A complete record of AI use
Prompts, files, tool calls, agent actions, and network activity gathered into one record your team can review.
Learn moreAI Agent Security
The control layer
for AI agents.
Observe agent activity, catch risky actions, and stay in control of what your AI can access and execute.
Activity, made readableExample flow
Shell command
npm run build categorized by Beam as Routine activity.File access
read .env categorized by Beam as Sensitive access.Shell command
rm -rf ./src categorized by Beam as Destructive action.Routine activity
RecordedSensitive access
Flagged for reviewDestructive action
Risk identifiedWorks with the tools you already use.
Claude CodeCodexChatGPTCursorGitHub CopilotAntigravityMuseMore coming
Visibility without blind spots
What Agentbeam does
Four things, done carefully, for teams that have given AI real access to real systems.
Unsafe activity, caught early
Sensitive data leaving, credential access, destructive commands, and permission changes surfaced with the evidence behind them.
Learn more
Local-first control
Keep observability close to the work. Agentbeam is designed to give teams visibility without sending every interaction away.
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Evidence ready for review
Turn a stream of agent activity into clear, durable evidence for security reviews, incident response, and compliance work.
Learn moreHow it works
From agent action to audit-ready evidence
Four steps, running the whole time an agent is working — not a scan you remember to run.
- 01
Point it at your agents
Agentbeam attaches to the coding agents already running on a machine — terminal-based and IDE assistants alike — with no change to how your team prompts them.
- 02
Every action gets recorded
Shell commands, file edits, tool calls, and network activity are captured into one local record as the agent works, not reconstructed after the fact.
- 03
Risky activity gets flagged
Sensitive-data access, credential exposure, destructive commands, and permission changes are surfaced with the evidence behind them, so review starts from a fact, not a guess.
- 04
MCP configs get scanned first
Before an agent connects to a new MCP server, its config is checked against heuristic patterns for tool poisoning, rug pulls, and credential exfiltration.
Why Beam
Built for one job, done honestly
Agent security, not cloud security
Scoped to what your AI agents do — commands, files, tool calls, MCP and skill configs — not your broader infrastructure.
Local-first, evidence-first
The collector binds to loopback only. No telemetry leaves the machine by default.
Open-source core
Beam CLI is public and self-hostable. Read the code that watches your agents, or run it yourself.
Resources
What’s happening
- From the blogAI agent security platforms: how to evaluate oneVendors selling "AI agent security" aren't all selling the same thing. Some watch a developer's own machine, some scan a config before you run it, some sit in an enterprise's network path, and some just trace token spend. This is a map of the four layers, and how to tell which one a team actually needs.Read more →
- Live classAI Safety for Agentic TeamsA live session on securing the AI agents your team already runs.Read more →
- EventsUpcoming sessionsWhat's currently open to register for, or ask for a private one.Read more →
FAQ
Questions, answered directly
What is Agentbeam?
Agentbeam is a local-first security and observability layer for AI coding agents. It records agent shell commands, file edits, tool calls and network activity, flags risky actions with the evidence behind them, and scans MCP configs and SKILL.md files for hidden instructions before an agent trusts them.
Does Agentbeam send my data anywhere?
No, by default. Agentbeam is local-first: activity is recorded to local files on the machine it runs on, and nothing is sent off-device unless you explicitly configure an export.
Which AI agents and tools does Agentbeam work with?
Agentbeam watches coding-assistant activity at the runtime level — shell commands, file changes, tool calls, and MCP server connections — so it works across the terminal-based and IDE agents your team already runs, without requiring each one to integrate separately.
Does Agentbeam block risky agent actions?
Agentbeam observes and flags — it does not block, yet. It surfaces sensitive-data access, credential exposure, destructive commands, and permission changes with the evidence attached, so your team can review and act on them.
What is MCP security scanning?
Before an agent connects to an MCP server, Agentbeam scans its config against heuristic patterns for tool poisoning, unpinned versions that enable rug pulls, and credential-exfiltration phrasing — heuristic triage, not a guarantee of safety.
Who is Agentbeam built for?
Security teams that need detection and evidence across every agent in use, and IT teams rolling out AI coding tools across developer machines who need fleet-wide visibility without slowing anyone down.
How do I get started with Agentbeam?
Talk to us using the form on this page and we'll walk you through setup for your team's stack. We'll follow up by email to schedule a short walkthrough.
Talk to us
Get a walkthrough of Agentbeam
Tell us about your team and stack. We'll follow up by email to schedule a short walkthrough — no sales deck, just what Agentbeam actually shows you.