Clojure MCP Server

The MCP Clojure SDK is a lightweight, idiomatic toolkit for building Model Context Protocol (MCP) servers in Clojure. It abstracts the low‑level networking and protocol plumbing, letting developers focus on defining rich, domain‑specific tools that AI assistants can invoke. By exposing a declarative API for resources, prompts, and sampling strategies, the SDK turns any Clojure application into a first‑class MCP participant with minimal ceremony.

At its core, the SDK solves the friction that often accompanies integrating external services into AI workflows. Traditional approaches require custom HTTP clients, manual JSON parsing, and boilerplate for authentication—all of which distract from the business logic that the AI assistant actually needs. With the MCP Clojure SDK, developers declare a set of tools (e.g., arithmetic operations, data visualization helpers, or code‑analysis utilities) and the SDK handles request routing, response formatting, and protocol compliance. This streamlines the creation of “smart” assistants that can call into native code, execute complex calculations, or generate visualizations on demand.

Key capabilities of the SDK include:

• Tool Definition – A concise DSL for registering functions as MCP tools, complete with input validation and type hints.
• Resource Management – Automatic handling of persistent state, such as caching or session data, that can be shared across tool invocations.
• Prompt Injection – Facilities to embed custom prompts or context into the MCP handshake, enabling more natural interactions with the AI.
• Sampling Configuration – Exposure of sampling parameters (temperature, top‑p) so that the server can influence the generative behavior of connected assistants.
• Template Ecosystem – Ready‑made and GitHub templates that bootstrap a new MCP server with best practices, reducing the learning curve.

Real‑world use cases span from simple calculator services to sophisticated data‑science pipelines. For example, the bundled vegalite_server can generate interactive Vega‑Lite charts from raw data, allowing an AI assistant to produce visual insights without leaving the conversation. The code_analysis_server demonstrates how static analysis tools can be wrapped as MCP endpoints, giving developers a single interface to lint, format, or refactor code snippets on demand. In each scenario, the SDK’s declarative style ensures that adding a new tool is as easy as writing a Clojure function and registering it.

Integration into AI workflows is seamless: an MCP‑enabled assistant automatically discovers available tools via the protocol’s introspection endpoints. Once a tool is registered, the assistant can invoke it with natural language prompts that are translated into structured JSON calls. The SDK’s support for custom sampling and prompt injection allows developers to fine‑tune how the assistant behaves, ensuring that responses remain consistent with business rules or domain constraints. This tight coupling between server logic and assistant behavior unlocks powerful, context‑aware interactions that would be cumbersome to implement with generic HTTP APIs.

What sets the MCP Clojure SDK apart is its commitment to idiomatic Clojure and minimal friction. By leveraging the language’s immutable data structures, multimethods, and rich ecosystem (e.g., , ), the SDK delivers a robust, production‑ready foundation while keeping the codebase approachable. Whether you’re building a lightweight calculator, a data‑visualization microservice, or an AI‑powered code review tool, the MCP Clojure SDK gives you a reliable, extensible platform that integrates naturally into modern AI assistant workflows.