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LSP MCP Server

An MCP server that lets you interact with LSP servers

Created by Tritlo2025/03/27
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What is LSP MCP Server?

what is LSP MCP Server? LSP MCP Server is an MCP (Model Context Protocol) server designed to facilitate interaction with LSP (Language Server Protocol) interfaces, enabling LLMs (Large Language Models) to query LSP Hover and Completion providers for enhanced code suggestions. how to use LSP MCP Server? To use the LSP MCP Server, clone the repository, install the dependencies, and run the server by providing the path to the LSP executable along with any necessary arguments. Ensure to start the LSP server using the start_lsp tool before utilizing other functionalities. key features of LSP MCP Server? get_info_on_location: Retrieve hover information at a specific file location. get_completions: Obtain completion suggestions at a specific file location. get_code_actions: Get code actions for a specified range in a file. start_lsp: Initialize the LSP server with a designated root directory. restart_lsp_server: Restart the LSP server without restarting the MCP server. Detailed logging for debugging and auditing. Simple command-line interface. use cases of LSP MCP Server? Enhancing code completion suggestions in IDEs. Providing hover information for better code understanding. Facilitating code actions for refactoring and improvements. FAQ from LSP MCP Server? What are the prerequisites for using LSP MCP Server? You need Node.js (v16 or later) and npm installed. For the demo server, GHC (8.10 or later) and Cabal (3.0 or later) are required. How do I enable logging? You can enable logging by setting the LSP_MCP_LOG environment variable before starting the server. Can I restart the LSP server without stopping the MCP server? Yes! You can use the restart_lsp_server tool to restart the LSP server independently.

As an MCP (Model Context Protocol) server, LSP MCP Server enables AI agents to communicate effectively through standardized interfaces. The Model Context Protocol simplifies integration between different AI models and agent systems.

How to use LSP MCP Server

To use the LSP MCP Server, clone the repository, install the dependencies, and run the server by providing the path to the LSP executable along with any necessary arguments. Ensure to start the LSP server using the start_lsp tool before utilizing other functionalities. key features of LSP MCP Server? get_info_on_location: Retrieve hover information at a specific file location. get_completions: Obtain completion suggestions at a specific file location. get_code_actions: Get code actions for a specified range in a file. start_lsp: Initialize the LSP server with a designated root directory. restart_lsp_server: Restart the LSP server without restarting the MCP server. Detailed logging for debugging and auditing. Simple command-line interface. use cases of LSP MCP Server? Enhancing code completion suggestions in IDEs. Providing hover information for better code understanding. Facilitating code actions for refactoring and improvements. FAQ from LSP MCP Server? What are the prerequisites for using LSP MCP Server? You need Node.js (v16 or later) and npm installed. For the demo server, GHC (8.10 or later) and Cabal (3.0 or later) are required. How do I enable logging? You can enable logging by setting the LSP_MCP_LOG environment variable before starting the server. Can I restart the LSP server without stopping the MCP server? Yes! You can use the restart_lsp_server tool to restart the LSP server independently.

Learn how to integrate this MCP server with your AI agents and leverage the Model Context Protocol for enhanced capabilities.

Use Cases for this MCP Server

  • No use cases specified.

MCP servers like LSP MCP Server can be used with various AI models including Claude and other language models to extend their capabilities through the Model Context Protocol.

About Model Context Protocol (MCP)

The Model Context Protocol (MCP) is a standardized way for AI agents to communicate with various services and tools. MCP servers like LSP MCP Server provide specific capabilities that can be accessed through a consistent interface, making it easier to build powerful AI applications with complex workflows.

Browse the MCP Directory to discover more servers and clients that can enhance your AI agents' capabilities.