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    An MCP server that provides persistent memory for database schemas by storing table structures and metadata in a local SQLite file. It enables LLMs to save, retrieve, and manage database snapshots to maintain a structured understanding of database architectures.
    5
    MIT
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    Helps AI agents decide what they are justified in believing from the evidence they have. EWP separates stored memory from verified knowledge, preserves conflicts and source lineage, and produces a deterministic warrant result that MCP clients can use consistently across different memory systems.
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    MIT
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    An MCP server that provides AI trading agents with persistent, outcome-weighted memory to learn from historical performance and detect behavioral biases. It enables agents to automatically adjust strategies and optimize position sizing based on context-aware recall of past trade outcomes.
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    149 PyPI
    1,421
    MIT
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    A Stack Overflow for Claude Code agents — a shared pool of solved-problem fixes.An agent hits an error, calls ask_pool for ranked prior fixes; solves something new, calls post_solution. Semantic search + write-time content shield. Free, Apache-2.0.
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    Apache 2.0
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    Provides time intelligence, persistent memory and complete traceability for AI coding agents. Enables sophisticated activity tracking, timezone management, smart reminders, and cross-session continuity with support for both per-project and centralized storage modes.
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    MIT
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    Saves the user's exact words as immutable, SHA-256-hashed captures before anything else, then derives events, entities, context cards, and causal hypotheses — every fact traceable to its verbatim source. Local-first personal memory for Claude Code, Codex, and any MCP client.
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    2
    MIT
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    Enables AI assistants and applications to interact with Airtable bases through a secure OAuth-authenticated MCP interface, providing complete API coverage for all Airtable operations.
    10
    MIT
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    SourceSage is an MCP (Model Context Protocol) server that efficiently memorizes key aspects of a codebase—logic, style, and standards—while allowing dynamic updates and fast retrieval. It's designed to be language-agnostic, leveraging the LLM's understanding of code across multiple languages.
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    MIT