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    A read-only MCP server that provides document awareness for agents by parsing local files into structured profiles, blocks, chunks, and search results, enabling agents to understand and cite document content without dealing with raw file formats.
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    Apache 2.0
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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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    Persistent, consensus-validated institutional memory for AI agents. Gives LLMs real memory that survives across sessions - validated through BFT consensus, not just dumped to a file.
    Last updated
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    Apache 2.0
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    Mason indexes your codebase into a persistent concept map linking features and flows to their implementing files, so AI agents can answer "where is X implemented" without running grep/glob. It also provides pre-edit impact analysis and generates CLAUDE.md files from structured analysis of git history, architectural file sampling, and test mappings.
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    MIT
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    A long-term memory MCP server for AI agents that stores memories (facts, decisions, etc.) in a single SQLite database with hybrid search and full edit history, ensuring consistency across sessions.
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    MIT
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    A personal digital twin MCP server that manages professional context, including skills, experience, and project learnings. It allows AI assistants to retrieve and update user preferences and career interests across different development environments.
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    A Model Context Protocol server that enables AI models to perform real-time internet and knowledge searches through Higress, enhancing model responses with up-to-date information from Google, Bing, Arxiv, and internal knowledge bases.
    Last updated
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    Apache 2.0
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    An MCP server for managing work logs, research results, and task checkpoints to enable seamless collaboration and state recovery between AI agents. It provides a persistent memory layer for tracking project history and resuming workflows across different sessions or tools.
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    A productivity coaching assistant designed for ADHD support that provides intelligent task management, goal tracking, and personalized recommendations. It utilizes a persistent memory system to learn user patterns and preferences, helping to reduce decision paralysis through actionable suggestions.
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