Agent Governance

Visibility and governance across the agentic development stack

Monitor AI coding agents, enforce policies, detect dangerous commands, and harden code generation—across every workstation and cloud agent where code is written.
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Complete visibility
Monitor AI coding agents, models, MCP tools, and skills across developer workstations and cloud agents.
Govern coding agents & LLMs
Enforce how agents behave with out-of-the-box and customizable policies—so you can block, allow, or audit actions across prompts, commands, tools, and skills, and control access to sensitive files and directories.
Secure by default
Secure AI-generated code from the start with guardrails to block risky packages before they ever reach the workstation—on the cloud or local.
Securing code written by humans and AI at
Cursor logoDropbox logoGlean logoOpenAI logomongoDB LogoPeloton logoRobinhood logoRubrik logo
Cursor logoDropbox logoGlean logoOpenAI logomongoDB LogoPeloton logoRobinhood logoRubrik logo
Cursor logoDropbox logoGlean logoOpenAI logomongoDB LogoPeloton logoRobinhood logoRubrik logo
Implementing Endor Labs is easy. I had exactly what I needed between the docs, CLI tool, a GitHub Action, and a GitHub app— all readily available."
Alex Olea Photo
Alex Olea
DevSecOps Engineer, Starburst

How it works

Visibility
Bring visibility to agentic development
See which agents and models are in use, the MCP servers they connect to, and the skills and hooks they run across your environment.
Agents and models
Monitor which agentic IDEs are in use (like Cursor or Claude Code), along with version details, session counts, and  associated accounts.
MCPs
Inventory every MCP agents are connected to—local or remote—along with usage, actions, and last activity.
Skills and hooks
Track which skills and hooks run across agents, how often they’re used, and their risk scores to identify high-risk behaviors.
Endor Labs AI Governance dashboard showing developers with AI 5, AI coding agents 3, AI model sessions 25, unapproved MCP servers 7, charts for AI models in coding agents, MCP servers invoked, and tools used, plus most triggered policy violations and file access blocked.Endor Labs AI Governance dashboard showing developers with AI 5, AI coding agents 3, AI model sessions 25, unapproved MCP servers 7, charts for AI models in coding agents, MCP servers invoked, and tools used, plus most triggered policy violations and file access blocked.Endor Labs AI Governance dashboard showing developers with AI 5, AI coding agents 3, AI model sessions 25, unapproved MCP servers 7, charts for AI models in coding agents, MCP servers invoked, and tools used, plus most triggered policy violations and file access blocked.
Table listing security policies with columns for Policy Name, Details, Payload Preview, and Agent, showing banned dangerous commands, server messages, credential file access, and self-modification alerts.Table listing security policies with columns for Policy Name, Details, Payload Preview, and Agent, showing banned dangerous commands, server messages, credential file access, and self-modification alerts.Table listing security policies with columns for Policy Name, Details, Payload Preview, and Agent, showing banned dangerous commands, server messages, credential file access, and self-modification alerts.
Governance
Configure and enforce agent behavior
Enforce policies on how agents interact with your code, systems, and data.
Agent activity
Trace MCP calls, prompts, and skills back to the agent and user behind each action.
System-level governance
Govern shell commands and file access. Prevent destructive actions, protect sensitive data, and stop risky behavior before it executes.
Configurable policies
Use built-in policies or define your own with RegEx to block high-risk actions or trigger alerts across key control points.
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FAQs

Read our documentation
What is Agent Governance?

Agent Governance is a capability that gives teams visibility and control over AI coding agents across developer workstations and cloud environments. It helps organizations monitor which agents, models, and tools are being used, and enforce policies to prevent risky or unauthorized behavior.

Who should use Agent Governance?

Agent Governance is designed for:

  • Security teams managing software supply chain risk
  • Platform and DevOps teams overseeing developer environments
  • Organizations adopting AI coding tools at scale

It’s especially useful where multiple AI agents and tools are used across teams.

What can Agent Governance detect and block?

Agent Governance can enforce controls across shell commands (e.g., blocking rm -rf or reverse shells), file access (e.g., blocking reads of .env or .pem credential files), MCP tool calls (e.g., preventing DROP or DELETE queries), prompts (e.g., blocking prompt injection or API key leakage), and agent skills. Both built-in policies and custom regex-based rules are supported.

How does Agent Governance enforce security policies?

Agent Governance allows teams to define and enforce policies across key areas like:

  • Shell commands (e.g., blocking destructive commands)
  • File access (e.g., restricting secrets)
  • MCP tool usage (e.g., preventing dangerous queries)
  • Prompts (e.g., detecting prompt injection or sensitive data)
  • Skills (e.g., controlling risky behaviors)

Policies can block actions in real time or trigger alerts for review.

Is Agent Governance available today?

Agent Governance is available today. Teams can request access or book a demo to get started.

Does Agent Governance require installing agents or IDE plugins on developer machines?

No. Agent Governance is designed to work without heavy agents, per-IDE plugins, or noisy alerts — specifically to avoid the friction and pushback those approaches typically create with development teams.