"The Models Resource" matching MCP servers:

An MCP server that gives models semantic context about a data warehouse, including table meaning, units, lineage, and health, to reduce guessing.

Bridges Microsoft Foundry agents and Power BI semantic models into GitHub Copilot Chat, enabling users to query and modify measures as the signed-in user via MCP.

This server acts as a MCP bridge to interact with the Cribl REST API. It allows AI models or other MCP clients to query and manage Cribl configurations.

The Excel to JSON MCP provides a standardized interface for converting Excel and CSV data into JSON format using the Model Context Protocol.

Enables discovery of Power BI workspaces and semantic models via REST API and Microsoft Modeling MCP, with authentication options including service principal and device login.

An open-source MCP server that connects to various data sources (SQL databases, CSV, Parquet files), allowing AI models to execute SQL queries and generate data visualizations for analytics and business intelligence.

The JSON to Excel MCP provides a standardized interface for converting (1)JSON data (2)URL pointing to JSON files into CSV format

Enables large language models and AI agents to securely and efficiently interact with Apache Kafka clusters through the Model Context Protocol.

An MCP server that allows AI models to create data visualizations using Vega-Lite syntax by providing tools to save data tables and generate visualizations from them.

Enables MCP clients to inspect, validate, transform, and query CityJSON models, with support for conversion, persistence, and 3D geometry validation.

This MCP server enables interaction with the Polytomic API to manage data connections, models, and synchronization tasks. It supports both Reverse ETL and ELT operations, allowing users to trigger syncs, monitor execution status, and configure data pipelines.

Enables AI assistants to manage a GBIF IPT from resource creation to publication, including metadata editing, data validation, Darwin Core mapping, and publishing, through plain language requests.

Exposes safe JSON contracts for validating and preparing datasets, running supervised fine-tuning, preference learning, RL, distillation, and evaluation, and managing checkpoints and exports through the Tinker SDK and Cookbook. It lets agents discover models and Hugging Face datasets, plan and execute training recipes, compare experiments, and export selected models.

An MCP server that exposes VeloDB analytics data to AI clients through a governed semantic metrics layer (MetricFlow) and raw SQL fallback, with multi-workspace isolation, staging workflows, and a web UI for managing models.

Enables DeepSeek Harness models to directly call local ArcGIS Pro via MCP tools for reading projects, layers, GDB structures, and executing Buffer/Clip/custom ArcPy operations locally.

A production-ready MCP server that provides comprehensive dbt project quality assessment for any GitHub repository, enabling AI agents to analyze dbt models, check metadata coverage, and map data lineage.

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.

Enables querying open Power BI Desktop models locally, including discovering instances, listing tables and measures, and running DAX queries without cloud login or publishing.

Provides read-only access to MetaTrader 5 market data, trading history, and technical analysis through Python execution. Supports querying price data, calculating indicators, creating charts, and generating forecasts with Prophet and ML models.

Enables agents to inspect dbt model semantics, retrieve contracts and lineage, and verify that edits do not change what models mean.