AIDevTools MCP Server

AIDevTools – MCP Server for AI‑Powered Development

AIDevTools is a collection of MCP servers that give language‑model assistants, such as Claude, direct control over local development environments. The core idea is to bridge the gap between an AI’s high‑level instructions and the low‑level operations that a developer actually needs to perform, from spawning processes to managing inter‑process communication and even handling specialist queries. By exposing a rich set of tools over the MCP interface, AIDevTools turns an AI assistant into a full‑blown development companion that can run commands, monitor outputs, and answer domain‑specific questions without leaving the conversational UI.

The server’s flagship component, Sidekick, handles process lifecycle management and real‑time output streaming. It lets an assistant spawn long‑running binaries, tail their logs with ring buffers, and interact through stdin/stdout/stderr streams. Developers can even receive audio notifications on macOS when a process finishes or encounters an error. Sidekick also provides a text‑based UI for visual monitoring, making it useful both in headless CI pipelines and local developer workstations. In addition to process control, Sidekick offers an “agent Q&A” system: developers can register as specialists and receive questions from the assistant, or conversely ask specialist agents for targeted advice. This bidirectional communication layer turns the MCP server into a lightweight knowledge base that adapts to the team’s expertise.

Complementing Sidekick is stdio2sse, a transparent proxy that allows stdio‑based MCP clients (like Claude Desktop) to talk to SSE‑only servers. This adapter simplifies integration with services that expose their APIs over Server‑Sent Events, ensuring that developers can leverage a broader ecosystem of tools without changing their workflow. The proxy automatically discovers available tools and forwards requests/responses asynchronously, maintaining low latency even under heavy load.

In practice, AIDevTools shines in scenarios where an AI assistant needs to execute code, monitor build processes, or query specialized knowledge. A developer can ask the assistant to run a test suite, stream the results live in the chat, and receive an audio cue when failures occur. AQA teams can set up specialist agents that answer questions about architecture or security policies, while the assistant orchestrates the underlying tooling. The ability to expose custom tools via MCP also means that any existing CLI utility can be wrapped and made available to the AI, turning legacy scripts into conversational commands.

Overall, AIDevTools delivers a unified interface for managing processes, communicating with specialists, and bridging disparate communication protocols—all of which empower developers to harness AI assistants as active participants in their codebases rather than passive suggestion engines. Its cross‑platform support, real‑time streaming, and modular design give it a clear edge for teams looking to embed AI directly into their development pipelines.