agent-bridge

Scan codebases to expose product actions as localhost API endpoints with a review/approval layer.

Updated Feb 5, 2026

Search Tags:#web application #AI-agent #codebase scanning #API layer #HTTP interface

Ready to run

npx skills add https://github.com/ilamanov/skills --skill agent-bridge-ilamanov

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: agent-bridge
Source: https://github.com/ilamanov/skills/tree/main/skills/agent-bridge
Command: npx skills add https://github.com/ilamanov/skills --skill agent-bridge-ilamanov

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill builds a secure local HTTP interface for any web application, allowing for the creation of an AI-agent API layer and enabling control by an AI agent.

Core Features & Use Cases

Safe HTTP Interface: Expose product actions as localhost API endpoints with a review/approval layer.
Codebase Scanning: Automatically discovers all product actions and exposes them.
Use Case: Ideal for users who want to expose product actions to an AI agent, create an agent API layer, or add an MCP-like interface to their app.

Quick Start

Run the 'Discover Actions' step to scan your codebase and identify actions to expose to the AI agent.

Frequently Asked Questions about agent-bridge

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I create a secure local HTTP interface for an AI agent to interact with my web application?▼

To create a secure local HTTP interface for an AI agent, you need a tool that scans your codebase and exposes product actions as localhost API endpoints. This approach adds a review and approval layer, ensuring safe AI-agent control over your web application.

How does codebase scanning discover actions to expose to an AI agent?▼

Codebase scanning for AI agents works by automatically discovering all product actions within your web application and exposing them as local API endpoints. You typically run a discovery step that identifies these actions and prepares them for the agent API layer.

Do I need Python to build an AI-agent API layer for my web application?▼

Yes, you need Python installed to build this AI-agent API layer. The process requires Python for execution to properly scan the codebase and establish the secure localhost HTTP interface for your web application.

What is the best way to add an MCP-like interface to a web application for AI control?▼

The best way to add an MCP-like interface to a web application is by building a secure local HTTP API layer. This involves scanning your codebase to expose product actions as localhost endpoints, complete with a review and approval layer for safe AI-agent interaction.

Can I review and approve AI agent actions before they execute through the local HTTP interface?▼

Yes, the local HTTP interface includes a review and approval layer for AI agent actions. When the agent interacts with your web application through the exposed localhost API endpoints, you can safely review and approve these product actions before they execute.