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

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

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.

Controls the Stata GUI through Windows Stata Automation COM, enabling do-file management, command execution, and data analysis within natural language workflows.

Enables AI agents to drive IBM SPSS Statistics for statistical analysis and publication-quality chart generation through natural language, returning structured results and ensuring safe execution.

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.

Enables AI assistants to execute IBM SPSS Statistics workflows via natural language, covering data management, restructuring, analysis, charting, and report export.

Enables AI agents to run IBM SPSS Statistics on macOS for statistical analyses, generate paper-ready charts, extract structured results, and execute mediation/moderation analyses with safety controls.

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.

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.

MCP server for safe batch execution of IBM SPSS Statistics syntax (.sps) via stats.exe Production mode, with static security checks and sandboxed output.

Provides a read-only interface to audit and continue coding agent sessions by extracting plans, intents, and edit authorship from history across multiple agents (Claude, Codex, OpenCode, Antigravity, Pi) via MCP, CLI, and Python SDK.

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

Provides read-only, source-attributed access to current CRAN and Bioconductor package metadata, dependencies, function documentation, vignettes, and version compatibility checks for AI assistants. It also enables retrieval of official Shiny, Quarto, Positron, and visualization docs alongside static analysis of R, ggplot2, and Quarto source code without executing it.

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

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

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.

Enables AI agents to discover, retrieve, compare, and analyze trusted macroeconomic statistics from central banks and international organizations, resolving concepts to official series with provenance and validation.

Enables local analysis of unstructured documents (PDF, DOCX, PPTX, SVG, PNG) by extracting text and structure with citation anchors, and verifies summaries against source material before a human approves saving a report.

AI-powered terrain analysis for any location on Earth. Uses super-resolution and computes environmental risk metrics including erosion, water flow, and a composite Site Intelligence Score.