Preloop
Apache-2.0 AI agent control plane — MCP firewall, model gateway, policy-as-code and human approvals
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preloop.aiAbout Preloop
Preloop is an Apache-2.0 licensed control plane for AI agents, aimed at the governance problem that appears the moment more than one agent is running in an organisation: nobody can see what tools they can reach, what they are spending, or who approved anything. It bundles six capabilities into one self-hostable platform — an MCP firewall that defines allow, deny and require-approval rules on tool access; an AI model gateway that attributes cost and enforces per-agent budgets; policy-as-code written in YAML with CEL expressions; human-in-the-loop approvals delivered to mobile, watch, Slack, Mattermost or a webhook; runtime session observability; and an audit trail. Onboarding is deliberately frictionless: `preloop agents discover` finds compatible agent configurations already on the machine and transparently rewrites them so tool calls route through the MCP firewall and model traffic through the gateway, with no SDK changes and no agent code changes. The named runtimes it rewrites include Claude Code, Codex CLI, Cursor, Gemini CLI, Hermes, OpenClaw, OpenCode and Windsurf. The vendor positions Preloop explicitly as an open-source alternative to AWS Bedrock AgentCore and as a way to build EU AI Act readiness evidence, with dedicated guidance published for that use case. Because the full control plane is Apache 2.0 and self-hostable, the paid tiers sell hosting, team governance and conditional-approval sophistication rather than the core capability.
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Key Features
Preloop Pros & Cons
✅ Pros
- +The entire control plane is Apache 2.0, so nothing essential is paywalled
- +Discovery rewrites existing agents with no SDK or code changes
- +Approvals reach a watch or Slack, which is where an on-call human actually is
⚠️ Cons
- −SSO, SAML and SCIM are listed as planned rather than shipped
- −Per-user pricing on the hosted tier gets expensive for large engineering orgs
- −Self-hosting the full stack is real operational work
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