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"Tools for Local File Read and Write in Minecraft Coder Pack (MCP)" matching MCP servers:

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    Enables blazingly fast file and content searching in large codebases using ripgrep, with intelligent filtering, fuzzy finding, and directory tree visualization while respecting .gitignore and avoiding common bloat directories.
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    2
    MIT
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    A local, zero-dependency MCP server that cuts coding-agent round-trips by aggregating search, read, edit, exec, git, and savings tools into single, validated calls, with cost tracking and no data leaving the machine.
    MIT
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    An MCP server that provides a flexible lens into directory structures and files, enabling LLM clients to efficiently navigate and understand codebases with minimal noise. It offers secure, gitignore-aware file access with tools like directory listing, file reading, and grep-like search.
    1
    MIT
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    MCP server providing npm registry search, package details, dependency auditing, bundle size estimation, and package comparison tools for AI agents.
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    MIT
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    MCP server connecting Claude Code to LM Studio, delegating token-expensive tasks to a local model while keeping the cloud model in control. It reduces cloud context usage by reading files locally and returning only the processed results.
    4
    MIT
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    An MCP server that provides a persistent sandbox for AI coding agents to explore codebases server-side, returning only compact summaries to reduce context consumption.
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    MIT
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    A fully local RAG MCP server for semantic code search and code intelligence, using AST-level chunking and hybrid search to pinpoint functions, classes, and APIs. No cloud, no API keys, zero setup.
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    MIT
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    Enables AI assistants to access and interact with Cursor/VS Code Local History data for file recovery and enhanced context awareness. Provides tools to browse file history, search across snapshots, and restore previous versions of files.
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    MIT
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    MCP server providing dependency and package management tools for AI agents. Analyze licenses, find outdated packages, visualize dependency trees, estimate bundle sizes, and audit security vulnerabilities.
    5
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    MIT
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    Analyzes source code structure across multiple languages using tree-sitter, extracting classes, functions, methods, and metadata with precise line numbers for efficient codebase exploration and AI-assisted development.
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    MIT
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    Provides AI-callable tools for modernizing legacy applications, including stack detection, API contract extraction, SQL to Flyway conversion, and migration effort estimation.
    4
    MIT