Kuri – A Rust‑First MCP Server Framework

Kuri is a lightweight, ergonomically designed framework for building Model Context Protocol (MCP) servers in Rust. It tackles the common pain point of integrating large language models with external systems by providing a seamless way to expose tools—predefined functions that the model can invoke for data retrieval or side‑effects. By keeping the developer experience close to idiomatic Rust, Kuri allows teams to rapidly prototype and deploy MCP services without wrestling with protocol plumbing or heavy macro syntax.

What Problem Does Kuri Solve?

When an LLM needs to interact with the world—fetching live data, performing calculations, or triggering workflows—it must rely on a well‑structured interface. MCP defines that interface as a set of tools, each with clear input schemas and output contracts. However, implementing an MCP server typically involves verbose serialization logic, manual routing, and boilerplate for middleware. Kuri abstracts these concerns so developers can focus on business logic: tools are ordinary async Rust functions annotated with simple attributes, and prompts are defined with the same minimal syntax. This reduces cognitive load and speeds up iteration cycles.

Core Features & Value

• Zero‑boilerplate routing – Kuri automatically exposes annotated functions over the MCP protocol, handling JSON schema generation and request dispatching behind the scenes.
• Minimal macro surface – Only and are required, each carrying descriptive metadata that the model uses to choose tools and supply arguments. No code generation or intrusive syntax is needed.
• Tower integration – Built atop the Tower ecosystem, Kuri inherits a rich set of middleware layers (timeouts, tracing, panic recovery) and can be composed with popular web frameworks such as Axum or Tonic.
• Rich type safety – Leveraging Rust’s strong type system, developers can define complex parameter types (enums, structs) and rely on compile‑time guarantees that tool signatures match the MCP contract.
• Extensibility – The framework is intentionally narrow in scope, making it easy to understand and extend. Custom transports or serialization strategies can be plugged in without touching the core logic.

Real‑World Use Cases

• Automated data pipelines – A model can request fresh metrics from a database or trigger ETL jobs via tools exposed by Kuri.
• Interactive assistants – Building chatbots that can perform arithmetic, fetch weather data, or schedule meetings by invoking local tools.
• CI/CD orchestration – Tools that trigger builds, run tests, or deploy artifacts can be called directly from the model’s reasoning loop.
• Enterprise knowledge bases – Exposing internal APIs as MCP tools allows the model to pull up-to-date policy documents or inventory information on demand.

Integration with AI Workflows

Kuri’s output is fully compliant with MCP, meaning any client that understands the protocol—Claude, OpenAI’s function calling interface, or custom LLM wrappers—can consume it. Developers can spin up a local server, register multiple tools, and let the model orchestrate them in real time. Because Kuri’s middleware stack is Tower‑based, it plays nicely with existing observability pipelines, enabling fine‑grained monitoring of tool usage and latency.

Unique Advantages

Kuri’s combination of developer ergonomics and deep integration with the Tower ecosystem sets it apart from other MCP server crates. It removes the typical friction of macro‑heavy frameworks while still offering production‑ready features like timeout handling and structured logging. For Rust teams looking to embed LLM capabilities into their services, Kuri delivers a clean, maintainable path from concept to deployment.