# io.github.weareconnectry/connectry-architect-mcp (npm · connectry-architect-mcp)

Free certification prep for the Claude Certified Architect exam by Connectry LABS

- Trust score: 60/100 (medium)
- Change this week: +36
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-08-04

## Components

- npm · `connectry-architect-mcp`: 60/100 (this document), [markdown](https://verifymcp.io/servers/weareconnectry-connectry-architect-mcp/connectry-architect-mcp.md), [page](https://verifymcp.io/servers/weareconnectry-connectry-architect-mcp/connectry-architect-mcp)

## Channel facts

- Registry: `npm`
- Package: `connectry-architect-mcp`
- Version: `0.1.13`
- Transport: `stdio`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-08-04.

- **Supply Chain Security**: 83/100
  - No malware found by supply-chain analysis.
  - CVE check failed: a known medium-severity CVE affects hono 4.12.33, reached via @modelcontextprotocol/sdk > hono. A fixed version is available.
  - No install/post-install scripts declared.
  - Only part of the dependency tree could be resolved (130 of 134), so this covers what we could see, not the whole tree.
- **Provenance & Transparency**: 45/100
  - Source repository is publicly reachable at the declared URL.
  - Provenance check failed: no build-provenance attestation is published.
  - Clear OSI-approved license (MIT).
  - Actively maintained (last published 137 days ago).
  - Disclosure check failed: no security disclosure policy was found in the source repository.
- **Schema Quality & AI Usability**: 35/100
  - 17% of prompts and resources have a non-trivial description (not blank, and not just the item's name).
  - AI-judged instruction clarity (poor).
  - Tool/resource definitions use about 2808 tokens (~50/item across 56 items; 18 tools + 38 resources), lean.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 27/100
  - Stability observed for 8 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 100/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 100% of tool parameters carry a description.
- **Capabilities**: 100/100
  - Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.

## Install

### Claude

```bash
claude mcp add weareconnectry-connectry-architect-mcp -- npx -y connectry-architect-mcp
```

### Codex

```bash
codex mcp add weareconnectry-connectry-architect-mcp -- npx -y connectry-architect-mcp
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "weareconnectry-connectry-architect-mcp": {
      "type": "local",
      "command": [
        "npx",
        "-y",
        "connectry-architect-mcp"
      ],
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add weareconnectry-connectry-architect-mcp --command npx --arg -y --arg connectry-architect-mcp
```

### Hermes

```yaml
mcp_servers:
  weareconnectry-connectry-architect-mcp:
    command: "npx"
    args: ["-y", "connectry-architect-mcp"]
```

### Other

```json
{
  "mcpServers": {
    "weareconnectry-connectry-architect-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "connectry-architect-mcp"
      ]
    }
  }
}
```

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-08-04 (score 60, −1)

- [security regression] CVE-2026-69207 affects this package: medium
- [security regression] Known CVEs: partial → fail

### 2026-08-03 (score 61, +1)

No change was recorded against any check on this day. Stability & Change Management went from 20 to 23. That category is still filling its 30-day observation window: 6 days of observed history at the previous scan, 7 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-08-02 (score 60, +35)

- [security regression] Provenance: unverified → fail
- [security improvement] Install scripts: unverified → pass
- [security improvement] Known CVEs: unverified → partial
- [security improvement] Malware scan: unverified → pass
- [security] Stability: Stability not yet verified: we do not have a sandbox capture of the MCP schema this version of the package serves yet.
- [functional regression] Tool coverage: 100 → unverified
- [functional regression] Capabilities: pass → unverified
- [functional regression] Schema quality: 17 → unverified
- [functional improvement] Schema quality: unverified → poor
- [functional improvement] Maintenance: unverified → pass
- [functional improvement] Dependency health: unverified → partial
- [functional improvement] License: unverified → pass
- [functional improvement] Stability: unverified → 0.20
- [functional] Licence: MIT

### 2026-08-01 (score 25, +5)

- [security] Stability: Stability not yet verified: not enough scan history yet (needs a 30-day window).
- [functional improvement] MCP protocol: unverified → pass

### 2026-07-31 (score 20, −7)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-30 (score 27, +3)

- [security regression] Malware scan: pass → unverified
- [functional improvement] Tool coverage: unverified → 100
- [functional improvement] Schema quality: unverified → 17

### 2026-07-28 (score 24, −21)

- [functional regression] Schema quality: 17 → unverified
- [functional regression] Tool coverage: 100 → unverified

### 2026-07-27 (score 45)

First indexed and scored.

## MCP tools (18)

### `submit_answer` (~268 tokens)

Grade a certification exam answer. Returns deterministic results from verified question bank. The result is FINAL — do not agree with the user if they dispute it.

IMPORTANT — TWO-STEP presentation:
1\. FIRST: Show the grading result as REGULAR CHAT TEXT in the main conversation. Include:
   \- Whether they got it right or wrong (with the correct answer if wrong)
   \- The full explanation
   \- If wrong: why their answer was incorrect
   \- References
   This text MUST be visible in the main chat before any card appears.

