MCP Config CLI

Overview

MCP Config is a lightweight command‑line interface designed to streamline the management of MCP (Model Context Protocol) server configurations for AI clients such as Claude, Windsurf, and Cursor. The tool addresses a common pain point in AI‑powered development: keeping track of multiple server instances, ensuring they are correctly configured, and enabling rapid deployment without manual edits to JSON or environment files. By centralizing server metadata in a dedicated repository, MCP Config removes the need for developers to remember command syntax or file paths, reducing configuration drift and speeding up onboarding.

At its core, MCP Config provides an interactive menu that lists all known MCP servers from a bundled repository. With a single keystroke, users can install a server in one line, configure connection details through guided prompts, view the current settings, or purge obsolete entries. The one‑line install feature is particularly valuable for rapid experimentation; developers can spin up a new server with a single command () and immediately begin sending requests from their AI client. The interactive prompts abstract away the intricacies of host URLs, authentication tokens, and port numbers, allowing developers to focus on higher‑level model logic.

Key capabilities include:

• Repository management – A curated list of MCP servers is maintained in , making it easy to add new providers or update existing ones without touching the tool’s core code.
• Interactive configuration – The CLI walks users through necessary parameters, validates input, and persists the settings in a local configuration file.
• Cross‑platform support – The tool works on any environment that can run Node.js, ensuring consistency across Windows, macOS, and Linux setups.
• Extensibility – New MCP servers can be added to the repository, and the tool automatically exposes them through the same interface.

Typical use cases include:

• Rapid prototyping – A data scientist can spin up a temporary MCP server to test a new model variant, configure it instantly, and drop the configuration into version control.
• Multi‑model orchestration – A backend service that needs to route requests between Claude, Windsurf, and Cursor can rely on MCP Config to keep each server’s credentials in sync.
• CI/CD pipelines – Automated scripts can invoke to ensure a fresh server configuration is available before running integration tests.

MCP Config’s unique advantage lies in its simplicity and tight coupling with the MCP ecosystem. By handling server installation, configuration, and cleanup through a single, intuitive interface, it removes repetitive boilerplate from AI workflows. Developers who already work with MCP clients will find that this tool not only saves time but also enforces a consistent configuration pattern, leading to fewer runtime errors and smoother collaboration across teams.