MCP Server Builder
anthropics/skills
Guides the design and implementation of Model Context Protocol servers in TypeScript or Python, from tool naming and error messages to evaluation.
AI Engineering from Scratch 中 Model Context Protocol (MCP) 路线的专注交互 tutor。
Install Learn MCP
$ npx skills add fancyboi999/ai-engineering-from-scratch-zh --skill learn-mcp -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install fancyboi999/ai-engineering-from-scratch-zh learn-mcp --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/fancyboi999/ai-engineering-from-scratch-zh.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/learn-mcp .claude/skills/learn-mcp && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "learn-mcp" agent skill from https://github.com/fancyboi999/ai-engineering-from-scratch-zh/tree/main/skills/learn-mcp into .claude/skills/learn-mcp/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "learn-mcp", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/fancyboi999/ai-engineering-from-scratch-zh/tree/main/skills/learn-mcpType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add fancyboi999/ai-engineering-from-scratch-zh --skill learn-mcp -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install fancyboi999/ai-engineering-from-scratch-zh learn-mcp --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/fancyboi999/ai-engineering-from-scratch-zh.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/learn-mcp .agents/skills/learn-mcp && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "learn-mcp" agent skill from https://github.com/fancyboi999/ai-engineering-from-scratch-zh/tree/main/skills/learn-mcp into .agents/skills/learn-mcp/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "learn-mcp", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add fancyboi999/ai-engineering-from-scratch-zh --skill learn-mcp -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install fancyboi999/ai-engineering-from-scratch-zh learn-mcp --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/fancyboi999/ai-engineering-from-scratch-zh.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/learn-mcp .cursor/skills/learn-mcp && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "learn-mcp" agent skill from https://github.com/fancyboi999/ai-engineering-from-scratch-zh/tree/main/skills/learn-mcp into .cursor/skills/learn-mcp/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "learn-mcp", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/fancyboi999/ai-engineering-from-scratch-zh.git --path skills/learn-mcp--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add fancyboi999/ai-engineering-from-scratch-zh --skill learn-mcp -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install fancyboi999/ai-engineering-from-scratch-zh learn-mcp --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/fancyboi999/ai-engineering-from-scratch-zh.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/learn-mcp .gemini/skills/learn-mcp && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "learn-mcp" agent skill from https://github.com/fancyboi999/ai-engineering-from-scratch-zh/tree/main/skills/learn-mcp into .gemini/skills/learn-mcp/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "learn-mcp", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install fancyboi999/ai-engineering-from-scratch-zh learn-mcpInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add fancyboi999/ai-engineering-from-scratch-zh --skill learn-mcp -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/fancyboi999/ai-engineering-from-scratch-zh.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/learn-mcp .github/skills/learn-mcp && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "learn-mcp" agent skill from https://github.com/fancyboi999/ai-engineering-from-scratch-zh/tree/main/skills/learn-mcp into .github/skills/learn-mcp/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "learn-mcp", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add fancyboi999/ai-engineering-from-scratch-zh --skill learn-mcp -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install fancyboi999/ai-engineering-from-scratch-zh learn-mcp --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/fancyboi999/ai-engineering-from-scratch-zh.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/learn-mcp .opencode/skills/learn-mcp && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "learn-mcp" agent skill from https://github.com/fancyboi999/ai-engineering-from-scratch-zh/tree/main/skills/learn-mcp into .opencode/skills/learn-mcp/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "learn-mcp", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
learn-mcp- GitHub stars
- 1.2k
- Token cost
- ~1.5k tokens
- SKILL.md length
- 365 words
- Files
- 1
- Skills in repo
- 14
- Repo updated
- First seen
- Licence
- MIT
At a glance
AI Engineering from Scratch 中 Model Context Protocol (MCP) 路线的专注交互 tutor。
- Works in 4 steps: 课程文件是否在本地可用。 → python3 --version 是否成功。 → 学习者能否在当前工作目录写入 MCP-LEARNING.md。 → …
- Tasks that involve MCP servers
- SKILL.md covers 使用宿主的调用语法, 选择课程前读取路线, 确立证据模式 and 查找或创建进度, plus 4 more sections
- Calls python3
What it does
Learn MCP is an agent skill from fancyboi999/ai-engineering-from-scratch-zh. AI Engineering from Scratch 中 Model Context Protocol (MCP) 路线的专注交互 tutor。 学习者想构建、保护、调试、验证或运行 MCP clients、servers、transports、gateways、 registries 或 conformance gates 时，开始或续学此路线。每次调用教学一课，并将 wire evidence 记录到 MCP-LEARNING.md。Start or resume this route when a learner wants to build, secure, debug, verify, or operate MCP clients, servers, transports, gateways, registries, or conformance gates.
Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Agent Workflows, covering MCP servers. It works with Model Context Protocol and Python. The repository describes itself as: Agent工程师最全学习路径 · 从零精通 AI 工程 · 20 阶段 503 课 · 中文全量翻译 + 配套站点 + 动画讲解视频 · 如何成为 AI Agent 工程师的修成指南. The licence is MIT.
When your agent uses it
- Tasks that involve MCP servers
Example prompts
- “/learn-mcp”
Requirements
- Python 3
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- 课程文件是否在本地可用。
- python3 --version 是否成功。
- 学习者能否在当前工作目录写入 MCP-LEARNING.md。
- 学习者选择第 07 课的可选第二实现时，是否有 TypeScript runner。
What it can do on your machine
Read from SKILL.md and the folder at commit 94b9888. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
python3
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Learn MCP loads about 1.5k tokens when it runs. Until then it costs about 100 tokens; SKILL.md has 365 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from fancyboi999/ai-engineering-from-scratch-zh at commit 94b9888, republished under its MIT licence (© fancyboi999). 365 words, ~1,542 tokens.
Download SKILL.mdSave it as
.claude/skills/learn-mcp/SKILL.md (or your agent's skills folder).- name
- learn-mcp
- description
- AI Engineering from Scratch 中 Model Context Protocol (MCP) 路线的专注交互 tutor。 学习者想构建、保护、调试、验证或运行 MCP clients、servers、transports、gateways、 registries 或 conformance gates 时，开始或续学此路线。每次调用教学一课，并将 wire evidence 记录到 MCP-LEARNING.md。Start or resume this route when a learner wants to build, secure, debug, verify, or operate MCP clients, servers, transports, gateways, registries, or conformance gates.
学习 Model Context Protocol (MCP)
教授专注的 Model Context Protocol (MCP) 路线。一次调用覆盖一节课。学习者应检查请求与响应、预测边界结果、运行或手工跟踪 lab，并在推进前记录课程 checkpoint。
使用宿主的调用语法
可移植 skill 名称是 learn-mcp。不要将某个宿主的语法说成协议规则。
| 宿主 | 开始或继续 |
|---|---|
| Codex | learn-mcp，或从 /skills 选择它 |
| Claude Code | /learn-mcp |
| 其他兼容宿主 | Use learn-mcp to start or resume the Model Context Protocol (MCP) path. |
选择课程前读取路线
唯一事实来源是 learning-paths/model-context-protocol.json。仓库可用时优先本地文件；否则从以下地址获取所需文件：
https://raw.githubusercontent.com/fancyboi999/ai-engineering-from-scratch-zh/main/<path>按 manifest 的 lessons 数组及其 order 进行。必修顺序为 06、07、08、09、10、11、12、13、14、15、16、18、17、28、29、30、31。第 16 课后，数字上的下一课不再是此路线的下一课。
对选中课程，完整读取 docs/zh.md 和 quiz.json。只在当前教学步骤需要时读取或运行 code/ 与 outputs/。采用课程声明的 protocol era。绝不把 legacy handshake 规则混进现代无状态 trace。
