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    MCP server for managing Git operations on local repositories, allowing users to list repositories, get and create tags, list commits, push tags, and refresh repositories through a standardized interface.
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    The Git MCP Server allows AI assistants to perform enhanced Git operations via the Model Context Protocol, supporting core Git functions, branch and tag management, GitHub integration, and more.
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    IMCP - Insecure Model Context Protocol The DVWA for AI Security! Welcome to IMCP – a deliberately vulnerable framework that exposes 16 critical security weaknesses in AI/ML systems. Whether you're a security researcher, developer, or educator, IMCP is your playground for hands-on learning about real
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    JavaScript
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    A TypeScript wrapper library for the Model Context Protocol SDK that provides a simplified interface for creating MCP servers with tools, resources, and prompts without needing to work directly with the protocol.
    23
    AGPL 3.0
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    A GitHub-based implementation of the Model Context Protocol that enables LLMs to access and manipulate data in a Universal Object Reference (UOR) framework, providing standardized interfaces for object management with decentralized storage.
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    Turns any YAML manifest into a fully-functional MCP server without hosting infrastructure, enabling custom tools, resources, and prompts via declarative configuration.
    25
    MIT
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    An MCP server that preserves LLM context by intercepting large data outputs and returning only concise summaries or relevant sections. It enables efficient sandboxed code execution, file processing, and documentation indexing across multiple programming languages and authenticated CLIs.
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    17,960
    20,472
    Elastic 2.0
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    Context Mode is an MCP server that reduces context window waste by sandboxing data-heavy tools, tracking session state in SQLite, and promoting code-based analysis over raw data reads, achieving up to 98% context savings.
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    17,960
    Elastic 2.0
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    An MCP server that enables processing of massive datasets up to 10M+ tokens using a recursive language model pattern for strategic chunking and analysis. It automates sub-queries and result aggregation using free local inference via Ollama or the Claude API to handle context beyond standard prompt limits.
    17
    1
    MIT
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    Provides AI coding assistants with context optimization tools including targeted file analysis, intelligent terminal command execution with LLM-powered output extraction, and web research capabilities. Helps reduce token usage by extracting only relevant information instead of processing entire files and command outputs.
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    TypeScript
    MIT