原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

Tiger Skills

作者:timescale版本 0.1.4i★ –i在你的电脑上运行
注册名称io.github.timescale/tiger-skills

安装

概览

作者提供的说明(英文原文)

Provider agnostic skills implementation, with skills sourced from local paths or GitHub repositories

PopNx MCP 的三大支柱

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。

它能帮你做什么

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。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 开发者工具
  • 你需要填写:GITHUB_TOKEN

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 需要你自己填写: GITHUB_TOKEN, SKILLS_FILE

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

  • npm已安装 Node.js(用于 npx 命令)

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": {
    "tiger-skills": {
      "command": "npx",
      "args": [
        "-y",
        "@tigerdata/tiger-skills-mcp-server"
      ],
      "env": {
        "GITHUB_TOKEN": "your-value",
        "SKILLS_FILE": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add tiger-skills --env GITHUB_TOKEN=your-value --env SKILLS_FILE=your-value -- npx -y @tigerdata/tiger-skills-mcp-server

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "tiger-skills": {
      "command": "npx",
      "args": [
        "-y",
        "@tigerdata/tiger-skills-mcp-server"
      ],
      "env": {
        "GITHUB_TOKEN": "your-value",
        "SKILLS_FILE": "your-value"
      }
    }
  }
}

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。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "tiger-skills": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@tigerdata/tiger-skills-mcp-server"
      ],
      "env": {
        "GITHUB_TOKEN": "your-value",
        "SKILLS_FILE": "your-value"
      }
    }
  }
}

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。

需要你填写的值

  • GITHUB_TOKEN 机密 env
    Token to access (private) GitHub repos
  • SKILLS_FILE env
    Location of configuration file for skills

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。

它能做什么

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。

基础检查i

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

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 timescale 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    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“开发者工具”中的其他服务器比较i

  • 星标数多于此分类中其他 5547 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 5547 个服务器的 1% 更新
  • 基础检查结果等于或优于此分类中其他 5547 个服务器的 100%

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。

常见问题

Tiger Skills 安全吗?

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。

它需要哪些密钥或代码?

你需要填写:GITHUB_TOKEN

它在我的电脑上运行还是在云端?

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)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.1.4)于11个月前进入注册中心。

哪些应用可以使用它?

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, Docker。

有什么可以替代它?

同一分类中有:GitHub, Desktop Commander, Cloudflare MCP

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:↓ 每周下载量i★ 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

GitHub

Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.

作者:github广泛使用★ 3.4万5天前更新

电脑或云端

Desktop Commander

MCP server for terminal commands, file operations, and process management

作者:wonderwhy-er广泛使用↓ 71万/周★ 1万17天前更新

在你的电脑上运行

Cloudflare MCP

Cloudflare MCP servers

作者:cloudflare广泛使用★ 444614个月前更新

在云端运行✓ mcp.cloudflare.com

作者的 README

打开 README

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。

Tiger Skills MCP Server

Emulate Claude Skills with any LLM via a Model Context Protocol (MCP) server.

What are Skills?

Skills are modular components that enhance the capabilities of an MCP-compatible agent by providing specific functionalities, workflows, and domain expertise. They transform a general-purpose agent into a specialized agent equipped with procedural knowledge that no model can fully possess.

The goal is to be fully compatible with Anthropic's skill format. See their Agent Skills Spec and related documentation for more details.

An overview of the Skills spec

Skill Structure

Skills are modular, self-contained packages that extend agent capabilities by providing specialized knowledge, workflows, and tools. Think of them as "onboarding guides" for specific domains or tasks—they transform the agent from a general-purpose agent into a specialized agent equipped with procedural knowledge that no model can fully possess.

What Skills Provide
  1. Specialized workflows - Multi-step procedures for specific domains
  2. Tool integrations - Instructions for working with specific file formats or APIs
  3. Domain expertise - Company-specific knowledge, schemas, business logic
  4. Bundled resources - Scripts, references, and assets for complex and repetitive tasks
Anatomy of a Skill

Every skill consists of a required SKILL.md file and optional bundled resources:

skill-name/

├── SKILL.md (required) │ ├── YAML frontmatter metadata (required) │ │ ├── name: (required) │ │ └── description: (required) │ └── Markdown instructions (required) └── Bundled Resources (optional) ├── scripts/ - Executable code (Python/Bash/etc.) ├── references/ - Documentation intended to be loaded into context as needed └── assets/ - Files used in output (templates, icons, fonts, etc.)

SKILL.md (required)

Metadata Quality: The name and description in YAML frontmatter determine when the agent will use the skill. Be specific about what the skill does and when to use it. Use the third-person (e.g. "This skill should be used when..." instead of "Use this skill when...").

Bundled Resources (optional)
Scripts (scripts/)

Executable code (Python/Bash/etc.) for tasks that require deterministic reliability or are repeatedly rewritten.

  • When to include: When the same code is being rewritten repeatedly or deterministic reliability is needed
  • Example: scripts/rotate_pdf.py for PDF rotation tasks
  • Benefits: Token efficient, deterministic, may be executed without loading into context
  • Note: Scripts may still need to be read by the agent for patching or environment-specific adjustments
References (references/)

Documentation and reference material intended to be loaded as needed into context to inform the agent's process and thinking.