第 23 课是唯一可选 capstone。只能在所有必修行完成且 manifest prerequisitePaths 中第 19、20 课均完成后提供。绝不悄悄向此路径添加其他课程。
确立证据模式
第一次可执行 checkpoint 前，确定：
- 课程文件是否在本地可用。
python3 --version是否成功。- 学习者能否在当前工作目录写入
MCP-LEARNING.md。 - 学习者选择第 07 课的可选第二实现时，是否有 TypeScript runner。
本地文件和 Python 3 都可用时，采用 executable mode。记录绝对工作目录、精确命令、exit code、request id 与 method、选择的 protocol era，以及观察到的结果或错误。隐去 tokens、secrets、cookies、authorization headers 和敏感参数值。
仓库或 runtime 不可用时，采用 conceptual mode。阅读课程，手工跟踪一个小型 request 与 response，并将证据标为 Conceptual。将 runtime、transport、authorization 和 deployment 检查保留为 Pending。绝不把手工跟踪说成已执行通过。
可执行文件需要但缺失时，提供将仓库克隆到学习者选择目录的选项。克隆前等待确认。没有克隆时概念课仍必须可用。
查找或创建进度
在当前工作目录使用 MCP-LEARNING.md。不要将此路线写入 LEARNING.md，也不要修改 Agent Skills 进度。
决定不存在状态前，安全处理旧文件名：
- 若存在
MCP-LEARNING.md，使用它。若也有MCP-ENGINEERING-LEARNING.md，两个文件都不要覆盖；报告冲突并询问下一次更新由哪个文件拥有。 - 若
MCP-LEARNING.md不存在而MCP-ENGINEERING-LEARNING.md存在，在教学前将 legacy 文件在同目录改名为MCP-LEARNING.md（rename the legacy file toMCP-LEARNING.md）。字节级保留所有学习者笔记和证据行（Preserve every learner note and evidence row byte for byte）。不能原子 rename 时，先复制，验证新文件匹配，再删除 legacy 文件。 - 只有两个文件名均不存在时才创建新状态文件。绝不以空白模板替换 legacy 进度。
文件存在时保留所有学习者笔记和证据。从第一个标为 In progress 或 Next 的行继续。所有必修行都 Done 时，检查可选 capstone 前置条件，并报告确切缺失路径，不能重启路线。
文件不存在时，不经定位测验直接创建：
# My Model Context Protocol (MCP) Path
<!-- Managed by the learn-mcp tutor.
Source: learning-paths/model-context-protocol.json -->
## Route
- Started: <YYYY-MM-DD>
- Required time: about 23 hours 15 minutes
- Current: 1 of 17
- Evidence mode: Executable or Conceptual
## Environment
- Repository files: Available or Pending
- Python 3: Confirmed or Pending
- TypeScript runner for Lesson 07: Optional, Confirmed, or Pending
- Working directory: <absolute path>
## Public deployment gate
- Lesson 15 executable checkpoint: Pending
- Threat model reviewed: Pending
- External target and authority confirmed: Pending
## Progress
| Order | Lesson | Status | Evidence | Completed |
|---:|---|---|---|---|
| 1 | 13/06 MCP fundamentals | Next | | |
| 2 | 13/07 MCP server | Locked | | |
| 3 | 13/08 MCP client | Locked | | |
| 4 | 13/09 MCP transports | Locked | | |
| 5 | 13/10 Resources and prompts | Locked | | |
| 6 | 13/11 Model input and MRTR | Locked | | |
| 7 | 13/12 Explicit scope and elicitation | Locked | | |
| 8 | 13/13 Durable tasks | Locked | | |
| 9 | 13/14 MCP Apps | Locked | | |
| 10 | 13/15 MCP security | Locked | | |
| 11 | 13/16 MCP authorization | Locked | | |
| 12 | 13/18 Production auth | Locked | | |
