# io.github.cdeust/ai-architect-mcp-spec (mcpb · ai-architect-mcp-spec.mcpb)

PRD verification and host-driven generation with multi-judge consensus across 17 MCP tools.

- Trust score: 13/100 (low)
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-08-03

## Components

- mcpb · `ai-architect-mcp-spec.mcpb`: 13/100 (this document), [markdown](https://verifymcp.io/servers/cdeust-ai-architect-mcp-spec/https-github-com-cdeust-ai-architect-mcp-spec-releases-download-v0-7-0-ai-archit.md), [page](https://verifymcp.io/servers/cdeust-ai-architect-mcp-spec/https-github-com-cdeust-ai-architect-mcp-spec-releases-download-v0-7-0-ai-archit)

## Channel facts

- Registry: `mcpb`
- Package: `https://github.com/cdeust/ai-architect-mcp-spec/releases/download/v0.7.0/ai-architect-mcp-spec.mcpb`
- Version: `0.7.0`
- 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 2026-08-03.

- **Supply Chain Security**: 13/100
  - Malware scan not yet available for this package.
  - CVE data not yet available for this package.
  - No install/post-install scripts declared.
  - Dependency-health data not yet available.
- **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 0 days ago).
  - Disclosure check failed: no security disclosure policy was found in the source repository.
- **Schema Quality & AI Usability**: 0/100
  - Schema quality not yet verified: we do not have a sandbox capture of the MCP schema this version of the package serves yet.
- **Stability & Change Management**: 0/100
  - Stability not yet verified: we do not have a sandbox capture of the MCP schema this version of the package serves yet.
- **Tool Coverage**: 0/100
  - Tool coverage not yet verified: we do not have a sandbox capture of the tool definitions this version of the package serves yet.
- **Capabilities**: 0/100
  - Protocol version not yet verified: we do not have a sandbox capture of the MCP handshake this version of the package performs yet.

**Unverified: 4 categories.** Categories scored 0 because our sandbox run of this package has not given us the schema these checks need to read. That is a gap on our side rather than a finding about the package, and we only credit what we can confirm, so the score stands at 0 until the capture succeeds. We are working through the fleet, so this normally clears without any action from you.

## Install

- Download bundle: `https://github.com/cdeust/ai-architect-mcp-spec/releases/download/v0.7.0/ai-architect-mcp-spec.mcpb`

## 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.

### 2026-08-03 (score 13)

First indexed and scored.

## MCP tools (17)

### `get_config` (~14 tokens)

Get the full skill configuration

### `read_skill_config` (~21 tokens)

Read the SKILL.md content that drives PRD generation

### `check_health` (~18 tokens)

Check system health — verify all components are accessible

### `get_prd_context_info` (~33 tokens)

Get configuration for a specific PRD context type

Input parameters:

- `context` (string, required): The PRD context type

### `list_available_strategies` (~19 tokens)

List thinking strategies available to the pipeline.

### `validate_prd_section` (~68 tokens)

Run deterministic Hard Output Rules validation on a single PRD section. Returns violations found — zero LLM calls, pure regex/parsing.

Input parameters:

- `content` (string, required): The markdown content of the PRD section
- `section_type` (string, required): The type of PRD section being validated

### `validate_prd_document` (~53 tokens)

Run full document validation including cross-section checks (SP arithmetic, AC numbering, FR-AC coverage, test traceability). Returns comprehensive validation report.

Input parameters:

- `sections` (array, required): Array of PRD sections to validate

### `get_quality_history` (~33 tokens)

Get historical PRD quality scores from the evidence repository

Input parameters:

- `limit` (integer): Maximum number of records to return

### `get_strategy_effectiveness` (~40 tokens)

Get strategy performance data — actual vs expected improvement, compliance rate

Input parameters:

- `min_executions` (integer): Minimum executions required to include a strategy

### `coordinate_context_budget` (~84 tokens)

Calculate token budget allocation for PRD generation. Returns per-section retrieval limits for Cortex recall, generation budgets, and section-specific query templates. Call this BEFORE starting section generation.

Input parameters:

- `completed_sections` (array): Section types already generated
- `context_window_size` (integer): Total context window size in tokens
- `prd_context` (string, required): The PRD context type

### `map_failure_to_retrieval` (~58 tokens)

When validate_prd_section returns violations, call this to get corrective Cortex recall queries. Closes the validation→retrieval feedback loop so retries use better context.

