code-to-tree MCP Server

The code‑to‑tree MCP server gives language models instant, high‑fidelity access to source‑code syntax trees. By converting arbitrary code snippets into Abstract Syntax Trees (ASTs) on demand, it removes the need for LLMs to generate or approximate parse structures themselves. This capability is especially valuable when an assistant must reason about code structure, perform refactorings, or generate documentation that requires precise knowledge of language constructs.

At its core, the server bundles a lightweight executable built with mcpc, so clients need only a single binary to run. Internally it relies on the tree‑sitter parsing engine, which supports a broad set of languages—including C, C++, Rust, Ruby, Go, Java, and Python—without pulling in heavyweight compilers or IDE plugins. The result is a self‑contained tool that can be dropped into any MCP‑enabled workflow, from desktop assistants like Claude to custom IDE extensions.

Key capabilities include:

• Accurate parsing: tree‑sitter produces deterministic ASTs that match the official language specifications, ensuring consistent results across invocations.
• Language agnostic interface: clients simply send code text and a language identifier; the server returns a JSON‑serialised AST that can be consumed by downstream logic.
• Minimal dependencies: the binary ships with all necessary parser libraries, so end users avoid complex build chains or runtime dependencies.

Typical use cases span code review automation, intelligent refactoring assistants, and educational tools that need to explain syntax trees visually. For example, an AI can ask the server to parse a new file, then walk the tree to locate all function definitions and suggest naming improvements. In continuous integration pipelines, the server can validate that code adheres to architectural patterns by inspecting AST nodes before a build step.

Integration is straightforward: MCP clients declare the server’s command path in their configuration, after which any prompt can invoke the service via standard MCP calls. Because the server operates as a separate process, it scales independently and can be upgraded without touching client logic. This decoupling makes it a standout component for developers building sophisticated, code‑aware AI assistants that require reliable syntactic analysis.