Research Methods Library

The Research Methods Library is a Model Context Protocol server that grounds AI assistants in approximately 19,000 sections of methodological texts by Mike Nguyen: A Guide on Data Analysis and its Springer volumes; Advanced Data Analysis; causalverse, an R package for causal inference; Credit Scoring: Theory, Methods, and Practice; Marketing Research: A Technical and Academic Treatment; Social Science Theory: A Field Guide to the Theories, Effects, and Frameworks Behind Research and Business; Applying Tidy Finance with Python to Vietnam, in English and Vietnamese; Machine Learning in Python; AI in Action; and peer-reviewed research articles.

Given a research question, choose_method recommends candidate designs (difference-in-differences, synthetic control, regression discontinuity, instrumental variables, matching, double machine learning, and 56 others), stating when each applies, the identifying assumptions to verify, and the R and Python packages that implement it. search and fetch retrieve the underlying sections; get_code returns runnable R, Python, or Julia code; cite formats references in APA, Chicago, MLA, Harvard, BibTeX, or RIS for the sections consulted.

What you can ask

Explain a method with its assumptions, diagnostics, pitfalls, and a worked example.
Example path

MCP connector

Server URL: https://research-methods-mcp.vercel.app/mcp
Login: None
Protocol: MCP 2026-07-28
Instructions: Research Methods Library: searchable sections, runnable R and Python code, and formatted citations from books, an R package, and research articles by Mike Nguyen on data analysis, statistics, causal inference, econometrics, experimental design, marketing research, empirical finance, credit scoring, machine learning, and AI.
The library is relevant whenever a user asks how to analyze data or answer a research question: which statistical test, model, or study design fits their data; how to estimate a causal or treatment effect; how to check assumptions or robustness; how to plan an experiment or compute sample size; how to write analysis code in R or Python; or how to cite a method.
For a study-design question, start with . To read the material, use search and then fetch. For runnable code, use . For a reference list, use cite with the ids of the sections you used. Every result includes the section URL and the citation of the work it comes from.

Tools

Reads data6

Skills

None in the store listings or on the server

MCP connector

Server URL

https://research-methods-mcp.vercel.app/mcp

None

Protocol

MCP 2026-07-28

Instructions

Research Methods Library: searchable sections, runnable R and Python code, and formatted citations from books, an R package, and research articles by Mike Nguyen on data analysis, statistics, causal inference, econometrics, experimental design, marketing research, empirical finance, credit scoring, machine learning, and AI.

The library is relevant whenever a user asks how to analyze data or answer a research question: which statistical test, model, or study design fits their data; how to estimate a causal or treatment effect; how to check assumptions or robustness; how to plan an experiment or compute sample size; how to write analysis code in R or Python; or how to cite a method.

For a study-design question, start with . To read the material, use search and then fetch. For runnable code, use . For a reference list, use cite with the ids of the sections you used. Every result includes the section URL and the citation of the work it comes from.