JetBrains MCP Proxy Server

Overview

The JetBrains MCP Proxy Server bridges the gap between AI assistants and IntelliJ‑based IDEs by acting as a lightweight intermediary that forwards Model Context Protocol (MCP) requests from the client to the IDE’s internal web server. By doing so, it eliminates the need for a separate network service or complex configuration when an AI assistant must read code, invoke refactorings, or access project metadata. Developers who rely on Claude or other AI tools can now tap into the full power of JetBrains’ language analysis, navigation, and tooling without leaving their AI workflow.

At its core, the proxy listens on a local port and forwards all MCP traffic to the IDE’s built‑in web server, which is already running on a specified host and port. The proxy handles authentication, session persistence, and logging transparently, allowing the AI client to treat the IDE as a native MCP endpoint. This design keeps the architecture simple: the IDE remains unchanged, while the proxy adds a thin, language‑agnostic layer that can be dropped in or removed as needed.

Key capabilities include:

• Transparent request forwarding: Every MCP call—whether it’s fetching the project model, invoking a tool, or streaming code completions—is routed unchanged to the IDE.
• Environment customization: Users can specify , , and logging flags in the proxy’s configuration, giving fine‑grained control over which IDE instance is targeted and how verbose diagnostics should be.
• Node.js compatibility: The proxy runs on Node 18+ and can be launched via npm, npx, or a custom command, making it easy to integrate into existing development environments such as VS Code or Claude Desktop.
• Cross‑platform support: The proxy works on Windows, macOS, and Linux, with special handling for Node installations managed by nvm or other version managers.

Real‑world scenarios that benefit from this server include:

• AI‑powered code review: An assistant can request the current file’s syntax tree, highlight problematic patterns, or suggest refactorings by simply sending MCP messages through the proxy.
• Contextual autocompletion: While writing code, the AI can query the IDE’s language server for type information or documentation and return rich suggestions to the user.
• Automated debugging: By accessing breakpoints, stack traces, and variable states via MCP, an AI helper can guide developers through complex debugging sessions.
• Learning and onboarding: New team members can leverage an AI tutor that pulls real project data from the IDE, providing explanations and walkthroughs tailored to the actual codebase.

Because the proxy is a thin wrapper around JetBrains’ already‑built MCP endpoint, it introduces minimal latency and no additional security concerns. Developers can quickly spin up or tear down the proxy as part of their local workflow, and the built‑in logging facilities help diagnose any connectivity issues. In short, the JetBrains MCP Proxy Server turns IntelliJ‑based IDEs into ready‑to‑use AI assistants’ data sources, enabling richer, more integrated developer experiences without modifying the IDE itself.