IAM Policy Autopilot is an open source static code analysis tool that helps you quickly create baseline AWS IAM policies that you can refine as your application evolves. This tool is available as a command-line utility and MCP server for use within AI coding assistants for quickly building IAM policies.

Australian lender credit policy library and client files for mortgage and finance brokers.

Audit trail and traceability for AI agents. See what every coding agent did, block risky calls, ask a human for approval, and prove it with signed trust checks.

Approval gate and audit trail for AI agent actions: policy check first, proof after. Any MCP client.

Permission-aware retrieval for AI systems: policy-enforced access to organizational knowledge.

Your personal AI runtime, local-first. Patchwork OS gives any AI model a consistent set of tools, YAML recipes, a delegation policy with approval queue, and a durable trace memory — all on your machine, all under your policy.

Model Context Protocol server transport: serve typed procedures as MCP tools to Claude and other MCP clients, with streaming progress, list_changed and an expose policy.

SceneScout — exploratory UI testing for AI coding agents. An MCP server that gives any agent (Claude Code, Cursor, VS Code Copilot, Codex, Gemini CLI and others) a structured view of a running web app, always-on oracles, a network-level write policy, memo

Enables MCP clients to query a sensitive local workspace through a read-only status bridge that returns only pre-defined numeric file counts, status enums, and static policy—never source, paths, diffs, logs, environment variables, or command execution.

Exposes a single authenticated MCP endpoint that federates to agents running on your own machines, letting you delegate coding jobs to be worked in fresh git worktrees and pushed to a branch, or proxy the stdio MCP servers installed there as tools. Agents dial out through a Cloudflare Tunnel and enforce your local policy, so no inbound ports are opened.