| 13 | 13/17 Gateways and registries | Locked | | |
| 14 | 13/28 Tool contracts and content | Locked | | |
| 15 | 13/29 Reliability and flow control | Locked | | |
| 16 | 13/30 Registry supply chain | Locked | | |
| 17 | 13/31 Conformance engineering | Locked | | |
## Wire evidence
| Date | Lesson | Mode | Request or scenario | Observed result | Command, cwd, exit |
|---|---|---|---|---|---|
## Notes检查能够本地观察的事实。只询问无法安全推断的选择或授权。
在十分钟内开始第 06 课
首次调用时立即开始课程。从仓库根目录运行：
python3 phases/13-tools-and-protocols/06-mcp-fundamentals/code/main.py要求学习者识别重复的 protocol version 和 client capabilities、完整的 server/discover result、错误 -32022，以及没有 protocol-session creation 或 teardown。在拓展第 06 课其余内容前记录这些观察。
命令不能运行时，从课程展示一个现代 request 和 response，要求学习者标出每个 envelope field，并把结果记录为 conceptual evidence。命令 checkpoint 保持 pending。
Show full SKILL.md (156 more words)Show less
强制执行公开部署闸门
任何 non-loopback bind、共享 ingress、hosted endpoint、registry publication 或其他公开部署前，从 manifest 读取 publicDeploymentGate。要求第 15 课 executable checkpoint，审阅目标与请求的 authority，并在外部行动前获得学习者明确确认。
任何必需证据缺失时，教授或重跑第 15 课，并将部署行动保持 pending。skill 调用不授予 network、credential、publishing 或 deployment authority。
教一节课
- 将选中行标为
In progress。说明其 manifest path、duration、group、protocol era 与 evidence mode。 - 描述本课可预防的一种生产失败。请学习者先预测 status、JSON-RPC result 或 state transition，再解释。
- 绘制一个 request boundary：producer、transport、consumer 以及各方验证的精确 fields。保持 protocol state、durable application state、transport state、authorization state 和 UI state 相互区分。
- 将 Build It 和 Use It 分成小节推进。对于代码，解释一个 invariant，要求预测，然后运行或跟踪能证伪它的最小 case。
- 演练一个成功案例和至少一个相关失败案例。优先记录精确 wire evidence：request id、method、protocol era、适用时 headers、body、status 或 error code、result type 和 terminal state。隐去 secret 值。
- 要求课程 manifest
checkpointEvidence的每一项。runtime evidence 必须来自观察输出；conceptual evidence 必须点明未执行的命令及剩余不确定性。 - 逐题提问所有
postquiz 项；quiz 无 staged 项时提问所有项。学习者回答前不揭示correct、答案索引或解释。回复提示绝不放入真实答案字母或答案分布；使用Reply with one letter: <A|B|C|D>. - 仅在课程 checkpoint 与 quiz 都完成后标为
Done。追加一条简洁的 Wire evidence，向 Notes 添加得分，将下一行设为Next，并更新Current。
通过 unit tests 不能替代指定 protocol evidence。不要从 in-process function 推断 HTTP behavior、从 authentication 推断 authorization、从 timeout 推断 cancellation，或从一个 SDK 推断 conformance。
收尾
结束时给出 quiz 得分、已记录的精确 checkpoint evidence、任何 pending 的 runtime 或 security evidence 及下一节 manifest 课程。除非学习者要求离开，否则保持在此路线。
© fancyboi999, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skills/learn-mcp of fancyboi999/ai-engineering-from-scratch-zh.
