Showing 3 open source projects for "semantic"

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    InsForge

    InsForge

    InsForge is the backend built for AI-assisted development

    InsForge is an open-source backend development platform designed specifically for AI-assisted or agent-driven application development, positioning itself as an agent-native alternative to tools like Supabase by exposing backend primitives (auth, database, storage, serverless functions, and AI integrations) in a way that intelligent agents can understand, reason about, and act upon directly. Rather than forcing developers to manually cobble together authentication flows, database schemas, storage buckets, and cloud functions, InsForge provides a semantic layer and toolchain that let agents configured with Model Context Protocol (MCP) understand the backend state, available operations, and how to manipulate these resources end to end. This enables AI coding assistants to complement human engineers by self-configuring backend components, connecting services, and evolving apps autonomously from prompts without switching contexts or manually provisioning infrastructure.
    Downloads: 4 This Week
    Last Update:
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  • 2
    WrenAI

    WrenAI

    Open-source SQL AI Agent for Text-to-SQL. Make Text2SQL Easy

    Wren AI is a SQL AI Agent for data teams to get results and insights faster by asking business questions without writing SQL, and it's open-source. Wren AI has implemented a semantic engine architecture to provide the LLM context of your business; you can easily establish a logical presentation layer on your data schema that helps LLM learn more about your business context. With Wren AI, you can process metadata, schema, terminology, data relationships, and the logic behind calculations and aggregations with “Modeling Definition Language”, to generate accurate SQL queries with semantic context. ...
    Downloads: 3 This Week
    Last Update:
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  • 3
    Mantic.sh

    Mantic.sh

    A structural code search engine for Al agents

    ...Unlike traditional text-based search tools that mainly match keywords, Mantic.sh understands code structure and meaning by combining syntactic heuristics with neural semantic reranking to produce results that reflect conceptual relevance, which helps find functions, definitions, and patterns that literal search might miss. It uses local embeddings and code graph awareness so that queries like “authentication flow” return not just superficially matching text but contextually related code across multiple repositories. ...
    Downloads: 0 This Week
    Last Update:
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