vsc-mcp

thomasgazzoni/vsc-mcp

3.5
developer_toolsai_chatbot

If you are the rightful owner of vsc-mcp and would like to certify it and/or have it hosted online, please leave a comment on the right or send an email to henry@mcphub.com.

VSC-MCP is a project that provides tools to expose Language Server Protocol (LSP) functionality as Model Context Protocol (MCP) tools, enabling AI clients to analyze and edit code programmatically.

Tools

Functions exposed to the LLM to take actions

pack_codebase

Package a local code directory into a consolidated XML file for AI analysis. This tool analyzes the codebase structure, extracts relevant code content, and generates a comprehensive report including metrics, file tree, and formatted code content. Supports Tree-sitter compression for efficient token usage.

pack_remote_repository

Fetch, clone, and package a GitHub repository into a consolidated XML file for AI analysis. This tool automatically clones the remote repository, analyzes its structure, and generates a comprehensive report. Supports various GitHub URL formats and includes security checks to prevent exposure of sensitive information.

read_repomix_output

Read the contents of a Repomix-generated output file. Supports partial reading with line range specification for large files. This tool is designed for environments where direct file system access is limited (e.g., web-based environments, sandboxed applications). For direct file system access, use standard file operations.

grep_repomix_output

Search for patterns in a Repomix output file using grep-like functionality with JavaScript RegExp syntax. Returns matching lines with optional context lines around matches.

file_system_read_file

Read a file from the local file system using an absolute path. Includes built-in security validation to detect and prevent access to files containing sensitive information (API keys, passwords, secrets).

file_system_read_directory

List the contents of a directory using an absolute path. Returns a formatted list showing files and subdirectories with clear [FILE]/[DIR] indicators. Useful for exploring project structure and understanding codebase organization.

Prompts

Interactive templates invoked by user choice

pack_remote_repository

Pack a remote GitHub repository for analysis

Resources

Contextual data attached and managed by the client

No resources

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