Axtary
Authorization for AI agents that binds human approval to exact payloads before execution.
Axtary
What is Axtary?
Axtary vs Similar AI Tools
| Pricing Model | Free, Custom Pricing | Free | Free | Free |
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How to use Axtary?
- 1Install the Axtary CLI and configure policies for your connectors.
- 2Integrate runtime packages (SDK, local proxy) where agents run.
- 3Define policies and approve actions via the hosted control plane.
- 4ActionPass artifacts bind approval to exact payloads.
- 5Monitor verifiable action ledger for audit trails.
Axtary Key Features
- Payload binding: verification fails if payload changes after approval
- ActionPass artifact: signed authorization for specific actions
- Connector readiness checks with non-destructive evidence
- Enforcement runs beside the agent via local SDK and proxy
- Verifiable action ledger for every attempt
- Support for MCP servers and native connectors (GitHub, Slack, Linear, etc.)
Axtary Use Cases
- Securing AI agent actions against compromise or mistakes
- Enforcing least privilege for agent tool access
- Preventing supply chain attacks on AI workflows
- Providing auditable trail of all agent actions
Axtary Pricing & Free Credits
Axtary currently operates on a Free, Custom Pricing model.
Self-Hosted
Free
Open source under Apache-2.0 license; local enforcement and credentials remain local.
Hosted Plan
Contact for Pricing
Managed hosted control plane for team coordination, approval, and audit exports.
Axtary Pros & Cons
Pros
- Fine-grained, payload-bound authorization prevents tampering
- Local enforcement keeps credentials secure
- Open source with verifiable ledger
- Supports multiple connectors and runtimes
Cons
- Requires integration effort to set up policies and packages
- Hosted plan pricing not publicly available
- Dependent on runtime packages for each platform
What is Axtary best for?
- AI developers deploying production agents
- Teams needing tight security for agent tool calls
- Organizations requiring audit trails for AI actions
Axtary FAQ
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