Stats Explorer

Stats Explorer MCP

An MCP server with 18 statistics and analytics tools an AI assistant can call instead of guessing numbers, on data files of any size:

• Tests: t-tests, z-tests, ANOVA (with a Tukey HSD post-hoc that names the groups that differ), ANCOVA, MANOVA, chi-square, Fisher's exact, binomial and correlation.
• A/B testing: A/B and A/B/n readouts for conversion rates and revenue-type metrics (lift with intervals, sample ratio mismatch check, Holm-adjusted comparisons, Bayesian probability to beat the control, segment breakdowns), and sample-size planning.
• Analytics: totals, averages and counts by category (top N), and "what drives X?" rankings across every column.
• Helpers: descriptive stats, confidence intervals, power analysis, a "which test should I use?" tool, and a data-file inspector.

The tools can read a developer's CSV, TSV, Excel or Parquet files by column name, so large datasets never get pasted into the chat. Each result includes:

• the effect size and confidence interval,
• a plain-English interpretation,
• warnings when an assumption looks shaky.

On top of that:

• Correct. 43 reference cases are checked against SciPy and statsmodels on every commit, to at least 6 significant figures.
• Guided by default. The agent first decides whether your request needs a hypothesis test or just exploration. Hypothesis tests follow the six steps of Stats Explorer's *Bring it all together* guide, in order.
• You stay in control. Every column, group, chart type and report section the agent proposes is shown to you to confirm or change before anything runs.
• Private. Runs locally over stdio. It makes no network calls and needs no API key (unless you turn on Jev's enforce mode, below). Data files are read only from your workspace folders.
• Checked by Jev, if you want. Connect Jev, TypeSafe's fast judgment model, alongside it, and Jev independently checks the test plan and the assistant's written conclusions against the computed results. You can run it without an orchestrator, enforced by Stats Explorer itself, or under a production orchestrator that signs every decision.

The engine, the file import and the six-step guide are shared with the Stats Explorer app, so results match the app exactly.

Connect it (pick your assistant)

GitHub Copilot in VS Code: about 1 minute, nothing else to install

1. In VS Code, open Extensions (Ctrl+Shift+X / Cmd+Shift+X), search Stats Explorer MCP, click Install.
2. Open Copilot Chat and switch the mode dropdown to Agent.
3. Click the tools icon in the chat box and check that Stats Explorer is listed and ticked.
4. Open the folder that holds your data and ask a question (see Example questions).

The extension registers the server itself, using VS Code's built-in runtime, so you don't need Node.js or an mcp.json file. Confirmations appear as forms you can edit.

Claude Code (terminal or the Claude Code panel in VS Code): about 2 minutes

You need Node.js 22 or later (24 LTS recommended). In a terminal, run this once:

claude mcp add -s user stats-explorer -e STATS_EXPLORER_CONFIRM_VIA=chat -- npx -y stats-explorer-mcp

claude mcp list

claude mcp list should show stats-explorer … ✓ Connected. Then start a new Claude session, because servers are loaded when a session starts. In VS Code: Ctrl+Shift+P → Developer: Reload Window, then New session. Type /mcp in the chat to see the servers the session has.

• -s user makes it available in every folder (without it, only in the folder where you ran the command).
• STATS_EXPLORER_CONFIRM_VIA=chat makes confirmations appear as messages in the chat, which you answer by replying. Claude Code doesn't always display form-style prompts.
• If you have the VS Code extension installed, Stats Explorer: Copy Setup Command for Claude Code copies this command for you.

Claude Desktop, Cursor, Windsurf, Cline and other MCP clients

Add this to the client's MCP config (claude_desktop_config.json, .cursor/mcp.json, and so on), then restart the client:

{

"mcpServers": { "stats-explorer": { "command": "npx", "args": ["-y", "stats-explorer-mcp"], "env": { "STATS_EXPLORER_ROOTS": "/path/to/your/data", "STATS_EXPLORER_CONFIRM_VIA": "chat" } } } }

Requires Node.js 22 or later. STATS_EXPLORER_ROOTS is the folder (or folders) the tools may read; see Data files.

