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learn-mcp 精选

Focused interactive tutor for the Model Context Protocol (MCP) path in AI Engineering from Scratch. 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. Teaches one lesson per invocation and records wire evidence in MCP-LEARNING.md.

在 GitHub 打开

安装方式

cp -r .claude/skills/learn-mcp ~/.claude/skills/learn-mcp

把该 skill 目录放进客户端 skills 目录。不同客户端的目录可能不同,Claude Code 默认是 ~/.claude/skills/

整仓一次性获取:git clone --depth 1 https://github.com/rohitg00/ai-engineering-from-scratch.git

依赖与权限

  • 无需 API Key
  • 需要联网访问外部服务
  • 依赖外部命令:python python3
  • 以上为按正文与 frontmatter 自动推断的信号,仅供参考;安装前建议先阅读原文。

SKILL.md 正文

来源 rohitg00/ai-engineering-from-scratch@56c886c · 许可 MIT · 内容未修改

Learn Model Context Protocol (MCP)

Teach the focused Model Context Protocol (MCP) route. One invocation covers one lesson.

The learner should inspect a request and response, predict a boundary result,

run or hand-trace the lab, and record the lesson checkpoint before advancing.

Use the invocation syntax of the host

The portable skill name is learn-mcp. Do not present one host's

syntax as a protocol rule.

HostStart or resume
Codexlearn-mcp, or choose it from /skills
Claude Code/learn-mcp
Other compatible hostsUse learn-mcp to start or resume the Model Context Protocol (MCP) path.

Read the route before selecting a lesson

The source of truth is learning-paths/model-context-protocol.json. Prefer local

files when this repository is available. Otherwise fetch a needed file from:

https://raw.githubusercontent.com/rohitg00/ai-engineering-from-scratch/main/<path>

Follow the manifest's lessons array by order. The required sequence is 06,

07, 08, 09, 10, 11, 12, 13, 14, 15, 16, 18, 17, 28, 29, 30, 31. Numeric next

navigation is not the route after Lesson 16.

For the selected lesson, read docs/en.md and quiz.json fully. Read or run

code/ and outputs/ only when the current teaching step needs them. Use the

lesson's stated protocol era. Never merge a legacy handshake rule into a

modern stateless trace.

Lesson 23 is the only optional capstone. Offer it only after all required rows

are complete and both manifest prerequisitePaths, Lessons 19 and 20, are

complete. Do not silently add another lesson to this path.

Establish the evidence mode

Before the first executable checkpoint, determine whether:

  1. The lesson files are available locally.
  2. python3 --version succeeds.
  3. The learner can write MCP-LEARNING.md in the current working

directory.

  1. A TypeScript runner is available if the learner chooses the optional second

implementation in Lesson 07.

When local files and Python 3 are available, use executable mode. Record the

absolute working directory, exact command, exit code, request id and method,

selected protocol era, and observed result or error. Redact tokens, secrets,

cookies, authorization headers, and sensitive parameter values.

When the repository or runtime is unavailable, continue in conceptual mode.

Read the lesson, hand-trace a small request and response, and label the evidence

Conceptual. Leave runtime, transport, authorization, and deployment checks

Pending. Do not describe a hand trace as an executed pass.

If executable files are needed but absent, offer to clone the repository into

a directory the learner chooses. Wait for confirmation before cloning. The

conceptual lesson must remain available without a clone.

Locate or create progress

Use MCP-LEARNING.md in the current working directory. Do not put

this route in LEARNING.md and do not modify Agent Skills progress.

Before deciding that no state exists, handle the former filename safely:

  1. If MCP-LEARNING.md exists, use it. If

MCP-ENGINEERING-LEARNING.md also exists, do not overwrite either file;

report the collision and ask which file should own the next update.

  1. If MCP-LEARNING.md is absent and MCP-ENGINEERING-LEARNING.md exists,

rename the legacy file to MCP-LEARNING.md in the same directory before

teaching. Preserve every learner note and evidence row byte for byte. If

an atomic rename is unavailable, copy the file, verify the new file

matches, and only then remove the legacy file.

  1. Create a new state file only when neither filename exists. Never replace

legacy progress with the blank template below.

If the file exists, preserve all learner notes and evidence. Resume the first

row marked In progress or Next. If all required rows are Done, check the

optional capstone prerequisites and report the exact missing path instead of

restarting the route.

If the file does not exist, create it without a placement quiz:

# 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

Check facts that can be observed locally. Ask only for choices or authority

that cannot be inferred safely.

Start Lesson 06 in ten minutes

On the first invocation, begin the lesson immediately. From the repository

root, run:

python3 phases/13-tools-and-protocols/06-mcp-fundamentals/code/main.py

Ask the learner to identify the repeated protocol version and client

capabilities, the complete server/discover result, error -32022, and the

absence of protocol-session creation or teardown. Record those observations

before expanding into the rest of Lesson 06.

If the command cannot run, show one modern request and response from the

lesson, ask the learner to label every envelope field, and record the result as

conceptual evidence. Keep the command checkpoint pending.

Enforce the public deployment gate

Before any non-loopback bind, shared ingress, hosted endpoint, registry

publication, or other public deployment, read publicDeploymentGate from the

manifest. Require the executable Lesson 15 checkpoint, review the target and

requested authority, and obtain the learner's explicit confirmation for the

external action.

If any required evidence is missing, teach or rerun Lesson 15 and keep the

deployment action pending. A skill invocation does not grant network,

credential, publishing, or deployment authority.

Teach one lesson

  1. Mark the selected row In progress. State its manifest path, duration,

group, protocol era, and evidence mode.

  1. Frame one production failure that this lesson prevents. Ask the learner to

predict the status, JSON-RPC result, or state transition before explaining

it.

  1. Draw one request boundary: producer, transport, consumer, and the exact

fields each side validates. Keep protocol state, durable application state,

transport state, authorization state, and UI state distinct.

  1. Work through Build It and Use It in small sections. For code, explain one

invariant, ask for a prediction, then run or trace the smallest case that

can falsify it.

  1. Exercise one success and at least one relevant failure. Prefer exact wire

evidence: request id, method, protocol era, headers when applicable, body,

status or error code, result type, and terminal state. Keep secret values

redacted.

  1. Require every item in the lesson's manifest checkpointEvidence. Runtime

evidence must come from observed output. Conceptual evidence must name the

unexecuted command and remaining uncertainty.

  1. Ask every post quiz item one at a time. If the quiz has no staged items,

ask all items. Do not reveal correct, an answer index, or an explanation

before the learner responds. Never put a real answer letter or the answer

distribution in a reply hint; use Reply with one letter: <A|B|C|D>.

  1. Mark the row Done only after the lesson checkpoint and quiz. Append one

compact Wire evidence row, add the score to Notes, set the next row to

Next, and update Current.

Do not use passing unit tests as a substitute for the named protocol evidence.

Do not infer HTTP behavior from an in-process function, authorization from

authentication, cancellation from a timeout, or conformance from one SDK.

Close

End with the quiz score, the exact checkpoint evidence recorded, any pending

runtime or security evidence, and the next manifest lesson. Keep the learner

on this route unless they ask to leave it.

质量与来源

所属仓库
rohitg00/ai-engineering-from-scratch
仓库星标
6.8 万
最近更新
昨天
采集时间
今天
commit
56c886c8821f
内容指纹
sha256:179fd74f575e064
文件路径
.claude/skills/learn-mcp/SKILL.md

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