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    Provides AI models with structured access to Trino's distributed SQL query engine, enabling LLMs to directly query and analyze data stored in Trino databases.
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    MIT
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    Entroly is a high-performance context engineering engine that optimizes AI coding agent context windows through information-theoretic compression and reinforcement learning. It gives your AI 100% codebase visibility while reducing token consumption by an average of 78%.It's learns fully autonomously.
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    Apache 2.0
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    Local-first context retrieval engine that serves precise documentation chunks to coding agents via MCP, ensuring high-confidence context for code generation.
    MIT
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    A task-aware context compression layer for Agent workflows, RAG pipelines, and AI Coding assistants, reducing noisy logs, retrieval chunks, and code context into high-signal LLM inputs via CLI, Python SDK, and MCP.
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    MIT
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    MCP server for managing and serving dynamic prompt templates using elegant and powerful text template engine. Create reusable, logic-driven prompts with variables, partials, and conditionals that can be served to any compatible MCP client like Claude Code, Claude Desktop, Gemini CLI, etc.
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    MIT
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    A narrative graph engine that enables LLMs to generate, track, and mutate complex fictional worlds while maintaining consistency between factions, characters, and locations. It acts as a specialized RAG framework for storytelling, allowing models to manage thousands of entities without exceeding context limits.
    MIT
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    Enables web search through SearXNG instances, offering tools for general and category-specific queries, engine selection, time filtering, and engine discovery.
    MIT
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    A production-ready reasoning engine that integrates Claude AI with specialized MCP tools for knowledge retrieval, schema validation, and domain-specific rubric evaluation. It enables structured RAG-based analysis across legal, health, and science domains via a RESTful API.
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    An MCP server that enables natural language interaction with Google's Discovery Engine API, allowing users to search, recommend, and manage data through conversational interfaces.
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    A multi-document RAG engine server that enables intelligent querying and analysis of PPT documents using the Model Context Protocol (MCP).
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    Enables agents to perform controlled enterprise data queries through semantic intent, with runtime validation of statistics, filters, granularity, permissions, and physical bindings. Exposes tools like semantic_query for safe, fail-closed access to data horizons and capabilities.