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"How to access Visual Studio Code" matching MCP servers:

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    A lab demonstrating how to deploy a Model Context Protocol (MCP) server and integrate it with Microsoft Copilot Studio, allowing users to connect AI models to different data sources and tools through a standardized protocol.
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    MIT
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    Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.
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    Apache 2.0
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    A local MCP server that provides semantic code search for Python codebases using tree-sitter for chunking and LanceDB for vector storage. It enables natural language queries to find relevant code snippets based on meaning rather than just text matching.
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    Enables semantic search over codebases using natural language queries, returning relevant code snippets with source locations. Integrates with Claude Code for automatic codebase exploration.
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    MIT
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    An MCP server that provides dynamic codebase context to Claude Code through tools like hybrid search, recent changes, and symbol definitions, enhancing AI-assisted coding with local RAG.
    Last updated
    8
    MIT
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    A self-hosted semantic code retrieval MCP server that enables natural language queries to find relevant code snippets using Tree-sitter AST parsing, embedding, and hybrid search with reranking.
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    MIT
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    Provides code repository indexing and semantic search capabilities, allowing natural language queries to find relevant code snippets with automatic incremental indexing and multi-language support.
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    ISC
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    Advanced content gap analysis using Query Decomposition and Keyword Fan-Out (Google's patented methodology). Tells you exactly what user queries your content covers - and what it misses. Built on academic research because I needed to understand how AI search engines actually evaluate content.
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    Apache 2.0
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    Adds interactive widgets to LLM chats for common tasks like timers, stopwatches, unit conversions, and displaying facts. Breaks away from text-only interfaces by providing visual, interactive components similar to Google's search result widgets.
    Last updated
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    The Unlicense
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    Enables AI agents to search, analyze, and extract insights from YouTube videos including transcripts, visual frames, and benchmarks without requiring API keys. Supports semantic search across playlists, sentiment analysis, and visual content indexing with automatic fallback chains for reliable access.
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    MIT