Example questions

Name the file in your message (or attach it); the assistant passes it to the tools and never pastes the data into the chat.

• *What's in sales.csv?*
• *Total revenue by state in sales.csv, top 10.* (group_summary)
• *What drives profit in sales.csv?* (find_relationships, then follow-ups)
• *Show the distribution of order value and a box plot by segment.*
• *Does average profit differ between the Consumer and Business segments? Is it significant?* (six-step hypothesis test)
• *Did the new checkout page (variant B) increase conversion in experiment.csv? Break it down by device.* (ab_test)
• *How many visitors do I need to detect a 10% lift on a 4% conversion rate, with 3,000 visitors a day?* (ab_test_plan)
• *Does revenue differ between the three regions, and which ones?* (ANOVA + Tukey HSD)
• *Make an HTML report of what we found and save it as findings.html.*

The analyze, explore_data and hypothesis_test prompts (slash commands in VS Code and Claude) start the same flows.

Working with Jev (optional)

When both Stats Explorer and a Jev MCP server are connected to Claude or Copilot, they split the work. Stats Explorer computes every number, and Jev checks two things before you see a result:

• The test plan: is this the right test, are the hypotheses right, are these the right columns?
• The written conclusions: does every number match, is "significant" stated correctly, are there claims of cause the analysis can't support?

Stats Explorer also runs its own number and significance checks on every claim. Only claims that pass go into reports, and each report lists every check under Independent checks.

Quick start with Claude Code (no orchestrator):

claude mcp add -s user jev -e TYPESAFE_API_KEY=YOUR_KEY -- npx -y @jkudish/jev-mcp

claude mcp add -s user stats-explorer -e STATS_EXPLORER_JEV=cooperate -e STATS_EXPLORER_CONFIRM_VIA=chat -- npx -y stats-explorer-mcp npx -y stats-explorer-mcp init-jev # adds routing rules to CLAUDE.md and .github/copilot-instructions.md

Any Jev MCP server works (@jkudish/jev-mcp, jev-mcp, typesafe-mcp, …): the packets come in the shapes their tools take. In VS Code, set Stats Explorer › Jev: Mode. See [docs/JEV.md](docs/JEV.md) for every mode and setting, the signed-approval format (with JavaScript and Python), what is sent to Jev, and the runnable orchestrator example in examples/orchestrator/.

How it works (default)

1. The agent classifies your request

Every analysis starts with start_analysis, where the agent picks a mode:

If it's unclear, the agent is instructed to ask you. Nothing else runs until start_analysis has been called.

2. Hypothesis tests follow the six steps, in order

Calling a step out of order is refused with a message that names the next step. Only steps 4 and 6 can be skipped, and only with a reason that appears in the report. If step 2 shows the chosen test doesn't fit, re-stating the plan in step 1 is allowed and restarts the later steps. The app's guide calls this a principled revision, not p-hacking.

3. You confirm every selection

When the agent proposes columns, groups, a chart type or report sections:

• Clients that support MCP forms (elicitation), such as VS Code, show you a form with the agent's choices pre-filled as dropdowns and checkboxes. Change anything, then accept or decline. Declining runs nothing.
• Other clients get a CONFIRMATION NEEDED response listing the proposal, the alternatives and a one-time token. The agent is instructed to show you the choices and call again with the token only after you agree. A token only works for the exact selection it was issued for, so a changed selection is proposed again.

A selection you've confirmed isn't asked about twice in the same session.

4. Charts and reports

• create_visualization: histogram, box plot, scatter (with least-squares line), bar (mean or count by category), line, and pie. These are the app's chart types. Returns an accessible SVG (light and dark mode) and can save it as .svg.
• build_report: only when you ask for one, and containing only the sections you tick. A completed hypothesis test becomes a write-up in the app's format: the question, the hypotheses, how it was tested (with steps 2–4), what was found, the verdict and base rates. Explorations never get a hypothesis section. Saved as HTML (default) or Markdown in your workspace; existing files are not overwritten unless you say so.

![An exploration report with summary statistics, a confidence interval and a histogram](https://raw.githubusercontent.com/meador793/stats-explorer