HaltState
Control AI agent actions. Investigate the evidence.
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HaltState MCP - Investigate AI agent activity from your MCP client

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Ask what your AI agents did, find a customer interaction, follow its timeline and verify linked Proof Packs from your MCP client. Ten investigation tools bring activity search, evidence verification and exports into your existing workflow. Connect agents with Python, TypeScript/JavaScript, Go, Java or Rust; enforce policies before connected actions execute. Self-service signup and AI-assisted policy setup help you start with one action.

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AI agents are gaining power. Their authority needs limits.

An agent trying to finish a task can delete data, exceed its permissions or make a change that should have required approval. Those decisions need enforceable boundaries.

We built HaltState around a clear conviction: deterministic control will become essential infrastructure for agentic AI.

Our patent-pending platform checks connected agent actions against your policies before execution. Allow the action, block it or require human approval—and preserve signed evidence of the decision and reported outcome.

Our patent work traces back to August 2025, with U.S. and international PCT applications covering secure agent orchestration and verifiable execution.

Now, HaltState MCP brings that evidence into your investigation workflow. Search agent activity, follow the timeline, verify Proof Packs and export records directly from your MCP client.

Connect your HaltState account from a compatible MCP client such as Claude Code, then ask:

• Show the last five activities for this agent, counting each business operation once.

• Find this customer interaction and follow its timeline.

• Verify the linked Proof Pack and show the recorded outcome.

Ten tools cover activity and evidence search, linked timelines, integrity verification and evidence exports. Compatible clients renew access automatically.

Connect agents with Python, TypeScript/JavaScript, Go, Java or Rust. Self-service signup and guided setup help you get started; the AI Policy Assistant drafts controls for human review before activation. Policy changes, human approvals and containment stay in the dashboard.

Give your agents useful autonomy. Keep authority over what they can do.

Start with one action:

MCP connection guide:

Create an account:

Very bold idea! Authorisation is something extremely lacking nowadays and will be a topic of discussion between businesses that go AI native, congratulations on your launch!

Maker

 With OpenAI agents going rogue all over the place and corporations with chatbots giving insane advice and making errors, Agent control is essential. Thank you for stopping by and commenting.