"Information about SAS (Statistical Analysis System) or other related terms" matching MCP servers:

Enables coding agents to write, run, and validate SAS 9.4 code locally via SASPy, with log triage, schema discovery, and safety guardrails.

This read-only MCP Server allows you to connect to SAS Data Sets data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out our MCP Server for SAS Data Sets (https://www.cdata.com/drivers/sasdatasets/download/mcp).

This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for SAS xpt (beta): https://www.cdata.com/download/download.aspx?sku=JXZK-V&type=beta

Enables MySQL database analysis through natural language, including schema exploration, query execution, performance analysis, and ER diagram generation via the Model Context Protocol.

A read-only MCP server for bounded table discovery, deterministic profiling, and maintained-library statistical testing (Welch's t-test and two-proportion z-test) using SQLite, pandas, SciPy, and statsmodels.

A read-only MCP server for exploring and analyzing a Secoda data catalog, enabling AI chat, semantic search, glossary browsing, and data lineage tracing.

Connects Claude Desktop to a healthcare claims database for natural-language analysis of CPT codes, reimbursement rates, payer performance, and denial patterns.

A server that enables executing and validating SQL queries against Google BigQuery with safety features that prevent data modifications and excessive processing.

An MCP server designed for SQL analysis that demonstrates sampling capabilities by interacting with SQL files in a local directory. It provides a framework for testing client-side sampling while managing SQL-based contexts.

Enables forensic analysis of Windows notification databases (wpndatabase.db) from E01 forensic images, automatically extracting and parsing notification data with search, filtering, timeline analysis, and sensitive information detection capabilities.

This read-only MCP Server allows you to connect to Azure Analysis Services data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).

Enables users to manage company departments, employees, expenses, and performance ratings through a natural language interface in Claude Desktop. It features 12 specialized tools for comprehensive CRUD operations and AI-powered organizational analysis using Google Gemini.

MCP server for snowflake that doesn't allow write operations under any circumstances, and includes a system prompt.

Retrieves comprehensive patient information including personal details, insurance plans, and employee data through the get_patient tool. Supports Docker Compose deployment and integration with Watson Orchestrate for healthcare data access.

Enables comprehensive analysis of CSV files and SQLite databases through tools for statistics, correlations, anomaly detection, pivot tables, time series analysis, visualization, and automated insights discovery.

This MCP server enables users to interact with and analyze the dair-ai/emotion dataset from Hugging Face containing labeled Twitter messages. It provides tools to sample data, search text, and perform statistical analysis on emotion distributions.

A comprehensive system that helps organizations track, manage, and respond to security vulnerabilities effectively through features like vulnerability tracking, user management, support tickets, API key management, and SSL certificate management.

A simple Model Context Protocol (MCP) server that allows LLMs to create and manage user entries in a JSON file system database.

A production-grade MCP server that enables AI assistants to securely manage healthcare data through clinical tools for patient vitals, lab results, and medication ordering. It prioritizes security and compliance with features like HIPAA-ready audit logging, PII redaction, and role-based access control.

Enables querying a Neo4j knowledge graph about Wroclaw University of Science and Technology using natural language. Converts user questions into Cypher queries and retrieves contextual information through an intelligent RAG pipeline with LLM-powered query routing.