"Exploration of the term '.core' and its references" matching MCP servers:

Enables autonomous data exploration on .csv-based datasets, providing intelligent insights with minimal effort.

Provides a read-only MCP interface to locally synchronized Amazon seller data, enabling AI agents and analytics tools to query order, inventory, advertising, and settlement information with completeness and freshness checks for safe analysis.

Enables interaction with dbt projects via the Model Context Protocol for data analysis and insights.

Enables AI assistants to interact with DBT (Data Build Tool) projects, allowing them to query project metadata, inspect models and sources, view compiled SQL, and run DBT commands.

Read-only-by-default MCP server for Datanika, an open-source dlt + dbt-core data pipeline platform: browse connections, introspect and preview source tables, compile and run dbt transformations, and monitor pipeline runs. 25 tools (17 read-only, plus 8 write tools gated behind --allow-write); source lives in the datanika-mcp/ subdirectory of the repo.

Enables the analysis of DBT manifests with automatic schema version detection and lineage tracking, allowing users to query model dependencies, access compiled code, and get detailed model information.

Exposes a synthetic issue tracker and pipeline warehouse as callable tools so an agent can answer operational questions about tickets, pipeline health, runs, incidents, and governed metrics with every claim cited to the exact tool call it came from. All writes are proposal-only, requiring human approval through a gated apply path that logs each step for audit.

Enables schema-aware exploration of JSON data by uploading samples, flattening nested structures, and using heuristic search with token overlap and fuzzy matching to find field paths for target names, accelerating ETL and API onboarding workflows.

Enables users to preprocess, analyze, and visualize CSV data through comprehensive tools for data manipulation, statistical analysis, and graph generation.

A Python MCP server that lets you manage Microsoft Fabric through natural language in Claude Code or Claude Desktop, with 77+ tools covering workspaces, lakehouses, warehouses, SQL, DAX, semantic models, notebooks, pipelines, OneLake, and Microsoft Graph.

This server facilitates scalable discovery and execution of OpenAPI endpoints using semantic search and high-performance processing, overcoming limitations of large spec handling for streamlined API interactions.

MCP server that archives Decent DE1 espresso shots from Visualizer.coffee into SQLite and provides analysis tools for shots, beans, and profiles via MCP.

Enables AI agents to inspect schemas, walk Delta table history, run read-only DuckDB queries, and check data-quality and job-run status safely.

Exposes local DuckDB pizza sales data as MCP tools for querying store-level and total sales metrics via natural language, enabling local LLMs to perform real-time analytical queries.

Enables AI to interact with Microsoft Access (.mdb, .accdb) and SQLite 3 databases, including read-only support for Access 97 databases. Supports executing SQL queries, importing/export data from CSV and Excel files, and storing notes about database files.

Provides stock market data and computes technical indicators like EMA, MACD, and RSI across multiple timeframes using the LongPort API and TA-Lib. It enables users to perform detailed financial analysis and multi-timeframe market reviews through standard MCP tools.

An MCP server that enables AI coding assistants to interact with a local Airflow cluster via its REST API for triggering DAG runs, monitoring status, reading logs, and diagnosing errors.

Provides a stateful local Spark session for running PySpark and SQL cells, enabling local data exploration before deploying to Microsoft Fabric.

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.

Creates compact skeleton representations of large JSON files by preserving structure while truncating string values and deduplicating arrays, helping users understand JSON structure without processing the full data payload.