aipatterns-mcp-server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| search_patternsA | 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. |
| get_patternA | 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. |
| get_incidentsB | Retrieve notable Australian AI incidents. Useful for understanding real-world failures, regulatory enforcement actions, and which patterns could have prevented the incident. |
| get_sector_benchmarkA | 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. |
| get_regulatory_changesA | 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. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 5 tools
Each tool targets a distinct aspect of the domain: pattern search, pattern detail, incidents, sector benchmarks, and regulatory changes. There is no overlap between their purposes.
All tool names follow a consistent verb_noun pattern (e.g., search_patterns, get_pattern, get_incidents). No deviations or mixed conventions.
With 5 tools, the server is well-scoped for its domain. Each tool adds clear value without redundancy or excessive granularity.
The tool set covers key operations: searching and retrieving patterns, incidents, benchmarks, and regulatory changes. A minor gap is the lack of a dedicated tool to list sectors for benchmarking, but the search tool likely compensates.