About
This MCP server enables users to open projects in their default editor and retrieve project metadata directly from Claude Desktop. It relies on the Filesystem MCP Server for file operations.
Capabilities
Project Opener MCP Server
Project Opener is a lightweight MCP (Model Context Protocol) server designed to give Claude Desktop users instant, programmatic access to the file system of their local development projects. By leveraging the existing Filesystem MCP Server, it exposes a small set of high‑level tools that let an AI assistant open projects in the user’s preferred editor or query metadata about a project without having to manually navigate directories. This removes friction for developers who want to let Claude handle routine navigation tasks, while keeping the interface simple and secure.
The server’s core value lies in its ability to translate a natural‑language request into an action on the local machine. For example, when Claude receives a prompt like “Open my React app in VS Code,” the server can resolve the relative path, launch the editor with the correct folder, and confirm success. Similarly, a query such as “What files are in my Django project?” can be answered by retrieving the directory listing. Because the server runs locally, it respects the user’s environment and permissions, ensuring that only authorized files are accessed.
Key capabilities of Project Opener include:
- Open Project – Launches the default editor (or a configured one) with the specified project path, streamlining the transition from conversation to code.
- Get Project Info – Returns metadata such as file count, size, or recent commit information for a given project path, enabling Claude to provide context‑aware suggestions.
- Filesystem Integration – Built on top of the standard Filesystem MCP Server, it inherits robust file‑access primitives while offering a higher‑level abstraction tailored to project workflows.
Typical use cases are plentiful: developers can ask Claude to open a new feature branch, inspect the structure of a microservice, or quickly jump into a legacy codebase. In continuous‑integration pipelines, an AI assistant can trigger test runs or linting by first opening the relevant project directory. Because Project Opener operates through MCP, it can be combined with other servers—such as a Git or Docker server—to create end‑to‑end AI‑driven development workflows that keep the assistant in sync with the local environment.
What sets Project Opener apart is its minimal surface area coupled with powerful automation. By focusing on the most common project‑level actions, it reduces the cognitive load on developers and allows Claude to act as a true pair programmer that can open files, inspect structure, and even prepare the environment for deeper code analysis or generation tasks.
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