Safe Kaggle MCP vs Stata MCP

A side-by-side look at the Safe Kaggle MCP and Stata MCP MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.

Safe Kaggle MCP logoSafe Kaggle MCPData Science Tools · Local subprocess (stdio)Safety-first Kaggle MCP — confirm-gated destructive ops, submission budget, injection-fenced.53GoodAuth: not declaredStata MCP logoStata MCPData Science Tools · Local subprocess (stdio)Let LLM help you achieve your regression analysis with Stata57GoodAuth: no auth required

Verdict: choose Safe Kaggle MCP for data science tools work as a local process; choose Stata MCP for data science tools as a local process. You can also run both side by side in one mcpServers block.

Which MCP server should you choose?

Safe Kaggle MCP logoChoose Safe Kaggle MCP when

  • You need dedicated capabilities in the Data Science Tools domain.
  • You prefer a local stdio subprocess transport.
  • You want tools like kaggle_whoami, kaggle_status, kaggle_audit_log.
Explore Safe Kaggle MCP

Stata MCP logoChoose Stata MCP when

  • You need dedicated capabilities in the Data Science Tools domain.
  • You prefer a local stdio subprocess transport.
  • Its auth model fits you: No auth required.
  • You want tools like stata_do, get_data_info, help.
Explore Stata MCP

Feature & specification comparison

Rows where the two servers differ are marked.

SpecSafe Kaggle MCP logoSafe Kaggle MCPStata MCP logoStata MCP
CategoryData Science ToolsData Science Tools
Quality signal53/100 · Good57/100 · Good
Install commandConfirmedConfirmed
TransportLocal subprocess (stdio)Local subprocess (stdio)
AuthNot declaredNo auth required
PricingNot declaredFree
Required env varsNone listedNone listed
Verified ownerCommunity listingCommunity listing
GitHub stars0269
Directory activity 1 views 0 installs 0 upvotes 7 views 0 installs 0 upvotes
Tools414

Tools & capabilities

Safe Kaggle MCP tools 41

  • kaggle_whoamiReturn the authenticated Kaggle username and credential source. Does not transmit or echo the API key. Use to confirm the server resolved credentials for the expected account.
  • kaggle_statusHealth check: credential validity, current per-competition submission budgets for this session, enabled safety switches, and the work-dir root.
  • kaggle_audit_logReturn the session's append-only ledger of mutating actions (submit / create / version / delete) with timestamps and the submission budget at the time — every field redacted. Makes the safety machinery inspectable, which no other Kaggle MCP can offer (none track tokens or budgets).
  • kaggle_list_competitionsList/triage competitions as a compact ranked table (title, slug, prize, deadline, evaluation metric, category). Paginated. Read-only.
  • kaggle_competition_landscapePre-digested triage report of competitions: for each, the slug, prize, evaluation metric, deadline, and **days_left** — sorted by soonest deadline so you can decide what to enter at a glance. A single decision-ready artifact rather than raw endpoint output (which is what other Kaggle MCPs return).
  • kaggle_get_competitionFetch one competition's details and a truncated, untrusted-wrapped rules digest. `competition` is the BARE slug (e.g. 'titanic'). Read-only.
  • kaggle_competition_leaderboardPublic leaderboard capped to top-N (default 20) to protect context.
  • kaggle_leaderboard_trackSnapshot the public top-N and diff it against the LAST snapshot you took: per-team rank deltas, new entrants, biggest climbers, and (if your_team is given) your movement + who passed you. Kaggle has no historical-leaderboard endpoint, so this stateful local tracking is unique. PUBLIC leaderboard only; deltas are vs your previous snapshot, not an absolute time series.
  • kaggle_download_competition_filesDownload competition data into an isolated work dir (zip auto-extracted with a zip-slip guard). Returns local paths + metadata, NOT file contents. Requires the competition's rules accepted (403 otherwise).
  • kaggle_eda_competitionDownload a competition's data and return a pre-first-submission view: a compact pandas digest per CSV (shape/dtypes/missingness/correlations) PLUS a train-vs-test column diff that auto-infers the target — the orientation no other Kaggle MCP ships. Requires the competition rules accepted (403 else).
  • kaggle_competition_kickoffOne-call competition kickoff: fetch the metric/deadline/rules, download the data if rules are accepted (otherwise tell you to accept first), run a train/test EDA with target auto-detection, and return a baseline plan plus your remaining submission budget. Collapses the manual setup ritual into a single decision-ready bundle — no other Kaggle MCP does this.
  • kaggle_submission_best_scoreReduce raw submission history to the decision signal: best public score (respecting metric direction), first/best/latest trend, today's submission count, and any failure reasons — the 'is it worth iterating?' answer other servers leave as a raw list. Public scores only (private score is hidden until the deadline).
  • +29 more on the listing page

Stata MCP tools 4

  • stata_doExecute a Stata do-file and return the execution log. Accepts a do-file path, runs it via the configured Stata executable, and can optionally read log content only when return-code errors are detected. Use when you need to run Stata commands, perform regression or statistical analysis, or execute a do-file.
  • get_data_infoGet descriptive statistics and a data preview for a supported data file (.dta, .csv, .tsv, .psv, .xlsx, .xls, .sav, .zsav). Returns overview, variable details, and optional head rows filtered by requested variables. Use when you need to understand a dataset or have no prior knowledge of the data.
  • helpRetrieve documentation and usage information for a Stata command. Use when you need to understand a command's syntax, options, or troubleshoot errors before running it.
  • read_logRead a Stata log file (.log or .smcl) and return its content. Supports full, core, and dict output formats. Use `lines` to return only the first/last N lines.

Ready-to-paste client configs

Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.

Safe Kaggle MCP

mcpServers (Claude Desktop / Cursor)
{
  "mcpServers": {
    "safe-kaggle-mcp": {
      "command": "uvx",
      "args": [
        "--from",
        "safe-kaggle-mcp",
        "kaggle-mcp"
      ]
    }
  }
}

Stata MCP

mcpServers (Claude Desktop / Cursor)
{
  "mcpServers": {
    "stata-mcp": {
      "command": "uvx",
      "args": [
        "stata-mcp"
      ]
    }
  }
}

Frequently asked questions

Safe Kaggle MCP is categorized under Data Science Tools and uses a local stdio subprocess. Stata MCP belongs to Data Science Tools and uses a local stdio subprocess. Pick Safe Kaggle MCP for data science tools work and Stata MCP for data science tools.

Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.

Safe Kaggle MCP has no declared pricing — check the project's own site. Stata MCP is listed as free. Auth: no auth required. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.

Yes. MCP clients support multiple servers: add safe-kaggle-mcp and stata-mcp as separate keys in the same mcpServers object, and your assistant will call tools from either one.

On AllMCPs, Safe Kaggle MCP has a quality signal of 53/100 (Good) with 1 views, 0 installs and 0 GitHub stars. Stata MCP has 57/100 (Good) with 7 views, 0 installs and 269 GitHub stars.