learn-mcp
rohitg00/ai-engineering-from-scratch
Interactive tutor for building, securing, and operating Model Context Protocol (MCP) systems.
What is learn-mcp?
Learn-mcp is a focused interactive tutor that teaches the Model Context Protocol (MCP) learning path from AI Engineering from Scratch. It guides learners through 17 required lessons covering MCP fundamentals, clients, servers, transports, security, authorization, and production deployment, recording progress and wire evidence in MCP-LEARNING.md.
- Teaches one MCP lesson per invocation with structured progression through 17 required lessons
- Records wire evidence (requests, responses, commands, exit codes) in MCP-LEARNING.md for executable and conceptual modes
- Enforces a public deployment gate requiring Lesson 15 security checkpoint before external deployment
- Handles progress tracking, legacy file migration, and resume capability from any checkpoint
- Supports both executable mode (with Python 3 and local files) and conceptual mode (hand-traced scenarios)
- Manages optional capstone lesson (Lesson 23) only after prerequisites are complete
How to install learn-mcp
npx skills add https://github.com/rohitg00/ai-engineering-from-scratch --skill learn-mcp- Python 3 (for executable mode; conceptual mode works without it)
- Access to learning-paths/model-context-protocol.json and lesson files (local or remote)
- Write access to current working directory for MCP-LEARNING.md progress file
- Optional: TypeScript runner for Lesson 07 second implementation
How to use learn-mcp
- 1.Invoke learn-mcp using your host syntax (Codex: learn-mcp, Claude Code: /learn-mcp)
- 2.Confirm local file availability and Python 3 version to enable executable mode
- 3.Read the lesson's docs/en.md and quiz.json fully before running code
- 4.Inspect a request and response, predict the boundary result, then run or hand-trace the lab
- 5.Record observations and evidence in MCP-LEARNING.md before advancing to the next lesson
- 6.For public deployment, complete Lesson 15 security checkpoint and confirm external target authority
Use cases
- Learning to build MCP servers and clients from scratch with hands-on labs
- Understanding MCP transports, resources, prompts, and authorization mechanisms
- Preparing for production MCP deployment with security and conformance requirements
- Reviewing wire-level protocol behavior through request/response inspection
- Building durable tasks and MCP applications with proper scope and elicitation
- AI engineers building Model Context Protocol integrations
- Developers learning protocol-driven architecture and tool integration
- Teams implementing MCP clients, servers, or gateways for production use
- Learners following the AI Engineering from Scratch curriculum
learn-mcp FAQ
The skill continues in conceptual mode: you read the lesson, hand-trace a small request/response scenario, and label evidence as Conceptual. Runtime and deployment checks remain Pending until executable mode is available.
No. The required sequence is fixed (06, 07, 08, 09, 10, 11, 12, 13, 14, 15, 16, 18, 17, 28, 29, 30, 31). Numeric navigation does not apply after Lesson 16. Lesson 23 is optional and only offered after all required lessons and prerequisite paths are complete.
Before any non-loopback bind, shared ingress, hosted endpoint, or registry publication, you must complete the executable Lesson 15 checkpoint, review your threat model and external target, and obtain explicit confirmation. A skill invocation does not grant network, credential, or deployment authority.
The skill uses MCP-LEARNING.md in your current working directory to record lessons, evidence mode, wire evidence (requests, responses, commands, exit codes), and completion status. It preserves all learner notes and resumes from the first row marked 'In progress' or 'Next'.
The skill reports the collision and asks which file should own the next update. If only the legacy file exists, it is renamed to MCP-LEARNING.md with all content preserved.
Full instructions (SKILL.md)
Source of truth, from rohitg00/ai-engineering-from-scratch.
name: learn-mcp description: > 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.
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.
| Host | Start or resume |
|---|---|
| Codex | learn-mcp, or choose it from /skills |
| Claude Code | /learn-mcp |
| Other compatible hosts | Use 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:
- The lesson files are available locally.
python3 --versionsucceeds.- The learner can write
MCP-LEARNING.mdin the current working directory. - 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:
- If
MCP-LEARNING.mdexists, use it. IfMCP-ENGINEERING-LEARNING.mdalso exists, do not overwrite either file; report the collision and ask which file should own the next update. - If
MCP-LEARNING.mdis absent andMCP-ENGINEERING-LEARNING.mdexists, rename the legacy file toMCP-LEARNING.mdin 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. - 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
- Mark the selected row
In progress. State its manifest path, duration, group, protocol era, and evidence mode. - Frame one production failure that this lesson prevents. Ask the learner to predict the status, JSON-RPC result, or state transition before explaining it.
- 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.
- 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.
- 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.
- 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. - Ask every
postquiz item one at a time. If the quiz has no staged items, ask all items. Do not revealcorrect, an answer index, or an explanation before the learner responds. Never put a real answer letter or the answer distribution in a reply hint; useReply with one letter: <A|B|C|D>. - Mark the row
Doneonly after the lesson checkpoint and quiz. Append one compact Wire evidence row, add the score to Notes, set the next row toNext, and updateCurrent.
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.
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