"Programs for Statistical Analysis: R, STATA, SPSS" matching MCP servers:

Enables AI agents to invoke a local Stata installation, including a Windows Stata build under Wine on Linux and macOS, for regression analysis, econometrics, paper replication, and empirical research with command guards, resource monitoring, and automatic log capture.

An MCP server that lets Large Language Models interact with Stata software to perform regression analysis and other statistical operations.

Enables LLM/agent applications to execute Stata code, load and inspect data, obtain structured regression results and graphs, and manage background tasks through the Model Context Protocol.

Provides a bridge between Stata statistical software and code editors like VS Code and Cursor, enabling users to run Stata commands directly from the editor, view output in real-time, and get AI-powered assistance with Stata coding.

An MCP server for managing, editing, and running Stata .do files, integrating with Claude Desktop to enable natural language control of Stata analysis on macOS.

Enables AI assistants to execute R code, create visualizations, analyze data, and manage packages through a local Rscript CLI.

MCP server that enables Claude to directly drive Stata, providing a persistent session and 75 tools for data management, estimation, post-estimation, graphs, and export. It lets users perform full Stata analyses through natural language instructions.

Connects AI agents to a local Stata installation, enabling execution of Stata code, data inspection, graph generation, and result verification through natural language interactions.

Enables an agent to execute Stata do scripts or inline commands locally and retrieve structured results including status, error diagnostics, and output text for consumption by the model.

econ-r-mcp is a local MCP server plus companion skill for reproducible applied econometrics and statistics workflows powered by headless R execution.

Provides project-local, reproducible Stata execution for humans and AI agents, with immutable run artifacts, provenance tracking, planning gates, and a shared dashboard.

Connects AI agents to a local Stata installation so they can run Stata commands and .do files, inspect datasets and codebooks, export graphs, look up help, and verify stored r()/e() results with structured error reporting.

Enables Large Language Models to access and manipulate Autodesk Revit models through a pyRevit-based bridge and the Model Context Protocol.

Provides econometric modeling capabilities through R, enabling AI assistants to perform sophisticated analyses including linear regression, panel data models, instrumental variables regression, and diagnostic tests.

Gives LLM agents spatial awareness inside Autodesk Maya, enabling scene inspection and measurement, aesthetic and engineering audits, camera planning, checkpoint/rollback safety, asset import, and viewport or render previews. Agents can also execute arbitrary Python in Maya to build and verify 3D scenes against engineering rules instead of writing blind.

Enable Claude (or any other LLM) to interactively debug your code (set breakpoints and evaluate expressions in stack frame). It's language-agnostic, assuming debugger console support and valid launch.json for debugging in VSCode.

MCP server that gives AI agents isolated, named Linux computers with stable IDs and lifecycle control. Supports multiple backends like Docker, Fly Machines, Modal, and E2B, with a dashboard for managing sandboxes.

AI-powered quantitative research assistant with 45 tools for causal inference methods (DID, RDD, IV, PSM), regression analysis, power calculations, and statistical code generation in R, Stata, and Python.

Enables AI assistants to build and manage Unity projects directly through the Unity Editor, providing 150+ tools for scene creation, script generation, play mode control, input simulation, and performance analysis.

Enables LLMs to safely execute pandas code for data analysis and generate interactive visualizations through MCP protocol.