Context7
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Description from the maker (original English)
Research methods for AI assistants: study design guidance, R and Python code, and citations
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Works in Claude on the web, desktop and mobile:
https://research-methods-mcp.vercel.app/mcpRun this in your terminal
claude mcp add --transport http research-methods https://research-methods-mcp.vercel.app/mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"research-methods": {
"url": "https://research-methods-mcp.vercel.app/mcp"
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"research-methods": {
"type": "http",
"url": "https://research-methods-mcp.vercel.app/mcp"
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
ChatGPT connects only to servers on the internet:
https://research-methods-mcp.vercel.app/mcpMenu names can differ slightly by plan and over time.
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Tool names and descriptions exactly as the server reported them on Nov 8, 2026. The maker wrote them, not us; we show them as plain text.
searchSearch sections of textbooks and an R package on research methods and data analysis: statistics and hypothesis testing, regression and generalized linear models, causal inference (difference-in-differences, synthetic control, regression discontinuity, instrumental variables, matc
fetchRead one section of the library by its section id. Returns the section in Markdown with its code, the section URL, and the citation of the work it comes from. Long sections come in parts; the text names the id of the next part.
choose_methodRecommend statistical, econometric, causal inference, or machine learning methods for a research question or data analysis task: which statistical test or model fits the data, how to estimate a causal or treatment effect, how to analyze an A/B test or experiment, how many observa
get_codeGet runnable code from the library for a specific statistical, econometric, causal inference, or machine learning task, in R, Python, or Julia. Suited to requests for code that carries out a named estimator, test, or modeling step; it returns code with brief context, not an expla
citeFormat references for works in the library in APA, Chicago, MLA, Harvard, BibTeX, or RIS. Pass the ids of the sections you used to get a deduplicated reference list plus the section links, or pass source ids to cite whole works. With no ids, returns a reference for every work in
list_sourcesList the works in the library (textbooks, an R package, and research articles) with their topics, code languages, section counts, licenses, links, and how to cite each one. Suited to questions about what the library covers or which work to consult. Takes no parameters and returns
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 9, 2026
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In the same category: Context7, Codebase Memory, Exa
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Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
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Connect AI agents to Exa for web search, content fetching, and multi-step research.
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Research Methods Library
A Model Context Protocol server that grounds AI assistants in methodological texts: study design recommendations, identifying assumptions, runnable R and Python code, and a citation for every source.
The Research Methods Library is a Model Context Protocol (MCP) server. Given a research question, it recommends candidate designs, states their identifying assumptions, returns runnable R and Python code, and supplies a formatted citation for every source consulted. Its index contains approximately 19,000 sections from 9 books, an R package, and the author's research articles (listed under Sources) covering causal inference, econometrics, experimental design, marketing research, credit scoring, machine learning, and artificial intelligence.
The server works with Claude, ChatGPT, Amazon Bedrock AgentCore, Cursor, Visual Studio Code, and any other MCP-compatible client. Access is free and requires no account or API key.
Endpoint: https://research-methods-mcp.vercel.app/mcp. Access is free and requires no account or API key.
| Client | Configuration |
|---|---|
| Claude (web, desktop, and mobile) | Settings → Connectors → Add custom connector; enter the endpoint |
| Claude Code | claude mcp add --transport http research-methods https://research-methods-mcp.vercel.app/mcp |
| ChatGPT | Settings → enable developer mode → add a custom connector of type MCP server with the endpoint and no authentication |
| Amazon Bedrock AgentCore | Add the endpoint as an MCP server target of an AgentCore Gateway, with no outbound authorization: agentcore add gateway-target --name research-methods --type mcp-server --endpoint https://research-methods-mcp.vercel.app/mcp --gateway , then agentcore deploy |
| Cursor, Visual Studio Code | Use the buttons above |
| Windsurf, Cline, Zed, and other clients | Add the following JSON to the client's MCP configuration |
{
"mcpServers": { "research-methods": { "url": "https://research-methods-mcp.vercel.app/mcp" } } }
<!-- install:end -->
States raised the minimum wage in different years. How do I estimate the effect on teen employment?
For this query the assistant calls choose_method, which returns staggered difference-in-differences together with its scope conditions, the reason a conventional two-way fixed-effects regression can be biased when treatment effects are heterogeneous, the assumptions to verify, implementations in R (did, fixest, didimputation, HonestDiD) and Python (csdid, pyfixest, differences), and the relevant readings.
