"Resources for Learning Law" matching MCP servers:

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.

AI-powered MCP server for connecting and managing Jupyter Notebooks. Enables interactive code execution, multi-notebook management, and multimodal output for data analysis, visualization, and machine learning.

An MCP server for executing Malloy queries and managing Malloy resources.

Enables querying and managing SAP Cloud Platform Integration resources such as packages, integration flows, message processing logs, security material, and artifact lifecycle through the CPI OData v2 API.

An MCP server for executing SAS code and managing SAS Viya resources, including data, CAS tables, models, and batch jobs, with support for multiple deployment modes and authentication options.

An MCP server that provides data visualization and machine learning tools, featuring automated intent-based pipeline routing for data cleaning and model training. It enables LLMs to process CSV or JSON data to generate visual charts, perform regressions, or execute clustering analysis.

Read-only MCP server for ZenMoney that syncs financial data into memory and exposes it through tools and resources, enabling agentic analysis of transactions and spending patterns.

Enables access to ForexFactory economic calendar data through MCP resources and tools. Supports retrieving economic events by time periods for integration with trading assistants and agentic workflows.

Enables AI clients to investigate data engineering workflows by exposing tools for job status, logs, schema lookup, read-only SQL, and searching documentation/incidents, along with resources and prompts for ETL failure analysis.

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.

Enables AI to analyze and transform data using fusion algorithms with statistical, machine learning, or hybrid methods. Provides seamless data format conversion and enhanced analytical capabilities through the Model Context Protocol.

Provides a standardized way for MCP clients to interact with Apache Airflow's REST API, supporting operations like DAG management and monitoring Airflow system health.

Reference implementation of KIP-1318, a secure Model Context Protocol server for Apache Kafka that enables AI agents to interact with Kafka clusters through governed tools and resources.

Enables AI applications to integrate with Tableau through tools, resources, and prompts for querying data, exploring content, and retrieving visualizations from Tableau workbooks and datasources.

A FastMCP integration server that provides access to Apache Gravitino metadata management APIs, allowing users to manage catalog/schema/table metadata, tags, and user-role information through a structured interface.

MCP server for managing Tailor Platform resources via tools like create, update, destroy, and search resources, as well as GraphQL queries.

An MCP server for controlling Apache Airflow 3 via its REST API, enabling operations like DAG management, task monitoring, and more through natural language.

Enables AI assistants to search and manage GeoNode resources via natural language, including metadata editing, permission changes, uploads, and ownership transfers, all under the acting user's own permissions.

Enables AI assistants to perform data analysis on local datasets through natural language, orchestrating Python, R, SQL, Spark, Jupyter, Power BI, and Tableau engines for statistics, machine learning, dashboard generation, and batch processing.

Enables AI applications to integrate with Tableau through developer primitives including tools, resources and prompts. Supports querying data from datasources, exploring content like workbooks and views, and retrieving visualizations using the Tableau REST API.