AIBD Dev Container MCP Server

Overview

The AIBD Dev Container delivers a turnkey, container‑based environment that lets developers harness Claude’s Model Context Protocol (MCP) to work directly on their code from within Visual Studio Code. By packaging a pre‑configured Node.js/TypeScript runtime, Docker volume persistence, and an MCP server into a single dev container, the project eliminates the friction of setting up isolated environments for each new project. Developers can simply clone this repository, launch VS Code’s “Reopen in Container” workflow, and immediately have a fully‑functional workspace that Claude can query for file contents, execute shell commands, or invoke custom tools—all through the MCP interface.

At its core, the server provides file system and shell access to Claude. Once the container is running, a lightweight MCP server listens on port 3100 (and an optional REST endpoint on 3101) and exposes a set of tools such as that allow the assistant to run arbitrary commands inside the container. This enables Claude to, for example, compile TypeScript code, run tests, or manipulate project files without leaving the chat. Because the container mounts a Docker volume at , any changes made by Claude are persisted across restarts, giving developers confidence that the assistant’s actions are durable.

Key capabilities include:

• Consistent development environments: Every clone of the repository starts from the same base image, ensuring that dependency versions and tooling are identical across teams.
• Persistent storage via Docker volumes: Project files live outside the container’s writable layer, so code survives container rebuilds and can be shared across multiple instances.
• Seamless Claude integration: The MCP server is launched automatically with , and its address is configured in Claude Desktop’s settings, requiring no manual network configuration.
• Shell execution: The flag unlocks the ability for Claude to run arbitrary shell commands, making it possible to trigger build scripts, linting, or deployment pipelines directly from the assistant.

Typical use cases include AI‑assisted debugging, where Claude can inspect source files, run unit tests, and suggest fixes; rapid prototyping, with the assistant generating boilerplate code or updating configuration files on demand; and continuous integration workflows, where Claude can trigger test suites and report results back to the chat. By exposing a stable, isolated runtime that Claude can interact with through MCP, the AIBD Dev Container removes the usual barriers between conversational AI and the developer’s codebase, allowing teams to iterate faster and with fewer context switches.