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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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    Elastic 2.0
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    yade-mcp connects AI agents to YADE — the open-source discrete element method engine — through the Model Context Protocol. Browse API docs, run simulations, and execute code, all through natural conversation.
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    MIT
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    MCP server that gives AI agents full access to ITASCA PFC - browse documentation, run simulations, capture plots, all through natural conversation. Built on the Model Context Protocol, pfc-mcp turns any MCP-compatible AI client (Claude Code, Codex CLI, Gemini CLI, OpenCode, toyoura-nagisa, etc.) into a PFC co-pilot that can look up commands, execute scripts, monitor long-running simulations.
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    MIT
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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.
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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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    MIT
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    Enables pattern-based file editing operations using copy/paste functionality with text landmarks instead of exact string matching. Allows AI agents to efficiently manipulate file content by identifying code patterns and insertion points without consuming large amounts of context tokens.
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    Enables browser automation and web testing on ARM64 devices like Raspberry Pi using system Chromium. Supports navigation, screenshots, form filling, JavaScript execution, and complete SaaS testing workflows through Claude Code integration.
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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 starter template for building custom MCP servers that can integrate with Claude, Cursor, or other MCP-compatible AI assistants. Provides a clean foundation with TypeScript support, example implementations, and easy installation scripts for quickly creating tools, resources, and prompt templates.
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