Bash MCP Server

The mcp-server-bash project offers a lightweight, shell‑based implementation of the Model Context Protocol (MCP). It bridges AI assistants such as Claude with external tooling by exposing a minimal set of MCP endpoints—handshake, tool discovery, and tool invocation—through simple JSON‑RPC messages. The server’s primary goal is to demonstrate how a single Bash script can fulfill the MCP contract, allowing developers to prototype or integrate AI‑driven workflows without relying on heavyweight runtimes or complex dependencies.

At its core, the server follows a two‑phase lifecycle: initialization and operation. During initialization, the script responds to the call, advertising its capabilities and registering a single “addition” tool. In the operation phase, it accepts requests to enumerate available tools and processes messages that trigger the addition logic. The mathematical example is intentionally simple—adding two numbers—but the architecture can be extended to any shell command or script, making it a versatile foundation for rapid experimentation.

Key features include:

• Zero‑dependency execution: Runs natively on any POSIX shell, requiring only Bash and standard utilities.
• JSON‑RPC compliance: Adheres to the official JSON‑RPC specification, ensuring interoperability with MCP‑aware clients.
• Extensibility: New tools can be added by extending the script’s command dispatch logic, allowing developers to expose complex pipelines or system commands.
• CLI‑friendly testing: The README shows how to invoke the server directly from the command line, facilitating quick validation without a full AI host setup.

Real‑world use cases are abundant for developers building AI‑augmented tooling. For instance, a data scientist could expose a Bash wrapper around or scripts as MCP tools, enabling Claude to query datasets on demand. Similarly, system administrators might expose diagnostic commands (e.g., , ) so that an AI assistant can provide real‑time system health reports. The minimal footprint makes it ideal for embedded environments or CI pipelines where installing a full Python server would be overkill.

Integration into AI workflows is straightforward. Once the MCP server is registered in an LLM host configuration (as shown with and a JSON config file), the assistant automatically discovers the “addition” tool during the handshake. Subsequent prompts that require arithmetic can invoke , and the assistant receives the result in the same JSON‑RPC response stream. This tight coupling eliminates manual API calls, allowing developers to focus on crafting natural language prompts that leverage the underlying shell logic.

In summary, mcp-server-bash demonstrates that a fully functional MCP server can be achieved with just a shell script. It solves the problem of integrating external tooling into AI assistants in an environment‑agnostic, lightweight manner while preserving full protocol compliance and extensibility for future growth.