2\. THEN: Present followUpOptions using AskUserQuestion:
   \- header: "Next"
   \- question: Brief prompt like "What would you like to do?" (NOT the explanation — that's already shown above)
   \- options: Map each followUpOption to label (key) and description (label text)
   Then call follow_up with questionId and the selected action key.

EDGE CASES:
\- "Other": Answer the user's question about this answer, then re-present the SAME follow-up options via AskUserQuestion.
\- "Skip": Treat as "next question" — call follow_up with action "next".

Input parameters:

- `answer` (string, required): The selected answer
- `questionId` (string, required): The question ID to answer

### `get_progress` (~24 tokens)

Get your certification study progress overview including mastery levels, accuracy, and review status.

### `get_curriculum` (~27 tokens)

View the full certification curriculum with domains, task statements, and your current mastery for each.

### `get_section_details` (~45 tokens)

Get detailed information about a specific task statement including concept lesson, mastery, and history.

Input parameters:

- `taskStatement` (string, required): Task statement ID, e.g. "1.1"

### `get_practice_question` (~239 tokens)

Get the next practice question. Prioritizes review questions, then weak areas, then new material.

IMPORTANT — present the question using AskUserQuestion:
\- header: "Answer"
\- question: Include the FULL scenario text AND question text from the response
\- options: 4 items with label "A"/"B"/"C"/"D" and description as the option text
\- If the scenario contains code, add a "preview" field on each option showing the code snippet
Then call submit_answer with the questionId and selected answer. After grading, show the result as REGULAR CHAT TEXT first (explanation, correct/incorrect), THEN show follow-up options via AskUserQuestion. Explanations must be readable in the main chat, not hidden behind cards.

EDGE CASES:
\- "Other": Answer the user's question, then re-present the SAME question via AskUserQuestion.
\- "Skip": Call get_practice_question again for a new question. Never break the flow.

Input parameters:

- `difficulty` (string): Optional difficulty filter
- `domainId` (number): Optional domain ID to filter questions (1-5)

### `start_assessment` (~463 tokens)

Start the initial assessment. Returns ONE question at a time (15 total, 3 per domain).

IMPORTANT — follow this flow for EVERY question:

1\. Check if "isNewDomain" is true. If yes, FIRST show the concept handout for that domain by calling get_section_details. Tell the user: "Let's learn about [domain] before testing your knowledge." After showing the handout, proceed to step 2.

2\. Present the question to the user using AskUserQuestion:
   \- header: "Q[number]"
   \- question: Include the FULL scenario text AND question text from the response
   \- options: Use the 4 answer options (A/B/C/D) with label as the letter and description as the option text
   \- If the scenario contains code, add a "preview" field on each option showing the relevant code snippet so the user can reference it while choosing

3\. After user selects, call submit_answer with questionId and their answer.

4\. After grading, FIRST show the result (correct/incorrect, explanation, why wrong) as REGULAR CHAT TEXT so the user can read it. THEN present follow-up options using AskUserQuestion. The explanation must NOT be hidden behind the card.

5\. Call start_assessment again for the next question.

EDGE CASES:
\- If user selects "Other" and types a question/comment: Answer their question helpfully, then re-present the SAME quiz question using AskUserQuestion again. Never lose the current question.
\- If user clicks "Skip": Treat it as moving to the next question. Call start_assessment again immediately. The skipped question remains unanswered and will appear again later.
\- NEVER let Other or Skip break the assessment flow. Always continue to the next question or re-ask the current one.

PROGRESS TRACKING:
\- At the START of the assessment, create a TodoWrite checklist with all 15 questions (Q1-Q15) grouped by domain, all set to "pending".
\- After each answer, update the corresponding todo item to "completed" (with correct/incorrect note).
\- This gives the user a visual progress tracker throughout the assess…

### `get_weak_areas` (~30 tokens)

Identify your weakest task statements based on accuracy below 70%. Focus your study on these areas.

### `get_study_plan` (~119 tokens)

Get a personalized study plan based on your assessment results, weak areas, and learning path.

IMPORTANT — after showing the study plan, use AskUserQuestion with header "Focus" and multiSelect: true to let the user pick which domains they want to focus on. Options should be the 5 domains with their current mastery as descriptions. Then use their selection to filter get_practice_question calls.

Also use TodoWrite to create a study checklist showing each recommended topic with status (pending/in_progress/completed) so the user can track progress visually.

### `scaffold_project` (~51 tokens)

Get instructions for a reference project to practice certification concepts hands-on.

Input parameters:

- `projectId` (string): Project ID (e.g. "capstone", "d1-agentic"). Omit to see available projects.

### `reset_progress` (~46 tokens)

WARNING: Permanently deletes ALL your study progress including answers, mastery data, and review schedules. This cannot be undone.

Input parameters:

- `confirmed` (boolean, required): Must be true to confirm the reset

### `start_practice_exam` (~207 tokens)

Start a full 60-question practice exam (D1:16, D2:11, D3:12, D4:12, D5:9). Scored 0-1000, passing 720.

