 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"mercury-spec-ops": {
"command": "npx",
"args": [
"-y",
"@n0zer0d4y/mercury-spec-ops"
]
}
}
}在终端中运行这条命令
claude mcp add mercury-spec-ops -- npx -y @n0zer0d4y/mercury-spec-ops粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"mercury-spec-ops": {
"command": "npx",
"args": [
"-y",
"@n0zer0d4y/mercury-spec-ops"
]
}
}
}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": {
"mercury-spec-ops": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@n0zer0d4y/mercury-spec-ops"
]
}
}
}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。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
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。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
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8日
注册名称已通过 GitHub 账户 n0zer0d4y 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
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
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。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(0.1.2)于12个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。
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。
The first MCP server to expose dynamic, AI-invocable tools for prompt generation and template assembly.
Transform how AI assistants interact with specialized content. Instead of static prompts and resources, Mercury Spec Ops provides 6 programmable tools that enable AI to dynamically generate technology-specific prompts and comprehensive templates on-demand. Built on a sophisticated modular architecture with 31 technology stacks, 10 analysis dimensions, and 34 template sections—all accessible through simple tool calls.
This MCP server provides a modular, extensible architecture with:
git clone https://github.com/n0zer0d4y/mercury-spec-ops.git
cd mercury-spec-ops npm install npm run build
npm run mcp
npm install -g @n0zer0d4y/mercury-spec-ops
Or use directly with npx (no installation required):
npx @n0zer0d4y/mercury-spec-ops
Configure the server in your MCP client (Claude Desktop, Cursor, etc.):
For Claude Desktop (claude_desktop_config.json):
{
"mcpServers": { "mercury-spec-ops": { "command": "npx", "args": ["-y", "@n0zer0d4y/mercury-spec-ops"] } } }
For Cursor (~/.cursor/mcp.json):
{
"mcpServers": { "mercury-spec-ops": { "timeout": 60, "type": "stdio", "command": "npx", "args": ["-y", "@n0zer0d4y/mercury-spec-ops"] } } }
For Claude Desktop (claude_desktop_config.json):
{
"mcpServers": { "mercury-spec-ops": { "command": "node", "args": ["/path/to/mercury-spec-ops/dist/src/server.js"] } } }
For Cursor (~/.cursor/mcp.json):
{
"mcpServers": { "mercury-spec-ops": { "timeout": 60, "type": "stdio", "command": "node", "args": ["/path/to/mercury-spec-ops/dist/src/server.js"] } } }
Windows Local Path Example (Cursor):
{
"mcpServers": { "mercury-spec-ops": { "timeout": 60, "type": "stdio", "command": "node", "args": [ "C:\\Development\\Projects\\MCP-Servers\\mercury-spec-ops\\dist\\src\\server.js" ] } } }
Important Notes:
npm run build firstcodebase-analysis-prompt with technology_stack: "node.js,typescript" and analysis_focus: "security,performance"resource://codebase-analysis-templatebug-analysis-prompt with technology_stack: "react", severity_level: "critical", and bug_type: "security"prd-prompt with project details and technology_stack: "react"prd-promptproject_name (required): Name of the software projectproject_description (required): Brief description of the projecttarget_audience (optional): Target audience for the product (enum values)project_type (optional): Type of project (enum values)key_features (optional): Key features to include in the PRDtechnology_stack (optional): Technology stack to be used (enum values)custom_instructions (optional): Custom instructions for PRD generationcodebase-analysis-promptrepository_path (required): Path to the repository to analyzetechnology_stack (required): Technology stack used in the codebase (enum values)analysis_focus (optional): Focus areas for analysis (enum values)custom_instructions (optional): Custom instructions for codebase analysisbug-analysis-promptrepository_path (required): Path to the repository with bugs to analyzebug_description (required): Description of the bug or issue to analyzeaffected_components (optional): Components affected by the bugseverity_level (optional): Severity level of the bug (enum values)bug_type (optional): Type of bug (enum values)technology_stack (optional): Technology stack used in the affected components (enum values)custom_instructions (optional): Custom instructions for bug analysisresource://prd-templateresource://codebase-analysis-templateresource://bug-analysis-templatesrc/
├── server.ts # Main MCP server implementation ├── types/ │ ├── enums.ts # All enum definitions (31 tech + 10 focus) │ └── index.ts # Type definitions and exports ├── prompts/ │ ├── modules/ # 45 modular prompt components │ │ ├── technology/ # 31 technology-specific modules │ │ │ ├── languages/ # 11 language modules │ │ │ ├── runtimes/ # 1 runtime module │ │ │ ├── frameworks/ # 10 framework modules (3 frontend, 7 backend) │ │ │ ├── databases/ # 4 database modules │ │ │ ├── cloud/ # 3 cloud platform modules │ │ │ └── tools/ # 2 DevOps tool modules │ │ ├── analysis-focus/ # 10 focus-area modules │ │ └── bug-severity/ # 4 severity-specific modules │ ├── base-prompts/ # Base prompt templates │ └── prompt-builder.ts # Programmatic prompt assembly ├── resources/ │ ├── templates/ # Modular template components │ │ ├── prd/ # 10 PRD template modules │ │ ├── codebase-analysis/ # 8 codebase analysis modules │ │ └── bug-analysis/ # 4 bug analysis modules │ └── template-builder.ts # Programmatic template assembly └── tests/ # Comprehensive test suite (66 tests) ├── utils/ # Utility function tests (enum parser) ├── prompts/ # Prompt builder tests ├── resources/ # Template builder tests └── types/ # Enum and type tests
The project includes a comprehensive test suite with 88% coverage:
# Run all tests
npm test
npm run test:watch
npm run test:coverage
npm run test:ui
npm run t
只显示了开头部分;其余内容请在仓库中阅读