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"Replicating ChatGPT Memory Functionality for Task Management and Skill Tracking" matching MCP servers:

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    Enables AI agents to semantically search and retrieve relevant skills from a local Markdown skill database, reducing context waste by loading only needed skills through tiered detail levels and tool calls.
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    MIT
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    Semantic, on-demand skill retrieval for Claude Code that saves tokens and improves skill discovery by replacing the native skill listing with vector embedding search.
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    MIT
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    Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.
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    Apache 2.0
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    Provides access to OpenAI's ChatGPT API with web search capabilities for Claude and other MCP clients. Supports various GPT models with configurable parameters like reasoning effort, temperature, and streaming mode.
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    MIT
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    MCP server providing durable Substrate organizational memory tools, including search, read, query, ingest, remember, and sync. It integrates with Codex to automatically capture completed turns and session boundaries for persistent memory.
    MIT
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    An MCP server that serves company documentation from a Markdown folder, exposing read-only search and fetch tools for agents to discover and retrieve authoritative documents.
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    Improves AI agent task performance by providing task area segmentation, hierarchical RAG, and hybrid search capabilities.
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    MCP ChatGPT Responses connects Claude to ChatGPT through two essential tools: standard queries for AI-to-AI conversations and web-enabled requests for current information. It uses OpenAI's Responses API to maintain conversation state automatically.
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    Embedded, local-first agent memory: facts extracted into a per-namespace SQLite file (vec0 + FTS5) with hybrid retrieval and point-in-time (time-travel) queries. ADD-only history over stdio — no server process, no cloud dependency.
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    Apache 2.0
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    Provides persistent memory for AI agents using hybrid search (vector embeddings + BM25) with neural reranking, enabling storage and retrieval of insights, debugging solutions, and patterns across coding sessions.
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    MIT
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    An MCP server providing long-term memory for LLMs via hybrid search (FTS5 + vector) stored in SQLite, with time-decay scoring and support for multiple AI assistants.
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    MIT
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    Cognitive memory engine for AI agents with 5,100+ knowledge modules, circadian rhythm awareness, emotional state tracking (PAD model), and hybrid semantic search. Supports persistent per-user memory, project-scoped contexts, and multi-protocol access.
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    Apache 2.0