Babashka MCP Server

Babashka MCP Server – Overview

The Babashka MCP Server bridges the gap between AI assistants and the powerful, lightweight Clojure interpreter known as Babashka. By exposing Babashka’s execution engine through the Model Context Protocol, developers can let an AI tool run arbitrary Clojure scripts on demand, retrieve past results, and manage execution timeouts—all without leaving the conversational flow. This solves a common pain point: how to execute ad‑hoc scripting logic from within an AI workflow while keeping the execution environment isolated, reproducible, and easily controllable.

At its core, the server offers a single, well‑defined tool called execute. When invoked, it receives raw Babashka code and an optional timeout value, runs the script in a sandboxed process, and returns the result or an error. The server also caches recent command outputs and exposes them as resources (), allowing the AI to reference previous results or replay specific executions. This history feature is invaluable for iterative debugging, audit trails, or when the AI needs to build on earlier computations. The ability to set per‑command timeouts protects both the server and the host system from runaway scripts, ensuring predictable latency in AI interactions.

Key capabilities include:

• Script execution: Run any valid Babashka snippet, from simple arithmetic to complex data transformations.
• Result caching: Quickly access recent outputs without re‑executing code, improving response times for repeated queries.
• Command history resources: Expose past executions as retrievable URLs, enabling the AI to reference or share specific results.
• Timeout configuration: Safeguard against long‑running or infinite loops by limiting execution time on a per‑call basis.

Typical use cases span from automating infrastructure tasks—such as generating configuration files or parsing logs—to data analysis pipelines where an AI assistant can execute Clojure scripts that manipulate JSON, CSV, or other structured data. In continuous‑integration scenarios, the server can run Babashka pods to perform security checks or code formatting on the fly. Because it follows the MCP specification, any AI platform that understands MCP can seamlessly integrate this server into its toolchain, treating Babashka execution as just another native capability.

Unique advantages of the Babashka MCP Server include its minimal footprint (Babashka is a single binary), native Clojure syntax support, and the promise of a future self‑hosted implementation that eliminates Node.js dependencies. This forward‑looking roadmap ensures the server remains lightweight, secure, and tightly coupled to the evolving Babashka ecosystem. For developers looking to enrich AI workflows with fast, reliable Clojure scripting, the Babashka MCP Server offers a straightforward, protocol‑compliant gateway that turns conversational prompts into executable code.