ai-governance-controls
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 | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| ai_safety_screenA | Screen an AI system's configuration for safety risks (SAF-001). Evaluates a system prompt against the SAF-002 output validation control. Returns a structured analysis framework for the host to complete. Args: system_prompt: The system prompt or configuration to screen. context: Optional deployment context (e.g. "customer-facing chatbot for a bank"). |
| ai_risk_classifyA | Classify an AI deployment's risk tier and applicable regulations (HOC-001). Evaluates a deployment description against the HOC-001 risk classification control, referencing EU AI Act risk tiers and NIST AI RMF. Returns a structured analysis framework for the host to complete. Args: deployment_description: Description of the AI system and how it is deployed. Include: what the system does, who uses it, what decisions it influences, what data it processes, and any human oversight in place. |
| ai_red_teamA | Generate adversarial test cases for an AI system prompt (SEC-005). Produces a red team runbook: specific adversarial inputs tailored to the system prompt, organized by attack category. Returns a structured framework for the host to generate the test cases. Args: system_prompt: The system prompt to red team. num_test_cases: Number of test cases to generate (default 10, max 30). |
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 3 tools
Each tool targets a distinct governance activity: red teaming, risk classification, and safety screening. No overlap in purpose, making them easily distinguishable for an agent.
All tools use snake_case with 'ai_' prefix and a descriptive term + action. 'ai_red_team' slightly deviates as noun-noun versus verb-noun in others, but the pattern is mostly consistent.
Three tools cover core governance areas but feel minimal for a comprehensive governance suite. The count is acceptable for a focused server but borderline low for broader coverage.
Only three of many possible AI governance controls are implemented (e.g., missing bias, privacy, explainability). Moreover, tools return analysis frameworks rather than performing actual analysis, leaving significant gaps.