Preloop

Preloop

23/01/2026
Automation & Workflow
Preloop: The Safety Layer for AI Agents | Control What AI Can Do
Preloop is an event-driven automation platform with built-in human-in-the-loop safety. AI agents respond to events across your tools automatically. When agents call sensitive operations, Preloop intercepts the request and routes it for human approval—no infrastructure changes required.
preloop.ai

Table of Contents

Preloop

Preloop is an “MCP Governance Layer”—a middleware platform that acts as a safety proxy for AI agents. It intercepts tool calls made by agents (like Claude Code or Cursor) and enforces human approval policies before allowing risky actions to proceed.

What It Is

Preloop functions as a proxy server for the Model Context Protocol (MCP). Instead of connecting your AI agent directly to sensitive tools (like database or deployment APIs), you route them through Preloop. The platform monitors tool calls in real-time; when an agent attempts a restricted action (e.g., “delete_database” or “refund_user”), Preloop pauses execution and triggers an approval request to a human via Slack, Mattermost, or mobile. Once approved, the action completes; if denied, the agent receives an error.

Key Features

  • MCP Proxy Architecture: Sits between your MCP client (Cursor, Windsurf, Claude Desktop) and MCP servers, requiring no changes to agent code.
  • Multi-Channel Approvals: Routes approval requests to where you work—supports Slack, Mattermost, Email, and a native Mobile App.
  • Granular Policy Engine: Define specific rules based on tool names and arguments (e.g., “allow payments < $50, require approval for > $50”).
  • Audit Trails: Maintains a complete log of every tool call, approval decision, and reviewer identity for compliance.
  • Event-Driven Workflows: Can trigger automation flows from webhooks (GitHub, Jira) while maintaining human-in-the-loop safety.

Use Cases

  • Production Safeguards: Let AI agents write code but require human approval before running deployment commands.
  • Financial Operations: Allow agents to draft invoices or refunds but mandate manager sign-off for transactions over a certain amount.
  • Data Integrity: Prevent accidental deletion or modification of production databases by blocking write operations without explicit permission.
  • Remote Management: Approve agent actions from your phone while away from your desk.

Pros and Cons

  • Pros: Agnostic to the agent framework (works with any MCP client); easy “drop-in” integration via proxy URL; adds safety to “black box” agents without rewriting code; mobile app is convenient for on-the-go approvals.
  • Cons: Adds a network hop (latency) to every tool call; requires sending tool data through a third-party proxy (privacy consideration); currently lacks Microsoft Teams support (supports Slack/Mattermost).

Pricing

  • Free Tier: Available for individuals and small setups.
  • Enterprise: Custom pricing for advanced governance features, SSO, and longer log retention.

How Does It Compare?

  • HumanLayer: The most direct competitor. HumanLayer acts as a Python SDK/middleware for adding approval steps to functions. Comparison: HumanLayer is often integrated at the code level (SDK), whereas Preloop operates as an MCP proxy, making Preloop easier to use with closed-source agents like Cursor or Claude Desktop where you can’t edit the agent’s internal code.
  • LangGraph (LangChain): A framework for building stateful agents with “breakpoints” for human input. Comparison: LangGraph requires you to build the agent from scratch effectively. Preloop sits outside the agent, meaning it works with pre-built agents you don’t control.
  • Weights & Biases: primarily an MLOps and observability platform. Comparison: W&B focuses on tracking experiments and evaluating model performance, not on real-time runtime blocking of specific tool calls for human approval.

Final Thoughts

Preloop solves a specific but critical problem in the “Agentic AI” era: trust. As developers increasingly use “black box” tools like Cursor and Claude Code that run on their local machines, the fear of an agent accidentally wiping a directory or pushing bad code is real. By using the standard Model Context Protocol (MCP) as an interception point, Preloop offers a clever, zero-code solution to this safety problem. It is essentially a firewall for your AI agents.

Its value proposition is strongest for teams using off-the-shelf AI coding tools who need enterprise-grade governance without building their own internal safety platforms. The lack of Microsoft Teams support at launch (Jan 2026) is a minor gap for corporate users, but the Slack and Mobile integrations cover the majority of the startup/dev ecosystem.

Preloop: The Safety Layer for AI Agents | Control What AI Can Do
Preloop is an event-driven automation platform with built-in human-in-the-loop safety. AI agents respond to events across your tools automatically. When agents call sensitive operations, Preloop intercepts the request and routes it for human approval—no infrastructure changes required.
preloop.ai