Execute pandas code in a restricted sandbox, optionally preloading a CSV/Excel file, and return the result as structured records.
MIT
519,972 tools. Updated 2026-09-06 08:15
"pandas" matching MCP tools:
- Execute pandas data analysis code securely with automatic safety checks and smart suggestions. Returns results or error messages.MIT
- Turn a project directory into a pandas data processing pipeline, generating code for data cleaning, transformation, and analysis.MIT
- Export collected OT data from local SQLite storage to CSV, SQLite, or Parquet files for analysis in Excel, SQL tools, or pandas/Spark.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
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
Matching MCP Connectors
Build, publish and read scored forms and quizzes where the score picks the next screen.
- Stats CompassOAuth
50+ pandas-powered tools for data loading, cleaning, visualization, and ML workflows
- 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
- 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
- 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
- Stream large query results to a CSV file instead of the reply, bypassing context limits and returning a path for analysis in R, DuckDB, or pandas.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