Input parameters:

- `violations` (array, required): Violations from validate_prd_section

### `start_pipeline` (~121 tokens)

Initialize a new PRD pipeline run. Returns run_id and the first NextAction the host must execute.

Input parameters:

- `codebase_path` (string): Absolute path to the codebase. Triggers index_codebase via automatised-pipeline.
- `feature_description` (string, required): What the PRD is about — passed to all prompts
- `skip_preflight` (boolean): If true, skip the preflight step that probes Cortex (and ai-architect when codebase_path is set). Default false. Use only when you accept degraded section generation without persistent memory recall.

### `submit_action_result` (~37 tokens)

Feed an ActionResult to the pipeline runner; receive the next NextAction.

Input parameters:

- `result` (required)
- `run_id` (string, required)

### `get_pipeline_state` (~189 tokens)

Read the current pipeline state by run_id. format:'summary' (default) returns the lightweight envelope; format:'full' returns the whole state, bounded to the Claude Code 100,000-char MCP response budget by shedding least-relevant detail first (observable __bounded markers; full grounding re-fetchable via format:'grounding'); format:'grounding' returns the codebase_grounding (+ prd_validation when it fits) blobs format:'full' sheds first; format:'validation' returns prd_validation alone (the blob format:'grounding' sheds when the pair overshoots); format:'action' returns the UNBOUNDED last action emitted for this run (including full spawn_subagents prompts) — the recovery path when a start_pipeline/submit_action_result response carries a __bounded marker on its action.

Input parameters:

- `format` (string)
- `run_id` (string, required)

### `plan_section_verification` (~69 tokens)

Extract claims from a PRD section and select judges. Returns JudgeRequest[] the host must execute via Agent tool in parallel.

Input parameters:

- `codebase_excerpts` (array)
- `content` (string, required)
- `memory_excerpts` (array)
- `section_type` (string, required)

### `plan_document_verification` (~50 tokens)

Same as plan_section_verification but across all sections of a document.

Input parameters:

- `codebase_excerpts` (array)
- `memory_excerpts` (array)
- `sections` (array, required)

### `conclude_verification` (~363 tokens)

Aggregate JudgeVerdict[] from spawned subagents into a VerificationReport (consensus + dissent). IMPORTANT: omitting claim_types when a reliability repository is open suppresses observation flushing for this batch — the calibration data will be missing for these runs (one-sided censoring).

Input parameters:

- `claim_types` (object): Map of claim_id → claim_type. When provided, enables per-(judge × claim_type) reliability lookup. Omit to fall back to per-agent scalar priors. Source: derive from plan_section_verification / plan_do…
- `claims` (array): OPTIONAL. Pass the Claim objects from the corresponding plan_section_verification / plan_document_verification response if you want oracle-based ground truth (breaks Curie A2 annotator-circularity fo…
- `consensus_strategy` (string)
- `run_id` (string): Pipeline run_id — required for calibrated Bayesian reliability weights (CC-3 control-arm seam uses this to partition treatment vs control runs). When absent, falls back to Beta(7,3) prior for all jud…
- `scope` (string)
- `section_type` (string)
- `verdicts` (array, required)

## Diagnostics

Captured diagnostic sections: Provenance. The full working is on the page: https://verifymcp.io/servers/cdeust-ai-architect-mcp-spec/https-github-com-cdeust-ai-architect-mcp-spec-releases-download-v0-7-0-ai-archit#diagnostics

## Score history

- 2026-08-03: 13

## Links

- Repository: https://github.com/cdeust/ai-architect-mcp-spec
- Website: https://ai-architect.tools/
- Changelog RSS feed: https://verifymcp.io/servers/cdeust-ai-architect-mcp-spec/https-github-com-cdeust-ai-architect-mcp-spec-releases-download-v0-7-0-ai-archit/changelog.xml
- Changelog JSON feed: https://verifymcp.io/servers/cdeust-ai-architect-mcp-spec/https-github-com-cdeust-ai-architect-mcp-spec-releases-download-v0-7-0-ai-archit/changelog.json
- HTML version of this page: https://verifymcp.io/servers/cdeust-ai-architect-mcp-spec/https-github-com-cdeust-ai-architect-mcp-spec-releases-download-v0-7-0-ai-archit