# io.github.uchit/aipatterns-mcp-server (npm · aipatterns-mcp-server)

Search AU enterprise AI patterns, benchmarks, incidents, and regulatory changes.

- Trust score: 69/100 (medium)
- Change this week: +23
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-08-03

## Components

- npm · `aipatterns-mcp-server`: 69/100 (this document), [markdown](https://verifymcp.io/servers/uchit-aipatterns-mcp-server/aipatterns-mcp-server.md), [page](https://verifymcp.io/servers/uchit-aipatterns-mcp-server/aipatterns-mcp-server)

## Channel facts

- Registry: `npm`
- Package: `aipatterns-mcp-server`
- Version: `1.1.0`
- 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**: 86/100
  - No malware found by supply-chain analysis.
  - Only part of the dependency tree could be resolved (94 of 98), so this covers what we could see, not the whole tree.
  - No install/post-install scripts declared.
  - Only part of the dependency tree could be resolved (94 of 98), 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 30 days ago).
  - Disclosure check failed: no security disclosure policy was found in the source repository.
- **Schema Quality & AI Usability**: 77/100
  - AI-judged instruction clarity (excellent).
  - Tool/resource definitions use about 465 tokens (~93/item across 5 items; 5 tools + 0 resources), lean.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 23/100
  - Stability observed for 7 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 uchit-aipatterns-mcp-server -- npx -y aipatterns-mcp-server
```

### Codex

```bash
codex mcp add uchit-aipatterns-mcp-server -- npx -y aipatterns-mcp-server
```

### opencode

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

### OpenClaw

```bash
openclaw mcp add uchit-aipatterns-mcp-server --command npx --arg -y --arg aipatterns-mcp-server
```

### Hermes

```yaml
mcp_servers:
  uchit-aipatterns-mcp-server:
    command: "npx"
    args: ["-y", "aipatterns-mcp-server"]
```

### Other

```json
{
  "mcpServers": {
    "uchit-aipatterns-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "aipatterns-mcp-server"
      ]
    }
  }
}
```

## 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 69, +4)

- [functional improvement] Stability: unverified → 0.23

### 2026-08-02 (score 65, +44)

- [security regression] Provenance: unverified → fail
- [security improvement] Known CVEs: unverified → partial
- [security improvement] Install scripts: unverified → pass
- [security improvement] Malware scan: unverified → pass
- [security] Stability: Stability not yet verified: not enough scan history yet (needs a 30-day window).
- [functional regression] Security disclosure: fail → unverified
- [functional regression] Tool coverage: 100 → unverified
- [functional improvement] Schema quality: unverified → excellent
- [functional improvement] License: unverified → pass
- [functional improvement] Dependency health: unverified → partial
- [functional improvement] Maintenance: unverified → pass
- [functional improvement] MCP protocol: unverified → pass
- [functional] First check of Schema quality: unverified
- [functional] Licence: MIT

### 2026-07-31 (score 21, −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 28, −18)

- [security regression] Malware scan: pass → unverified

### 2026-07-27 (score 46)

First indexed and scored.

## MCP tools (5)

### `search_patterns` (~125 tokens)

Search the aipatterns.com.au AI pattern library. Returns matching patterns with slug, title, description, maturity level, and category. Useful for finding design patterns relevant to a specific AI use case, capability, or compliance concern.

Input parameters:

- `category` (string): Optional category filter (e.g. agentic-ai, governance, security, rag, observability, compliance, human-in-the-loop)
- `maturity` (string): Optional maturity filter (e.g. production, beta, experimental)
- `query` (string, required): Search term to match against pattern title, description, or content

### `get_pattern` (~62 tokens)

Retrieve full detail of a specific AI pattern from aipatterns.com.au, including implementation guidance and regulatory context. Use the slug returned by search_patterns.

Input parameters:

- `slug` (string, required): Pattern slug, e.g. "agentic-ai/agent-checkpoint-and-recovery"

### `get_incidents` (~92 tokens)

Retrieve notable Australian AI incidents. Useful for understanding real-world failures, regulatory enforcement actions, and which patterns could have prevented the incident.

Input parameters:

- `limit` (number): Maximum number of incidents to return (default 5)
- `sector` (string): Filter by sector: banking, insurance, government, retail, healthcare, utilities
- `severity` (string): Filter by severity: critical, high, medium, low

### `get_sector_benchmark` (~79 tokens)

Get the AU AI Maturity Index benchmark score for a specific sector. Returns overall score, dimension scores (adoption, governance, investment, incidents), sector rank, and national averages. Scores computed from Q2 2026 evidence base.

Input parameters:

- `sector` (string, required): One of: banking, insurance, government, retail, healthcare, utilities

### `get_regulatory_changes` (~107 tokens)

Retrieve recent and upcoming Australian AI regulatory changes (APRA, OAIC, ASIC, TGA, Privacy Act reform). Useful for understanding compliance obligations when building AI systems for the Australian market.

Input parameters:

- `impact_level` (string): Filter by impact level: critical, high, medium, low
- `limit` (number): Maximum number of changes to return (default 5)
- `regulator` (string): Filter by regulator abbreviation: APRA, OAIC, ASIC, TGA

## Diagnostics

Captured diagnostic sections: Provenance, Dependencies. The full working is on the page: https://verifymcp.io/servers/uchit-aipatterns-mcp-server/aipatterns-mcp-server#diagnostics

## Score history

- 2026-08-03: 69
- 2026-08-02: 65
- 2026-08-01: 21
- 2026-07-31: 21
- 2026-07-30: 28
- 2026-07-28: 46
- 2026-07-27: 46

## Links

- npm package: https://www.npmjs.com/package/aipatterns-mcp-server
- Socket report: https://socket.dev/npm/package/aipatterns-mcp-server
- Repository: https://github.com/uchit/aipatterns-mcp-server
- Changelog RSS feed: https://verifymcp.io/servers/uchit-aipatterns-mcp-server/aipatterns-mcp-server/changelog.xml
- Changelog JSON feed: https://verifymcp.io/servers/uchit-aipatterns-mcp-server/aipatterns-mcp-server/changelog.json
- HTML version of this page: https://verifymcp.io/servers/uchit-aipatterns-mcp-server/aipatterns-mcp-server