Execute pandas code in a restricted sandbox, optionally preloading a CSV/Excel file, and return the result as structured records.
MIT
457,387 tools. Updated 2026-08-14 10:50
"pandas" matching MCP tools:
- Execute pandas data analysis code securely with automatic safety checks and smart suggestions. Returns results or error messages.MIT
- Load time series data from pandas, files, SQL, or URLs into a data handle for forecasting. Choose synchronous or asynchronous execution.BSD 3-Clause
- Install the MNE-Python analysis backend on demand to enable all MNE tools without a restart. Select from ica, analysis, or full profiles.MIT
- Filter rows in a local .xlsx file using AND-combined predicates (eq, contains, gt, etc.). Server-side formula evaluation returns accurate matching rows as a markdown table.MIT
- Load FileMaker records into a named dataset for fast analytics. Fetch records once, store as pandas DataFrame, then run multiple analyses without extra database round trips.GPL 3.0
Matching MCP Servers
- AlicenseAqualityBmaintenanceEnables data analysis on CSV/Excel files using pandas. Supports profiling, column interpretation, sandboxed code execution, and interactive chart generation.4MIT
- AlicenseAqualityFmaintenanceEnables LLMs to safely execute pandas code for data analysis and generate interactive visualizations through the Model Context Protocol.445MIT
- Recover cell formatting (number formats, fonts, fills) discarded by pandas, enabling LLMs to interpret date serials, currency, and percentages correctly.MIT
- Count unique values in a spreadsheet column, sorted by frequency with percentage. Shows distribution of categorical data in a markdown table.MIT
- Analyze FileMaker datasets with groupby, aggregation, filtering, pivoting, and time-series resampling. Returns compact summary tables instead of raw records.GPL 3.0
- Identify merged cell regions in Excel workbooks with master values, ranges, and layout heuristics to recover visual structure lost in pandas reads.MIT
- Search code across your SourceGraph instance using text, patterns, or regular expressions. Filter by repository, file, language, and more for precise results.MIT
- Compute net totals across transaction types in a single call by summing signed sums of a quantity column, with per-component breakdown and warnings for unmatched conditions.MIT
- Export tracked ENCODE experiments as a CSV, TSV, or JSON table with metadata, publication counts, and PMIDs. Ideal for manuscripts, reports, and further literature analysis.AGPL 3.0
- Scans a CSV or Excel file to return the complete value distribution for specified columns, including dtype, null counts, and frequency counts sorted by most common.MIT
- Send input to an active process and receive its response. Ideal for interactive REPLs such as Python, Node.js, or shell sessions.MIT
- Check supported dataset formats and installed library versions for pandas, openpyxl, and pyreadstat.AGPL 3.0
- Group rows in a local .xlsx file by specified columns, then compute aggregations like sum, mean, count, or distinct count per group. Returns a markdown table of grouped results.MIT
- Reshape a flat table from a .xlsx file into a 2D matrix, aggregating values across index and columns. Choose from sum, mean, min, max, count, or count_distinct.MIT
- Download an Egnyte file's real binary to local disk. Returns the local file path for code access, supporting large files via streaming.Apache 2.0
- Generate interactive bar, line, or pie charts from pandas aggregated data, saving as self-contained HTML files.MIT