  • When to include: For documentation that the agent should reference while working
  • Examples: references/finance.md for financial schemas, references/mnda.md for company NDA template, references/policies.md for company policies, references/api_docs.md for API specifications
  • Use cases: Database schemas, API documentation, domain knowledge, company policies, detailed workflow guides
  • Benefits: Keeps SKILL.md lean, loaded only when the agent determines it's needed
  • Best practice: If files are large (>10k words), include grep search patterns in SKILL.md
  • Avoid duplication: Information should live in either SKILL.md or references files, not both. Prefer references files for detailed information unless it's truly core to the skill—this keeps SKILL.md lean while making information discoverable without hogging the context window. Keep only essential procedural instructions and workflow guidance in SKILL.md; move detailed reference material, schemas, and examples to references files.
Assets (assets/)

Files not intended to be loaded into context, but rather used within the output the agent produces.

  • When to include: When the skill needs files that will be used in the final output
  • Examples: assets/logo.png for brand assets, assets/slides.pptx for PowerPoint templates, assets/frontend-template/ for HTML/React boilerplate, assets/font.ttf for typography
  • Use cases: Templates, images, icons, boilerplate code, fonts, sample documents that get copied or modified
  • Benefits: Separates output resources from documentation, enables the agent to use files without loading them into context
Progressive Disclosure Design Principle

Skills use a three-level loading system to manage context efficiently:

  1. Metadata (name + description) - Always in context (~100 words)
  2. SKILL.md body - When skill triggers (<5k words)
  3. Bundled resources - As needed by the agent (Unlimited\*)

\*Unlimited because scripts can be executed without reading into context window.

Configuration

Environment Variables
  • SKILLS_FILE: Path to the YAML file configuring the set of skills. Default: ./skills.yaml
  • SKILLS_TTL: Time (in milliseconds) to cache loaded skills. Default: 5 minutes
Skills Configuration File

The set of skills is configured via a YAML file. Both local directories and GitHub repositories are supported. Config can point to individual skills or collections of skills.

local-directory-collection:

A collection of local skills stored in the ./skills directory.

Each skill should be in its own subdirectory with a SKILL.md file.

type: local_collection path: ./skills local-individual-skill:

An individual local skill stored in the ./skills/skill-name directory.

type: local path: ./path-to/individual/skill-name anthropic-github-collection:

A GitHub repo containing a collection of skills.

Each skill should be in its own subdirectory with a SKILL.md file.

type: github_collection repo: anthropics/skills

path: ./ # not needed for this example since skills are at the root of the repo

Optionally specify skills/paths to ignore in this collection

ignored_paths:

  • .claude-plugin
  • document-skills disabled_skills:
  • canvas-design

Setting enabled_skills will _only_ load the specified skills from the collection

enabled_skills:

- frontend-design

- webapp-testing

single-github-skill-example:

A GitHub repo containing an individual skill.

type: github repo: anthropics/claude-cookbooks path: ./skills/custom_skills/creating-financial-models

Skill names must be unique across all configured skills. Any duplicates will be ignored with a warning.

Connection string parameters

Individual clients can control the set of skills that are enabled, as well as the protocol(s) used, via parameters in the connection string.

  • enabled_skills: Comma-separated list of skill keys to enable. If not provided, all configured skills are enabled.
  • disabled_skills: Comma-separated list of skill keys to disable. If not provided, no skills are disabled.
  • tools=0: Disable all tools (for resource-only integration).
  • resources=0: Disable all resources (for tool-only integration).
Example
http://tiger-skills-mcp-server/mcp?disabled_skills=foo,bar&resources=0

Subagent Task Execution

This MCP server (optionally) provides a subagent tool that can be used to break up complex tasks into smaller subtasks, each handled by its own agent instance. This is useful for tasks that require multiple steps, especially when those steps may require consuming large amounts of data in LLM context.

The subagent will automatically have access to the same set of skills as configured for the view skill tool, as well as the ability to (recursively) invoke further subagents. In addition, a mcp.yaml configuration file can be provided to specify additional tooling to be made available to the subagent.

If you do not wish to use subagents, you can set SUBAGENT_DISABLED=true in the environment to disable the tool.

MCP Configuration for Subagents

Create a mcp.yaml file to specify additional tools for the subagent to have accessible. This file is read from the root directory by default, or you can specify a different path via the MCP_PATH environment variable.

Only the streamable HTTP transport is supported at this time.

pg_aiguide:

type: http url: https://mcp.tigerdata.com/docs

Development

Cloning and running the server locally.

git clone git@github.com:timescale/tiger-skills-mcp-server.git
Building

Run ./bun i to install dependencies and build the project. Use ./bun watch to rebuild on changes.

You will need a GitHub token with the correct scopes. Here is a direct link to create such a new token.

Create a .env file based on the .env.sample file.

cp .env.sample .env

Then update the GITHUB_TOKEN value in .env.

Testing

The MCP Inspector is a very handy to exercise the MCP server from a web-based UI.

./bun inspector
Test via HTTP
./bun watch http
FieldValue
Transport TypeStreamable HTTP
URLhttp://localhost:3001/mcp
Test via stdio
./bun watch stdio
FieldValue
Transport TypeSTDIO
Commandnode
Argumentsdist/index.js
Testing in Claude Desktop

Create/edit the file ~/Library/Application Support/Claude/claude_desktop_config.json to add an entry like the following, making sure to use the absolute path to your local tiger-skills-mcp-server project, and use a valid GitHub token.

{

"mcpServers": { "tiger-skills": { "command": "node", "args": [ "/absolute/path/to/tiger-skills-mcp-server/dist/index.js", "stdio" ], "env": { "GITHUB_TOKEN": "ghp_whatever" } } } }

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