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"Semantic UI" matching MCP servers:

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    MCP server for the OrionBelt Semantic Layer. Enables LLMs to explore governed semantic models, compile YAML metric definitions into optimized SQL across 8 engines (BigQuery, ClickHouse, Databricks, Dremio, DuckDB, MySQL, PostgreSQL, Snowflake), and execute analytics queries via natural language. Works with Claude, Cursor, Windsurf, and Copilot.
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    Apache 2.0
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    A server that enables querying the dbt Semantic Layer through natural language conversations with Claude Desktop and other AI assistants, allowing users to discover metrics, create queries, analyze data, and visualize results.
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    MIT
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    Connect Claude to your Power BI semantic models. Browse workspaces, tables, and measures, run DAX queries, and get results — with large datasets automatically saved to local CSV files to protect the LLM context window. Includes a query history log for cross-session reuse and auditability.
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    MIT
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    50 tools and 400 functions for working with Excel/.xlsx spreadsheets — read/write, recalculate formulas, diff, repair broken references, and audit. Built for AI agents.
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    MIT
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    MCP server that exposes Chronova developer productivity data to AI agents. Built on the Model Context Protocol, it lets tools like Claude Desktop, Cursor, and OpenCode query your coding stats, activity, and AI-assisted coding metrics.
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    ISC
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    A tutorial implementation MCP server that enables analysis of CSV and Parquet files. Allows users to summarize data and query file information through natural language interactions.
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    Enables AI assistants to interact with Databar.ai's data enrichment API, allowing discovery, configuration, and execution of data enrichments across hundreds of providers using natural language.
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    MIT
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    Enables LLMs to interact with Google Analytics Admin and Data APIs to retrieve account summaries, property details, and custom metrics. It allows users to run core and real-time reports to analyze website performance and configuration via natural language.
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    Apache 2.0
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    A read-only MCP server that exposes dbt project artifacts and data quality result tables (BigQuery/Postgres) to LLM clients, enabling deep introspection, run-history analysis, source freshness, test coverage, and lineage walks.
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    MIT
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    Aurekai MCP exposes 89 native akai_\* runtime operators to any MCP-compatible host, covering the full Aurekai binary family — API gateway, artifact inspection, proof bundle export, semantic embedding, batch queuing, entity detection, compression, and more. Zero external dependencies; runs locally via npx -y @aurekai/mcp.
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    Apache 2.0