Open the folder on GitHubat commit 94b9888
Compare with similar skills
Learn MCP next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Learn MCP this skillfancyboi999/ai-engineering-from-scratch-zh | 1.2k | — | ~1.5k | Automated safety check: Pass | MIT | |
| MCP Server Builderanthropics/skills | 180k | 63 repos | ~2.3k | Automated safety check: Pass | Apache-2.0 | |
| MCP Server BuildershareAI-lab/learn-claude-code | 78k | 5 repos | ~1.2k | Automated safety check: Pass | MIT | |
| MemPalace Setup and OperationMemPalace/mempalace | 59k | — | ~2.2k | Automated safety check: Pass | MIT | |
| FastmcpTommy-yw/RunbookHermes | 546 | 3 repos | ~2.1k | Automated safety check: Pass | MIT | |
| Fastmcp Client CLIPrefectHQ/fastmcp | 28k | — | ~823 | Automated safety check: Pass | Apache-2.0 |
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Course Guide
fancyboi999/ai-engineering-from-scratch-zh
AI Engineering from Scratch 课程的主题路由器。给它一个主题、问题或正在处理的 bug， 它会指出精确教授它的课程，以及下一条正确命令。触发短语： “在哪里学习”、“哪节课涵盖”、“课程导航”、“我卡在”、“接下来该做什么”、 “教我 MCP”、“教我 Agent Skills”、“在哪里准备 Claude certification”，或 "where do I…
Learn
fancyboi999/ai-engineering-from-scratch-zh
AI Engineering from Scratch 课程的交互式课程 tutor。读取 LEARNING.md，获取下一课， 在终端按章节教学，结尾测验并记录进度。可在克隆仓库中或完全通过 raw.githubusercontent.com 工作—— 无需设置。触发短语：“下一课”、“教我”、“继续课程”、“我们来学习”、“继续学习”，或 "next lesson", "teach…
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Questions about Learn MCP
What does Learn MCP do?
AI Engineering from Scratch 中 Model Context Protocol (MCP) 路线的专注交互 tutor。. Learn MCP is an agent skill from fancyboi999/ai-engineering-from-scratch-zh.md。Start or resume this route when a learner wants to build, secure, debug, verify, or operate MCP clients, servers, transports, gateways, registries, or conformance gates.
When should I use Learn MCP?
Learn MCP fits situations like: tasks that involve MCP servers.
How do I install Learn MCP in Claude Code?
Run `npx skills add fancyboi999/ai-engineering-from-scratch-zh --skill learn-mcp -a claude-code`. Or copy the skill folder (skills/learn-mcp in fancyboi999/ai-engineering-from-scratch-zh) into .claude/skills/learn-mcp in your project. Claude Code loads it when a task matches its description.
How do I install Learn MCP in Codex?
Run `npx skills add fancyboi999/ai-engineering-from-scratch-zh --skill learn-mcp -a codex`. Or copy the skill folder (skills/learn-mcp in fancyboi999/ai-engineering-from-scratch-zh) into .agents/skills/learn-mcp in your project. Codex loads it when a task matches its description.
Can I use Learn MCP in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add fancyboi999/ai-engineering-from-scratch-zh --skill learn-mcp -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/learn-mcp, .gemini/skills/learn-mcp, .github/skills/learn-mcp and .opencode/skills/learn-mcp in your project.
What does Learn MCP need to run?
Going by SKILL.md and its folder, Learn MCP needs the command-line tools its instructions call (python3). Our summary lists: Python 3.
Does Learn MCP access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Learn MCP safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Learn MCP use?
Learn MCP is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Learn MCP use?
About 1.5k tokens (SKILL.md is roughly 6.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Learn MCP?
Skills that share tags, products or a category with Learn MCP: MCP Server Builder (anthropics/skills, 180k stars), MCP Server Builder (shareAI-lab/learn-claude-code, 78k stars), MemPalace Setup and Operation (MemPalace/mempalace, 59k stars) and Fastmcp (Tommy-yw/RunbookHermes, 546 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Learn MCP?
fancyboi999 (a GitHub user) maintains it in fancyboi999/ai-engineering-from-scratch-zh, which has 1,195 GitHub stars. The repository holds 14 skills in this directory. The repository was last updated on October 9, 2026.
Source: fancyboi999/ai-engineering-from-scratch-zh on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.