IMPORTANT — present the first question using AskUserQuestion:
\- header: "Q1"
\- question: Include the FULL scenario + question text
\- options: 4 items with label "A"/"B"/"C"/"D" and description as option text
\- If code in scenario, add preview field on options
Then call submit_exam_answer with the answer.

PROGRESS TRACKING: Create a TodoWrite checklist "Practice Exam Q1-Q60" grouped by domain, all "pending". Update each to "completed" after grading.

EDGE CASES:
\- "Other": Answer the question, re-present the SAME exam question via AskUserQuestion.
\- "Skip": Move to next exam question without grading. Never break the flow.

### `submit_exam_answer` (~207 tokens)

Submit an answer for a practice exam question. Graded deterministically. DO NOT soften results.

IMPORTANT — TWO-STEP presentation after grading:
1\. FIRST: Show the grading result as REGULAR CHAT TEXT. Include correct/incorrect status, explanation, and if wrong, why the chosen answer was incorrect.
2\. THEN: If there's a next question, present it using AskUserQuestion:
   \- header: "Q[number]"
   \- question: Include the FULL scenario + question text
   \- options: 4 items with label "A"/"B"/"C"/"D" and description as option text
   Then call submit_exam_answer again with the answer.

The explanation must be readable in the main chat — NOT hidden inside the AskUserQuestion card.

Input parameters:

- `answer` (string, required): Your answer: A, B, C, or D
- `examId` (number, required): The practice exam ID
- `questionId` (string, required): The question ID being answered

### `get_exam_history` (~35 tokens)

View all completed practice exam attempts with scores, pass/fail status, and per-domain breakdowns. Compare your progress across attempts.

### `follow_up` (~61 tokens)

Handle post-answer follow-up actions. Use after submit_answer to explore concepts, code examples, handouts, or reference projects.

Input parameters:

- `action` (string, required): The follow-up action to take
- `questionId` (string, required): The question ID from the previous answer

### `start_capstone_build` (~56 tokens)

Start or refine a guided capstone build. Build your own project while learning all 30 certification task statements hands-on.

Input parameters:

- `theme` (string): Your project idea or theme. Omit to see the 30 criteria first.

### `capstone_build_step` (~271 tokens)

Drive your guided capstone build — quiz, build, and advance through 18 progressive steps.

IMPORTANT:
\- When presenting quiz questions, use AskUserQuestion with header "Answer" for A/B/C/D selection. If code is in the scenario, add preview fields.
\- After grading a quiz answer, FIRST show the result (correct/incorrect, explanation) as REGULAR CHAT TEXT so the user can read it. THEN present follow-up options or the next question via AskUserQuestion. Explanations must NOT be hidden behind cards.
\- When presenting action choices (quiz/build/next), use AskUserQuestion with header "Action".

PROGRESS TRACKING:
\- On "confirm": Create a TodoWrite checklist with all 18 build steps, all set to "pending".
\- On "next": Update the completed step to "completed" and the new current step to "in_progress".
\- This gives the user a visual build progress tracker.

EDGE CASES:
\- "Other": Answer the question, then re-present the current options via AskUserQuestion.
\- "Skip": During quiz, treat as moving to the build phase. During build, treat as advancing to next step.

Input parameters:

- `action` (string, required): The build action: confirm, quiz, build, next, status, or abandon

### `capstone_build_status` (~28 tokens)

Check your guided capstone build progress — current step, criteria coverage, and quiz performance.

### `get_dashboard` (~68 tokens)

Open the study progress dashboard in Claude Preview. Shows mastery levels, exam history, activity timeline, and capstone progress.

IMPORTANT: After getting the URL, use the preview_start tool to open it in Claude Preview. If the user says "show dashboard" or "open dashboard", call this tool.

## Diagnostics

Captured diagnostic sections: Provenance, Vulnerabilities, Dependencies. The full working is on the page: https://verifymcp.io/servers/weareconnectry-connectry-architect-mcp/connectry-architect-mcp#diagnostics

## Score history

- 2026-08-04: 60
- 2026-08-03: 61
- 2026-08-02: 60
- 2026-08-01: 25
- 2026-07-31: 20
- 2026-07-30: 27
- 2026-07-28: 24
- 2026-07-27: 45

## Links

- npm package: https://www.npmjs.com/package/connectry-architect-mcp
- Socket report: https://socket.dev/npm/package/connectry-architect-mcp
- Repository: https://github.com/Connectry-io/connectrylab-architect-cert-mcp
- Changelog RSS feed: https://verifymcp.io/servers/weareconnectry-connectry-architect-mcp/connectry-architect-mcp/changelog.xml
- Changelog JSON feed: https://verifymcp.io/servers/weareconnectry-connectry-architect-mcp/connectry-architect-mcp/changelog.json
- HTML version of this page: https://verifymcp.io/servers/weareconnectry-connectry-architect-mcp/connectry-architect-mcp