Rail Score
Score agent prompts and outputs against responsible-AI policies before you ship customer-facing automation.
Overview
ai.responsibleailabs/rail-score is a Ship-phase MCP server that scores agent interactions for policy fit, prompt injection, PII, and DPDP-oriented risk.
What is this MCP server?
- Streamable HTTP MCP at mcp.responsibleailabs.ai for Claude Code, Cursor, and other MCP clients
- Responsible-AI scoring aligned with policy rules you configure for your agent workflows
- Prompt-injection and PII detection surfaced as structured guardrail signals
- DPDP-oriented checks for teams shipping in India-compliant contexts
- Server schema version 1.1.0 with GitHub source at Responsible-AI-Labs/rail-score-mcp
- Published MCP server version 1.1.0
- Single remote endpoint: https://mcp.responsibleailabs.ai/mcp (streamable-http)
- Open-source repository: github.com/Responsible-AI-Labs/rail-score-mcp
What problem does it solve?
You are shipping an AI agent without a clear way to measure policy violations, injection attempts, or leaked PII in real conversations.
Who is it for?
Solo builders shipping MCP-connected agents who need lightweight compliance and safety scoring on a streamable HTTP endpoint.
Skip if: Teams that only need generic content moderation with no agent-policy or India DPDP context, or offline-only local models with no HTTP MCP client.
What do I get? / Deliverables
After registering the remote MCP server, your agent can run structured responsible-AI scoring so you fix risky flows before users see them.
- Structured guardrail scores for agent prompts and responses
- Injection and PII risk signals usable in pre-ship review
- Repeatable MCP-callable checks in your security workflow
Recommended MCP Servers
Journey fit
How it compares
Responsible-AI scoring MCP integration, not a general-purpose LLM chat skill.
Common Questions / FAQ
Who is ai.responsibleailabs/rail-score for?
Indie and small-team builders running Claude Code, Cursor, Codex, or Windsurf who want guardrail scoring on agent traffic before production launch.
When should I use ai.responsibleailabs/rail-score?
Use it during Ship security hardening when you validate prompts, tool chains, and outputs for injection, PII, and policy breaches.
How do I add ai.responsibleailabs/rail-score to my agent?
Add the streamable HTTP remote MCP URL https://mcp.responsibleailabs.ai/mcp in your client’s MCP server config per Responsible AI Labs docs.