Give me Python code for a probability-of-default model with gradient boosting.
Only California passed the law and I have 30 years of state data. What can I do?
Write the methods section for my regression discontinuity and give me BibTeX for the sources.
Each response links to the specific section consulted and carries the citation of the work from which it is drawn.
| Tool | What it does |
|---|---|
choose_method | Matches a research question to methods, with when to use each, key assumptions, R and Python packages, and readings. 62 curated methods. |
search | Finds sections across all works, with links, snippets, code languages, and a citation. Compatible with ChatGPT deep research. |
fetch | Reads a section in full, with its code, link, and citation. Compatible with ChatGPT deep research. |
get_code | Runnable R, Python, or Julia code for a task, with the packages it uses. |
cite | References in APA, Chicago, MLA, Harvard, BibTeX, or RIS for the sections consulted, deduplicated by work. |
list_sources | The works in the library (textbooks, an R package, and research articles), with topics, languages, licenses, and links. |
Prompts (slash commands in clients that support them): plan_analysis, write_methods_section, explain_method. Resources: the library catalog and a table of contents for each work.
All tools are read-only. The server makes no calls to language models and stores no information about its users; see the privacy policy.
| Work | Code | Sections | Served | License |
|---|---|---|---|---|
| A Guide on Data Analysis | Python, R | 1,635 | Full text | CC BY-NC-SA 4.0 |
| causalverse: The All-in-One Causal Inference Toolkit | R | 1,163 | Full text and function reference | GPL-3.0 |
| Credit Scoring: Theory, Methods, and Practice | Python | 2,639 | Full text | CC BY 4.0 text, MIT code |
| Marketing Research: A Technical and Academic Treatment | Python, R | 1,842 | Excerpts and code; full text on the website | All rights reserved text, MIT code |
| AI in Action: A Reference for Artificial Intelligence | Julia, Python | 5,978 | Excerpts and code; full text on the website | All rights reserved |
| Advanced Data Analysis | Python, R | 1,844 | Full text | CC BY 4.0 |
| Applying Tidy Finance with Python to Vietnam | Python | 1,345 | Excerpts and code; full text on the website | All rights reserved |
| Tài Chính Ứng Dụng với Python | Python | 1,309 | Excerpts and code; full text on the website | All rights reserved |
| Machine Learning in Python | Python | 361 | Full text | CC BY-SA 4.0 |
| Social Science Theory: A Field Guide to the Theories, Effects, and Frameworks Behind Research and Business | R | 1,118 | Full text | CC BY 4.0 text, MIT code |
| Research Articles and Publications | — | 7 | Abstracts, DOIs, and citations | Publishers' terms |
Sections of *A Guide on Data Analysis* that appear in the Springer print volumes are cited as their published chapter, then the volume. For example, a section on causal inference is cited as Nguyen, M. (2025). Causal inference. In *Experimental design* (Vol. 4, pp. 7–48). Springer Cham. https://doi.org/10.1007/978-3-032-01839-7_2, in Nguyen, M. (2025). *Experimental design* (Vol. 4). Springer Cham. https://doi.org/10.1007/978-3-032-01839-7
The source files of each work (.Rmd, .qmd, .Rd) are parsed into a single index of sections, code blocks, and citations. During index construction every link is verified against the published website: a section whose anchor is absent links to its chapter page, and unpublished pages are excluded. Queries are answered from the in-memory index; no database or language model is involved.
docker build -t research-methods-mcp .
docker run -p 8080:8080 research-methods-mcp # http://localhost:8080/mcp
Or with Node.js: npm ci && npm run build && npm start (listens on 127.0.0.1:8787; set HOST and PORT to change). The same handler runs on Vercel through api/index.mjs and vercel.json (the hosted endpoint) and on Deno Deploy through src/deno.ts.
npm ci
npm run build:index # parse the book repositories (sibling folders) into data/index.json.gz npm run build # bundle dist/stdio.js and dist/http.js npm test # end-to-end tests through real MCP clients npm run check-links # audit every link in the index against the live sites
To add a book, add an entry to sources.yml and rebuild the index. To add or tune a method, edit methods.yml; the build fails if a method points at a section that does not exist.
Users are asked to cite the works they draw on; the cite tool formats the references. To cite the server itself, see CITATION.cff.
The server code is MIT licensed. The content it returns keeps each work's own license, listed above and by the list_sources tool.