MCP-for-Stata
Related Servers
Alternatives to MCP-for-Stata
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityDmaintenanceConnects AI agents to a local Stata installation, enabling execution of Stata code, data inspection, graph generation, and result verification through natural language interactions.597 PyPI90AGPL 3.0
- AlicenseNot gradedqualityCmaintenanceConnects 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.AGPL 3.0
- FlicenseNot gradedqualityDmaintenanceEnables 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.1-
- AlicenseAqualityBmaintenanceEnables 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.10MIT
- AlicenseCqualityDmaintenanceProvides project-local, reproducible Stata execution for humans and AI agents, with immutable run artifacts, provenance tracking, planning gates, and a shared dashboard.22AGPL 3.0
- AlicenseAqualityBmaintenanceControls the Stata GUI through Windows Stata Automation COM, enabling do-file management, command execution, and data analysis within natural language workflows.127MIT
TDQS
Scored across 4 tools
Each tool targets a distinct action: stata_do executes code, get_data_info inspects datasets, help retrieves command docs, and read_log reads log files. There is no meaningful overlap between executing, inspecting, documenting, and reading outputs.
get_data_info and read_log follow a clean verb_noun pattern, but stata_do uses a domain prefix while help is a bare noun with no verb. The set is readable but mixes several conventions.
Four tools is reasonable for a focused Stata execution server, covering run, inspect, document, and read-log workflows. It is on the lean side but each tool earns its place without redundancy.
The surface covers the core loop of running Stata, understanding data, consulting help, and reading logs. Minor gaps exist (e.g. no direct inline command execution distinct from do-files, no data writing or file listing), but core workflows are supported.