Enterprise DNA
M MCP Servers Developer low

sekera-radim/impri

by Various

Human-in-the-loop approval inbox for AI agents. An agent proposes an action, a human approves or rejects it, then it runs. Watchers + approval inbox, MCP + REST, self-hostable (MIT

S

MCP

sekera-radim/impri

Added 13 July 2026

#ai-agents #ai-safety #approval-workflow #human-in-the-loop #llm #mcp #model-context-protocol #self-hosted

Overview

Impri is a self-hostable tool that adds a human-in-the-loop approval step to AI agent workflows. Agents submit proposed actions to an inbox, where a human can approve or reject them before execution. It supports MCP and REST interfaces and includes watcher functionality for monitoring proposals.

Best for

Best for
Teams needing a lightweight, self-hosted approval layer for AI agents

Use cases

  • Adding human oversight to autonomous agent workflows
  • Approving or rejecting agent-generated actions before execution
  • Monitoring agent proposals with watchers

Notes

Impri is a self-hostable tool that adds a human-in-the-loop approval step to AI agent workflows. Agents submit proposed actions to an inbox, where a human can approve or reject them before execution. It supports MCP and REST interfaces and includes watcher functionality for monitoring proposals.

0 stars on GitHub. Last updated 2026-07-13. Licensed MIT.

Use cases

  • Adding human oversight to autonomous agent workflows
  • Approving or rejecting agent-generated actions before execution
  • Monitoring agent proposals with watchers

Pros

  • Self-hostable with MIT license for full control
  • Provides clear human-in-the-loop governance for agent actions
  • Supports both MCP and REST interfaces for integration

Cons

  • No stars yet, indicating a new or unproven project
  • Requires manual approval step, slowing fully autonomous processes
  • Limited community support and documentation due to early stage

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Self-hostable with MIT license for full control
  • Provides clear human-in-the-loop governance for agent actions
  • Supports both MCP and REST interfaces for integration

Cons

  • No stars yet, indicating a new or unproven project
  • Requires manual approval step, slowing fully autonomous processes
  • Limited community support and documentation due to early stage
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