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    Enables AI assistants and developers to analyze code for language-specific best practices and idiomatic patterns across programming languages, CI automation, and configuration formats.
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    MIT
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    Provides GDB and clangd-based tools for debugging C++ programs, enabling step execution, variable inspection, diagnostics, and combined runtime-static analysis.
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    MIT
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    An MCP server that extends AI coding assistants with deterministic, algorithmic capabilities such as code analysis, fault localization, and formal verification, enabling an autonomous engineering team within the IDE.
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    MIT
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    Transforms code repositories and development documentation into a queryable Neo4j knowledge graph, enabling AI assistants to perform intelligent code analysis, dependency mapping, impact assessment, and automated documentation generation across 15+ programming languages.
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    Enables token-efficient semantic search and analysis over any directory of files through hybrid search, directory overview, structural analysis, and dependency graphs.
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    MIT
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    Enables Claude to access and search UVM 1.2 source code, class hierarchies, and method implementations, providing expert-level knowledge of the Universal Verification Methodology.
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    MCP server that provides AI assistants with structured access to codebases via LogicStamp Context, enabling component analysis, dependency graphs, drift detection, and token-optimized context delivery.
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    MIT
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    Topos scores code quality by analyzing the geometric and topological structure of program graphs, surfacing structural debt that conventional linters can't compute. Gives coding agents a medal-scored (SLOP → GOLD) feedback loop for writing cleaner, more composable code.
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    BSD 3-Clause
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    Enterprise-grade (40m+ lines) codebase intelligence in a zero-setup, private and local MCP: managed indexing, hybrid semantic search, polyglot code dependency graphs, and DB/API/infra knowledge. Benchmark: 61% less tokens, 84% fewer calls, 37x faster than standard AI grep.
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    AGPL 3.0
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    memex is a developer context-continuity MCP server — it watches your git repos and builds a temporal knowledge graph (modules, symbols, decisions, open problems) via Graphiti + Neo4j, then serves it to any AI coding agent over MCP. Every edge carries a validity window and a confidence score that decays over time. 12 tools across read and write. Install via npx -y stifler-memex-mcp. MIT licensed.
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    MIT
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    An AI-powered toolkit for the M8 mobile development framework that enables automated generation of Vue pages, low-code components, and mock data. It provides real-time code standard validation and a comprehensive UI component knowledge base to streamline development in AI editors.
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    MIT