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mindsdb

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Basic Information

MindsDB is an open-source server designed to let humans, AI, agents, and applications get accurate answers from large-scale, distributed data sources. The repository provides a self-hostable server you can run locally or in the cloud, with recommended Docker-based installation options. It exposes a Model Context Protocol (MCP) server to connect applications, offers MindsDB SQL for creating knowledge bases and unified views, and includes built-in agents specialized for question answering over connected data. The project focuses on connecting hundreds of enterprise data sources, unifying structured and unstructured data for queryable access, and responding with context-aware answers. The codebase and documentation target deployable server functionality, integrations, and developer contribution workflows.

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35255
App URL
https://github.com/mindsdb/mindsdb
Github Repository
https://github.com/mindsdb/mindsdb/blob/main/README.md

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App Details

Features
Connect to many enterprise data sources with documented integrations and Docker-based deployment options. MindsDB SQL provides abstractions such as knowledge bases for indexing unstructured data and views for creating unified, no-ETL access across sources. JOBs enable scheduled synchronization and transformations for near real-time processing. Built-in agents let users chat with and query unified data. An MCP server is included to allow external applications to connect and interact with MindsDB programmatically. The repo contains install and contribution guides, community support channels, and badges indicating Python and Docker ecosystem compatibility.
Use Cases
MindsDB lets teams query and derive answers from federated data without complex ETL by creating unified views and indexed knowledge bases, which simplifies analytics and Q&A workflows. Scheduled JOBs automate data synchronization and transformations so responses can reflect fresh data. Built-in agents and the MCP server enable integration into applications and conversational interfaces, making it easier to embed data-aware intelligence. The Docker-first install options reduce setup friction for both experimentation and production deployments. Community docs, contribution guidance, and support channels help teams extend integrations and customize the server for specific data and application needs.

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