Plasma MCP Server

Plasma is a Ruby‑based Model Context Protocol (MCP) server framework that aims to make building AI assistants feel as natural as writing a Rails application. By adopting a convention‑over‑configuration philosophy, it lets developers scaffold tools, prompts, resources and persistent storage with a single command. The result is a lightweight yet fully‑featured MCP service that can be spun up locally or deployed in containers, enabling rapid experimentation and iteration.

The core problem Plasma solves is the friction of wiring an AI assistant to external logic. Traditional MCP servers require boilerplate for routing, parameter validation and state management, which can distract from the actual business logic. Plasma removes that overhead by providing a Rails‑like directory layout (, , ) and a code generator that creates fully‑formed tool classes. These tools expose typed parameters, automatic documentation extraction from comments, and a simple helper to return structured results. The framework also bundles a storage layer for variables and records, so developers can persist session data or domain objects without pulling in an external database.

Key capabilities include:

• Convention‑driven scaffolding – generate tools, prompts, and resources with a single CLI command.
• Typed parameter handling – define parameters declaratively (, , ) and have them automatically validated.
• Built‑in persistence – variables for per‑session state and records for long‑term storage, all accessible from within tools.
• Local authentication (in progress) – an Omniauth‑based system that will allow secure user context handling.
• Container friendly – optional Docker support for easy deployment in CI/CD pipelines or cloud environments.

In practice, Plasma shines when building domain‑specific assistants. A project management bot could expose a tool that writes to a records table, while an HR assistant might use variables to track the current employee context. Because tools are first‑class citizens, developers can compose complex workflows by chaining tool calls or embedding prompts that invoke other tools. The server’s STDIN/STDOUT mode also makes it trivial to test interactions via JSON‑RPC, which is ideal for automated integration tests or sandbox environments.

What sets Plasma apart is its blend of familiar Rails ergonomics with the flexibility of MCP. Developers who already understand Ruby on Rails find the learning curve gentle, yet the platform remains agnostic enough to fit into diverse AI pipelines—from a lightweight local prototype to a production‑grade microservice behind an API gateway. As the project matures, the addition of authentication and a richer ecosystem of generators will further streamline the creation of secure, scalable AI assistants.