AI Agent Guardrails MCP server - security layer
If you already use Guardrails, the guardrails mcp server is the piece that lets your assistant work with it directly. AI Agent Guardrails MCP server - security layer.
MCP server for AI agent security guardrails. Provides input validation, prompt injection detection, PII redaction, output filtering, policy enforcement, rate limiting, and comprehensive audit logging.
Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client. The configuration blocks on this page cover the common clients.
The toolset is worth reading before you wire it up, because it tells you what the integration is really for:
validate_input — Validate and sanitize incoming requests through all guardrail checksfilter_output — Filter and redact sensitive data (PII, secrets, credentials) from responsescheck_policy — Evaluate a request against security policies (RBAC, resource access, quotas)get_audit_logs — Query the audit log with filtering by type, user, time rangeget_stats — Get engine statistics including active users, block rate, request countsupdate_config — Update guardrail configuration at runtimeThis sits in the developer tooling group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. Guardrails's toolset — validate_input, filter_output, check_policy and 3 more — is a fair guide to whether it matches your workflow. It is maintained by ExpertVagabond; worth a glance at recent repository activity before you build anything load-bearing on it.
This entry was verified against Guardrails's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.
| Tool | What it does |
|---|---|
| validate_input | Validate and sanitize incoming requests through all guardrail checks |
| filter_output | Filter and redact sensitive data (PII, secrets, credentials) from responses |
| check_policy | Evaluate a request against security policies (RBAC, resource access, quotas) |
| get_audit_logs | Query the audit log with filtering by type, user, time range |
| get_stats | Get engine statistics including active users, block rate, request counts |
| update_config | Update guardrail configuration at runtime |
## Configuration
```json
{
"mcpServers": {
"guardrails": {
"type": "stdio",
"command": "node",
"args": ["/path/to/guardrails-mcp-server/index.js"]
}
}
}Configuration as documented by the project. Restart the client after saving.
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