ai.responsibleailabs/rail-score (Model Context Protocol Server)
The ai.responsibleailabs/rail-score MCP server provides responsible-AI guardrails for agents, including scoring with policy, prompt injection detection, and PII detection. It also references DPDP, aligning agent behavior with policy and compliance requirements. The server is positioned for use with Model Context Protocol (MCP) tooling and responsible-AI workflows.
🛠️ Key Features
- Scoring with policy
- Prompt injection detection
- PII detection
- DPDP-related guardrails
🚀 Use Cases
- Agent evaluation using policy-based scoring
- Detecting prompt injection attempts for agents
- Identifying PII during agent processing
- Applying DPDP-focused compliance guardrails
⚡ Developer Benefits
- Centralized guardrails for agent workflows
- Structured use within MCP-based environments
- Coverage across policy scoring, injection detection, and PII detection
⚠️ Limitations
- No tool count or additional implementation details were provided beyond the listed guardrail capabilities