"Polars" matching MCP tools:

• pivot_tableA

  Vibe Math MCP

  Summarize tabular data by creating pivot tables: choose row and column indices, select a value column, and apply aggregation (sum, mean, count, min, max) to reveal patterns and relationships.

  MIT

• get_scan_resultA

  polaris-audit

  Retrieve website audit results for privacy, security, accessibility, and performance issues using a scan token. Get scores, grades, and actionable fix instructions.

  MIT

• audit_urlA

  polaris-audit

  Submit a website URL for a free audit scan that analyzes privacy, security, accessibility, and performance issues, providing actionable fix instructions.

  MIT

• statisticsA

  Vibe Math MCP

  Compute descriptive statistics, quartiles, and IQR-based outlier detection for numerical data. Obtain count, mean, standard deviation, min, max, median, Q1, Q2, Q3, IQR, and outlier values. Select analysis types as needed.

  MIT

• get_public_resultA

  polaris-audit

  Fetch publicly shared website audit reports to view privacy, security, accessibility, and performance scores with key findings summaries.

  MIT

• correlationA

  Vibe Math MCP

  Calculate correlation matrices between multiple variables using Pearson's r or Spearman's rank. Choose matrix or pairwise output to analyze linear or monotonic relationships.

  MIT

• dataA

  squire

  Execute Python scripts for dataset processing in disposable remote runtimes with pandas, polars, and pyarrow. Upload inputs and download generated artifacts.

• array_statisticsA

  Vibe Math MCP

  Calculate statistical measures (mean, median, std, min, max, sum) on arrays. Supports column-wise, row-wise, or overall computations using Polars.

  MIT

• array_operationsB

  Vibe Math MCP

  Perform element-wise operations on 2D arrays including add, subtract, multiply, divide, and power, supporting array-to-array and array-to-scalar computations.

  MIT

• get_compute_ready_stream

  Valuein — SEC EDGAR Fundamentals

  STATUS: pending — direct R2 Parquet access is in private beta (ETA 2026-Q3). Calls return 501 FEATURE_NOT_AVAILABLE today. When live: returns a pre-signed Cloudflare R2 URL for bulk Parquet access that can be piped into Python/DuckDB/Polars for high-throughput computation that exceeds the MCP context window. Datasets: fact (per-entity partition — requires ticker), ratio (all computed ratios), valuation (DCF inputs), filing (SEC filing metadata), references (company universe), index_membership (historical index composition). URL would expire in 15 minutes. TODAY use the Python SDK (`pip install valuein-sdk`) for the same data via DuckDB.

  Connector