<2-3 sentences summarising what the project addresses and solves, the target audience, and the benefit.> cclsp addresses the challenge of integrating LLM-based coding assistants with Language Server Protocol (LSP) by providing a Model Context Protocol (MCP) server. It enables AI coding tools to accurately navigate code, find references, and perform safe renames, overcoming LLM limitations with precise line/column reporting. This benefits developers seeking enhanced AI-assisted code understanding and refactoring.

How It Works

cclsp acts as an MCP server, translating LLM requests into robust LSP actions. Its core innovation lies in intelligently handling imprecise AI-generated code locations by attempting multiple position combinations and resolving symbols reliably. This approach ensures accurate symbol navigation and refactoring, even when LLMs struggle with exact coordinates.

Quick Start & Requirements

• Installation: Automated setup via npx cclsp@latest setup is recommended. Manual installation involves npm install -g cclsp followed by setup.
• Prerequisites: Node.js 18+ or Bun runtime. Separate installation of language servers (e.g., typescript-language-server, python-lsp-server, gopls) is required.
• Links: Demo available at https://github.com/user-attachments/assets/52980f32-64d6-4b78-9cbf-18d6ae120cdd. Interactive setup wizard guides users through configuration and LSP installation.

Highlighted Details

• Core Functionality: Provides MCP tools for find_definition, find_references, rename_symbol (with dry_run and strict position options), and get_diagnostics.
• Multi-language Support: Configurable for numerous languages including TypeScript, Python, Go, Rust, C/C++, Ruby, PHP, Java, C#, and Swift via their respective LSP servers.
• AI-Friendly: Designed specifically for LLMs to leverage LSP features effectively, overcoming common AI limitations in code context accuracy.
• Configuration: Offers an interactive setup wizard and a flexible JSON configuration system for defining LSP server commands and initialization options.

Maintenance & Community

The README encourages contributions but does not detail specific community channels, active maintainers, sponsorships, or a public roadmap.

Licensing & Compatibility

• License: MIT.
• Compatibility: The MIT license permits commercial use and integration into closed-source projects without significant restrictions.

Limitations & Caveats

A known issue involves potential performance degradation with the Python LSP server (pylsp) over extended periods, which can be mitigated by configuring an automatic restartInterval or manually restarting the server.