Engineering
SDK integration guides, API usage patterns, and implementation best practices for responsible AI systems.
9 articles
A tool-call firewall for AI agents using MCP
Score every tool call an agent wants to make before it runs. The RAIL Score MCP server returns ALLOW, FLAG, or BLOCK, so you can stop destructive or malicious actions in one guard.
RAIL Score MCP quickstart: score content and enforce a policy
Connect to the RAIL Score MCP server with the Python mcp SDK, score content across 8 responsible-AI dimensions, and turn those scores into an allow, flag, or block decision with a policy.
Add guardrails to any AI agent with one MCP URL
Wrap an agent turn with prompt-injection detection, a tool-call firewall, PII redaction, and policy scoring using the RAIL Score MCP server and the Python mcp SDK.
DPDP compliance for AI agents: mask and gate Indian personal data over MCP
Use the RAIL Score MCP server to detect and mask Aadhaar, PAN, GSTIN, and bank details, then gate processing steps for consent and cross-border rules under India's DPDP Act 2023.
Safe Regeneration: how RAIL automatically fixes unsafe AI outputs
Why blocking unsafe AI outputs is not enough. How RAIL's Safe Regeneration moves beyond binary flag-and-block to iteratively detect, fix, and verify AI responses -- preserving utility while enforcing safety.
Integrating RAIL Score into your AI workflow
How to add RAIL Score evaluation at every stage of your AI pipeline: development, CI, production, and monitoring.
Building an ethics-aware chatbot: complete tutorial
Build a chatbot with built-in ethical guardrails using OpenAI, RAIL Score SDK, and real-time safety evaluation.
Integrating RAIL Score in Python: complete developer guide
Step-by-step guide to integrating RAIL Score evaluation into your Python application using the official SDK.
Bias detection in text: from traditional ML to RAIL API
How bias detection has evolved from keyword matching to multi-dimensional evaluation with the RAIL Score API.