DevEnvInfoServer - Cursor MCP Server for Development Environment Information

What is DevEnvInfoServer - Cursor MCP Server for Development Environment Information?

DevEnvInfoServer is a Model Context Protocol (MCP) server that provides detailed information about a user’s development environment to the Cursor code editor. It gathers system, hardware, software, and configuration data to help Cursor’s intelligent agent offer more context‑aware assistance.

How to use DevEnvInfoServer - Cursor MCP Server for Development Environment Information?

Clone the repository, create and activate a Python virtual environment, then install dependencies with pip install -r requirements.txt. In Cursor Settings > Features > MCP, add a new server with type stdio and command python claudemcp.py (or the full path to your Python interpreter and that script). Once added, Cursor’s agent will automatically use the server’s tools when relevant, or you can explicitly prompt it for environment details.

Key features of DevEnvInfoServer - Cursor MCP Server for Development Environment Information

• Operating system version, hardware, and Python details
• Installed compilers, interpreters, and package managers
• Running containers, virtual machines, and GPU/CUDA info
• Shell config files, aliases, and editor configurations
• Top environment variables, locale, timezone, and network config
• Simplified system performance (CPU load, battery, temperature)

Use cases of DevEnvInfoServer - Cursor MCP Server for Development Environment Information

• Cursor agent automatically retrieving installed Python packages to debug import issues
• Providing a list of available shells or active SSH connections during a coding session
• Checking Docker containers or Kubernetes configuration without leaving the editor
• Inspecting compiler versions and build tool installations for project setup
• Reviewing shell aliases and custom scripts when diagnosing command behavior

FAQ from DevEnvInfoServer - Cursor MCP Server for Development Environment Information

What information does this server collect?

It gathers system details (OS, hardware, Python versions), development tools (compilers, interpreters, package managers), running services (Docker, VMs, SSH), configuration files (shells, editors, git), and performance metrics (CPU, battery, GPU). No user files or private code are accessed beyond what is explicitly listed.

How is the server connected to Cursor?

It uses the Model Context Protocol with stdio transport, communicating through standard input and output streams. Cursor acts as the MCP client and discovers the server’s tools automatically after configuration.

What are the runtime dependencies?

Python 3 and the packages listed in requirements.txt (including psutil, pyserial, and platform‑native libraries). The server runs system commands via subprocess to collect information.

Can I generate a report of the environment?

Yes. The server can optionally produce a Markdown file (development_environment_info.md) containing all collected information for easier review and debugging.

Does the server require approval before executing tools?

By default, Cursor asks for your approval before any MCP tool call. You can review the arguments before approving. A “YOLO Mode” is available for automatic execution without prompts.