// moorai vs operant

MoorAI vs Operant Endpoint Protector

Both put a security agent on the developer's machine, in front of AI agents — the difference is what that agent reads, and what leaves the device. Operant and MoorAI agree the endpoint is the right control point. Both ship a native agent, both sit in front of Claude Code / Cursor / Copilot, and both govern MCP tool calls. If you've decided the endpoint is where controls belong, you're choosing between two products that share that thesis.

The divergence is the data model. Operant's core mechanism is content inspection: per its public materials it inspects “every prompt, file upload, and tool call,” does “inline auto-redaction for 100+ sensitive data types,” and applies “bidirectional tokenization” — and it logs “every MCP tool call… with full prompt context.” That's powerful, but definitionally content-processing, and it's proprietary, so you can't audit how content is handled on the box. MoorAI takes the opposite default: content-free by construction — only one-way hashes and metadata leave the endpoint, and because the agent is open source (AGPL), that claim is verifiable by reading the code, not taken on trust.

MoorAIOperant Endpoint Protector
Content handlingContent-free by construction — one-way hashes + metadata; content never leaves unless an admin enables a capture tierInspects prompts, files, tool calls; inline redaction + “bidirectional tokenization” (per Operant)
What leaves the device by defaultHashes + event metadata onlyTelemetry to SIEM; “every MCP tool call logged with full prompt context” (per Operant)
Open-source / auditableOn-device agent is open source (AGPL); the content-free claim is code-verifiableProprietary; no open-source component stated
Coding-agent-nativeYes — Claude Code, Cursor, Copilot and similarYes — Claude Code, Cursor, Copilot, Cline, Windsurf, Aider (per Operant)
Deployment modelNative on-device agent (macOS; Windows) + consoleNative app for macOS, Windows, Linux; MDM/Jamf/Intune rollout (per Operant)
MCP governanceApproval-gating + rug-pull / tool-drift detectionRuntime RBAC for MCP clients/servers/tools; ScopeGuard, Intent Guards (per Operant)
Output screeningYes — incl. insecure-code-generation screeningCodeInjectionGuard inspects AI-generated commands/shell/packages (per Operant)
Enforcement / killKill-on-critical; model-endpoint allow-listing; entitlement envelopeBlock-before-execution; quarantine; rate/token throttling (per Operant)
Detection frameworksOWASP LLM Top 10, MITRE ATLAS mappingOWASP coverage; SOC 2 Type II; CoSAI/OWASP membership (per Operant)
Fleet governanceManaged + unmanaged fleet governanceEnterprise rollout via MDM + IdP; AI/MCP registry (per Operant)
Compliance / SIEMCompliance mapping + SIEM streamingSIEM forwarding (Splunk, Datadog, Elastic, Chronicle); SOC 2 Type II (per Operant)
Pricing modelConsole free up to 200 users; contact for pricingNot publicly disclosed

Honest limits

All Operant claims here are drawn from Operant's public materials (operant.ai product/solution pages and the May 2026 launch coverage) and attributed “per Operant.” Operant does not publish pricing or claim an open-source component, so those rows say so explicitly.

Audit the design before you install it.

No demo required to check the claim — the on-device agent is open source, so you can read exactly what it hashes and what it sends.

Read the source Start free up to 200 users ↗

glick.run — AGPL-3.0