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    coldstart gives coding agents durable memory of a specific codebase, with no embeddings, no vector store, and no API key. Agents write notes after real tasks — what a file is for, how a flow spans files, which invariants hold — and those notes are surfaced automatically to a later session whose task matches, so nothing gets rediscovered from scratch. Every note is anchored to real files by content
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    MIT
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    A local-first MCP server that scores your codebase's Build Readiness by reading code and running tests on your machine, outputting a diligence-grade score and risk register without uploading your source.
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    Apache 2.0
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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.
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    MIT
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    Provides AI coding assistants with persistent memory, AST-based project indexing, and tools for live context management and hallucination detection. It enables saving lessons to local files, trimming conversation history, and verifying code symbols to prevent errors.
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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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    Provides compiler-grade TypeScript symbol renaming and file/directory move planning through the TypeScript Language Service, returning structured edit plans without modifying files.
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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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    Local MCP server and CLI for Access layout files, rendered to SVG without Microsoft Access. Enables visual verification of form/report layout changes.
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    MIT
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    A coding agent toolkit that provides IDE-like semantic code retrieval and editing tools, enabling LLMs to efficiently navigate and modify codebases at the symbol level rather than working with entire files.
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    MIT
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    Generates DeepWiki-style documentation for private code repositories with RAG-based Q\&A capabilities, semantic code search, and multi-language AST parsing. Supports local LLMs (Ollama) or cloud providers for privacy-focused codebase analysis.
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    MIT