Agent & MCP security

Operant AI: runtime security platform for AI, agents and MCP

Operant AI is a runtime security platform for AI, agents and MCP from Operant AI. It is a commercial product offered as: Cloud-native. Pricing model: not published.

  • Last reviewed

Best for

Platform teams running agents and MCP servers on Kubernetes that want runtime controls and an MCP gateway

Consider instead if

  • You want a guardrail API for a single LLM application rather than a platform for agents. See Lakera Guard.
  • You want an open-source scanner to probe a model before release. See garak.

What Operant AI does

Operant AI is a commercial platform that its homepage says will discover, detect and defend AI, agents and MCP in real time. Named products include a Semantic Firewall, Endpoint Protector, Agent Protector, AI Gatekeeper and an MCP Gateway, and the MCP section covers registries, allow and deny lists and access controls. The site describes Kubernetes-native stacks and shows prompt injection and PII detections in its dashboards. Operant also publishes Woodpecker, a red teaming command-line tool for AI and cloud apps under Apache-2.0. We could not open a pricing page or public documentation, so confirm packaging and details with the vendor.

This summary is our own wording of the sourced facts on this page.

Key facts

Each value links to the page that states it, with the date we checked it.

Latest release
Not documented in the sources we checked
Pricing model
Not published in the sources we checked Source, checked October 21, 2026: operant.ai (opens in a new tab)
Documentation
Not documented in the sources we checked
API reference
Not documented in the sources we checked
Quickstart
Not documented in the sources we checked
Security page
Not documented in the sources we checked

Capabilities

As documented by the vendor or project. The tag is our label from a controlled vocabulary.

Integrations

Where Operant AI fits in our AI security layers

Our analysis

Our editorial model, not a standard. The primary layer follows the category, except for tools whose main documented job is detection and response; other layers rest on a capability the sources document. How the model works.

AI security layers that Operant AI covers, with the role, how each applies and what it rests on
LayerRoleHow it appliesBased on
L7 Agent access Agent and tool access Primary Limit which tools, MCP servers, data and credentials an agent can use, and require approval for risky actions. Follows its category, Agent & MCP security
L6 Runtime Runtime guardrails Also covers Documents prompt injection detections. Shows prompt injection risks and detections in its dashboards
L4 Testing Testing and red teaming Also covers Documents a red teaming command line tool for agents. Publishes Woodpecker, a modular red teaming CLI for AI and cloud apps

OWASP LLM Top 10 mapping

Our analysis

The risk list is OWASP's (Top 10 for LLM Applications, 2025). The mapping is our analysis, and each row rests on a capability the sources document.

OWASP LLM risks mapped to Operant AI, with the capabilities each mapping rests on
RiskHow it appliesBased on
LLM01 Prompt Injection Dashboards surface prompt injection risks and detections. Shows prompt injection risks and detections in its dashboards
LLM06 Excessive Agency MCP allow and deny lists and access controls limit what agents can reach. Offers an MCP Gateway for enterprise MCP security; Applies registries, allow and deny lists and access controls to MCP

Alternatives and related tools

More in Agent & MCP security, ranked within the category by Coverage Score.

Open sourceApache-2.0
  • CLI
  • Self-hosted

Scans skills and MCP servers, inspects agent tool calls and keeps an audit trail around AI coding agents.

Best for: Security teams that want scanning, guardrails and an audit trail around the coding agents developers already run, starting in observe mode before anything is blocked

Coverage Score 76 out of 100
  • LLM01 Prompt Injection
  • LLM02 Sensitive Information Disclosure
  • LLM06 Excessive Agency

Reviewed

Open sourceMIT
  • CLI
  • Self-hosted

Proxies AI clients to MCP servers it runs as isolated Docker containers, with tool filters and call logs.

Best for: Developers and platform teams that already use Docker and want MCP servers to run in containers behind one gateway with per-server tool selection

Coverage Score 72 out of 100
  • LLM02 Sensitive Information Disclosure
  • LLM06 Excessive Agency

Reviewed

agentgateway

agentgateway (a Series of LF Projects, LLC)

Open sourceApache-2.0
  • CLI
  • Self-hosted
  • Cloud-native

Open-source proxy that applies auth, CEL policy and guardrails to LLM, MCP and agent-to-agent traffic.

Best for: Platform teams that want one open-source gateway in front of MCP servers and LLM providers, with token validation, CEL rules per MCP method and pluggable guardrails

Coverage Score 69 out of 100
  • LLM02 Sensitive Information Disclosure
  • LLM06 Excessive Agency

Reviewed

Operant AI FAQ

Is Operant AI open source?

The platform is commercial and proprietary. Operant publishes a separate red teaming tool, Woodpecker, on GitHub under the Apache-2.0 license.

What does Operant AI cover?

The homepage names a Semantic Firewall, Endpoint Protector, Agent Protector, AI Gatekeeper and an MCP Gateway, aimed at AI apps, agents and MCP servers.

Does Operant AI publish prices?

No. The homepage states no prices, and the pricing path we opened returned a not-found error.

Key facts you can cite

We have no commercial relationship with Operant AI.

Sources & last reviewed

Last reviewed . We compile from the vendors' own public pages and repositories and we do not run the products. Source links open in a new tab. Found a mistake? Report a correction.