Search arXiv papers, download full text, semantic search, citation graphs, and alerts via MCP.
Research Methods Library is installed from its publisher's own source and answers where it runs, so this marketplace is not in the path of a single call. There is no address here to send one to, and a panel that pretended otherwise would be showing you an answer we made up. Install it and call it from your own client — the Installation tab has the entry for each one.
What it does
Research methods for AI assistants: study design guidance, R and Python code, and citations
Quickstart
# 1 — add it to Claude Code
claude mcp add --scope user --transport http research-methods-library-mcp https://research-methods-mcp.vercel.app/mcp
# 2 — ask your agent for something these tools do
# search, fetch, choose_method and 3 more
Research Methods Library costs nothing on mcprush: there is no plan to choose here, no cap to set and nothing mcprush can bill you for.
Collected from a public index. Nobody has claimed this account, so nothing here was written by its author — claim it if it is yours.
Where are you running it?
Every route below installs the same thing and ends at the same approval screen. Nothing here runs on your machine and nothing runs on ours: this server answers at its publisher’s own address, and what you install is the connection straight to it.
This is a public server: it answers at its publisher’s own address and this marketplace is not in the path. Claude Code registers it in one command; --scope user makes it available in every project. The transport below is http, as the publisher's own manifest declares it.
claude mcp add --scope user --transport http research-methods-library-mcp https://research-methods-mcp.vercel.app/mcpReconnect, or start a new session, and the tools appear in the model’s tool list.
One config entry pointing straight at the publisher’s own address — this marketplace is not in the path, and nothing from this listing executes on your machine.
6 tools, with what each one reads, writes and reaches shown before you agree — the same list on every route above. Read the tool surface.
Tool surface
What the model actually sees. Descriptions are diffed on every release — see version history.
Search 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, matching, double machine learning), econometrics, experimental design, survey methods, marketing research, credit scoring, m
| Parameter | Type | Required | Notes |
|---|---|---|---|
| query | string | yes | What to look for, in plain words, e.g. "staggered difference-in-differences with never-treated controls". |
| source | string | no | Limit to one work: data_analysis (A Guide on Data Analysis); causalverse (causalverse: The All-in-One Causal Inference Toolkit); credit_score (Credit Scoring: Theory, Methods, and Practice); marketing |
| language | string | no | Prefer sections with code in this language. |
| limit | integer | no | Number of results (default 8). |
Read 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.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| id | string | yes | Section id, e.g. "data_analysis:sec-regression-discontinuity". |
Recommend 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 observations are needed (power and sample size), how to handle panel, time-series, survey, text, or survival data, and how to b
| Parameter | Type | Required | Notes |
|---|---|---|---|
| question | string | yes | The research question and setting, e.g. "effect of a minimum wage increase that some states adopted in different years on teen employment". |
| language | string | no | Only list packages for this language. |
| limit | integer | no | Number of methods (default 3). |
Get 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 explanation of the method. Results can be restricted to one language or one work. Returns code blocks with the section they c
| Parameter | Type | Required | Notes |
|---|---|---|---|
| topic | string | yes | The task, e.g. "Callaway and Sant'Anna group-time ATT", "rdrobust bandwidth", "WoE binning scorecard". |
| language | string | no | Programming language of the code: r, python, or julia. |
| source | string | no | Limit to one work: data_analysis (A Guide on Data Analysis); causalverse (causalverse: The All-in-One Causal Inference Toolkit); credit_score (Credit Scoring: Theory, Methods, and Practice); marketing |
| limit | integer | no | Number of sections to return code from (default 4). |
Format 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 the library.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| ids | array | no | Section ids, or source ids: data_analysis, causalverse, credit_score, marketing_research, ai_in_action, advanced_data_analysis, tidy_finance_vn, tidy_finance_vn_vi, mlpy, publications. |
| style | string | no | Citation style (default apa). |
List 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 one entry per work.
No parameter schema on file.
- Every tool — any call limit is its publisher’s, not ours
- No card, and mcprush charges nothing for it
- Runs at its publisher’s own address — this marketplace is not in the path
- Nothing to cap, because mcprush bills nothing
What counts against your monthly calls
| Tool | Unit | Calls used | Out of the allowance |
|---|
Nothing here is billable: mcprush charges nothing to install Research Methods Library or to call it, at any volume.
Two independent axes, because powerful and malicious are different questions. The grade is threat only. The capability level is blast radius, and it is never a penalty on the grade — it is priced as one subtract-only term in the score, where you can see it.
| Term | Level | What it prices | Points |
|---|---|---|---|
| capability-exposure | minimal | capability blast radius (minimal) — client exposure if the model is manipulated | −0 |
| coverage-honesty | manifest | inspection depth (manifest) — how much of the target the scan could see | −4 |
What the scan could actually read
A grade is only as meaningful as its coverage, so the scanner publishes its own depth before it publishes its result.
The scan read each tool’s name, description, input schema and annotations exactly as the server listed them the last time it answered us; no code was reviewed. We ask the server again about once a month, and a list that changed is graded again.
The implementation source was not read — this reflects the declared tool metadata only.
Capability — what it could do if the model were manipulated
Tags derived from each tool’s schema and the implementation, not from what the tool calls itself. minimal is the level these add up to.
| Tool | Capability tags | Why the tag was assigned |
|---|---|---|
| search | no tags | |
| fetch | untrusted-input | untrusted-input: keyword "fetch" |
| choose_method | no tags | |
| get_code | no tags | |
| cite | no tags | |
| list_sources | no tags |
Toxic-flow graph
The lethal trifecta, checked as a graph rather than as a checklist: untrusted input, a sensitive source and an external sink have to meet before there is a path worth worrying about.
The public result for this release does not print the flow graph, so there is nothing to show here. That is not the same as "no paths were found": what the scan did read is above, under coverage.
Supply chain and provenance
This is the first scan of this surface here, so there is nothing yet to compare it against.
Every result on this tab comes from one deterministic pass over the published package — offline, rule by rule, and auditable line by line above. Same methodology version, same bytes, same score.
Release history
This is an address its publisher runs: which release it serves is theirs to choose, so there is nothing here to pin. The history below is for reading; the current release on file is 0.1.1.
No release note was published with this version.
One review per account, from a signed-in account that does not publish this listing. Nothing else is asked — you can say what you think before you install it. Publishers can reply once per review, and a review can be edited or deleted by whoever wrote it.
Any signed-in account that does not publish Research Methods Library can review it, once — before installing it or after. A review from an account that has installed it is marked as one.
Nobody has reviewed this listing. The rating on the card is the mean of the reviews written here and nothing else, so there is no rating until somebody writes the first — which takes a signed-in account that does not publish it, and nothing else.