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    Multi-modal RAG engine for AI assistants. Stores conversation history, conclusions, diffs, error traces, and other development artifacts in LanceDB with vector search, multi-factor scoring, and an LLM-driven consolidation pipeline.
    10
    MIT
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    Provides semantic search capabilities over the Plesk Extensions Guide documentation using Retrieval-Augmented Generation (RAG) and vector embeddings. It enables AI assistants to retrieve relevant technical information and answer natural language queries regarding Plesk extension development.
    MIT
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    A Model Context Protocol server integration that creates a persistent, searchable working memory for AI-assisted development by enabling automated context recall and knowledge persistence in Chroma, the open-source embedding database.
    65 PyPI
    24
    MIT
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    Context Portal (ConPort): A memory bank MCP server building a project-specific knowledge graph to supercharge AI assistants. Enables powerful Retrieval Augmented Generation (RAG) for context-aware development in your IDE.
    73 PyPI
    768
    Apache 2.0
  • F
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    Enables semantic search and interaction with Fuel Network documentation and Sway Language resources within AI-powered development environments. It provides high-quality technical context using a local vector database to assist with smart contract development and FuelVM queries.
    7
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    Enables multi-tenant RAG with Qdrant, LM Studio embeddings and summaries, and advanced document processing for semantic search across isolated client collections.
    13
    MIT
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    Enables persistent memory and semantic search for development workflows with hierarchical compression. Store and retrieve development knowledge across IDE sessions using natural language queries, circumventing context window limitations.
    3
    AGPL 3.0
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    An MCP server that gives an Agent Studio project a memory that outlives a run, using S3 for storage and exposing tools to recall, remember, list, and forget memories.
    10 npm
    MIT
  • F
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    A multi-functional computing platform server designed to integrate with large language models like Qwen, providing file access, database connections, API integration, and vector database functionality.
    3
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    An institutional-grade algorithmic trading platform that bridges MetaTrader 5 with an autonomous AI cortex for high-frequency data extraction, ML-driven analysis, and autonomous decision-making using the FEAT methodology.
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    Enables storing, querying, and managing decision traces with semantic search using Voyage AI embeddings and ChromaDB. Supports outcome tracking and category filtering for software development decisions.
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    A multi-model platform that integrates RAG (Retrieval-Augmented Generation) with LLMs, supporting OCR via Tesseract and offering both backend API and frontend web interface.
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  • F
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    Enables context-aware semantic search across codebases using Qdrant vector database with intelligent GitHub issue resolution, Projects V2 management, and progressive context retrieval for 95%+ token reduction in AI-assisted development.
    9
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