MCP Installer

MCP Installer is a lightweight, command‑line tool that streamlines the discovery, configuration, and deployment of Model Context Protocol (MCP) servers for AI assistants such as Claude or Cursor. In many development environments, connecting an assistant to external services requires manual edits to configuration files and tedious server setup. MCP Installer automates these steps, allowing developers to focus on building intelligent workflows rather than managing infrastructure.

The tool bundles three core utilities: find‑mcp, which queries the Smithery registry to locate available MCP servers; collect-config, which gathers the connection parameters needed by an AI client; and install‑mcp, which installs the chosen server onto a local machine. By orchestrating these tasks, MCP Installer eliminates the common pain points of manual path discovery, API key handling, and cross‑platform configuration differences. Developers no longer need to remember where a file should live on Windows, macOS, or Linux; the installer writes the correct file in the appropriate location for either Cursor or Claude automatically.

Key capabilities include automatic detection of client type, secure handling of the Smithery API key, and seamless integration with existing AI tools. Once installed, an MCP server can expose resources such as data repositories, computational services, or custom prompts to the assistant. This opens up a range of use cases: a data‑science team can expose a local Jupyter notebook server to Claude for on‑the‑fly analysis, or a web‑development squad can expose a local API gateway so Cursor can invoke backend services during conversation. The server’s standard‑output interface means it can be embedded in CI pipelines or invoked from other automation scripts without additional dependencies.

What sets MCP Installer apart is its end‑to‑end workflow: discover, configure, and run an MCP server with a single command. It abstracts away platform quirks, centralizes API key management through the Smithery ecosystem, and produces a ready‑to‑use configuration file that any MCP‑aware client can consume. For developers building AI‑augmented applications, this means faster prototyping, fewer configuration errors, and a smoother path from idea to deployment.