"Finding or Accessing CSV Data" matching MCP servers:

Enables validating CSV structure, checking simple schemas, converting between CSV and JSON, sampling rows, and finding duplicate keys on local files. All processing stays local, so no user data is ever uploaded.

A spreadsheet and CSV analysis toolkit for AI agents that enables loading CSV files, filtering and querying data, computing statistics, creating aggregations, building pivot tables, and exporting chart-ready data using pandas.

A Windows-optimized server providing universal data analytics for JSON and CSV files through over 32 tools including schema discovery and interactive visualizations. It is specifically designed for seamless integration with Claude Desktop on Windows.

Enables searching and filtering over 1.5 million electronic components across JLCPCB, Mouser, and DigiKey using parametric queries and smart parsing. It supports finding alternative parts, accessing pinout data, and downloading KiCad footprints directly through AI coding assistants.

A fully autonomous patent data marketplace for AI agents, providing highly structured JSON datasets with strategic insights. Supports instant M2M transactions via ROSE on the Oasis Network.

Turn any CSV into a stunning interactive dashboard with one command — works as CLI, MCP server, or AI skill

Enables coding agents to read performance findings from sixty, get detailed evidence for each finding, and close or resolve them with descriptions, while also checking service telemetry and providing installation instructions.

Provides safe, deterministic inspection, transformation, validation, and diffing of structured data (JSON, CSV, YAML, Parquet) via schema-aware MCP tools.

Enables AI assistants to generate realistic, synthetic test data on demand, including valid PESELs, NIPs, addresses, and more across 27 EU countries, through two tools: list_generators and generate.

Exposes Semgrep as deterministic, rule-matching analysis tools over MCP so a code-review agent can scan only the lines changed in a diff, scan whole files on demand, and check analyzer availability, version, ruleset, and limits. Results are returned as compact per-finding lines with source snippets suitable as comment anchors, along with counts of suppressed out-of-diff matches.

Provides machine learning researchers with tools for creating publication-quality scientific visualizations, statistical plots, and 2D data representations. It streamlines the research workflow by enabling AI assistants to generate complex figures from CSV, JSON, or direct data inputs.

MCP server for Hydra ETL: lets AI assistants write declarative YAML ETL pipelines (CSV, Parquet, PostgreSQL, MySQL, MongoDB, APIs) and validate them before any data is read or written.

A Model Context Protocol server that extracts embedded data (such as i18n translations or key/value configurations) from TypeScript/JavaScript source code into structured JSON configuration files.

Provides AI agents with data validation, transformation, and normalization capabilities, including JSON schema validation, CSV processing, data normalization, text cleaning, and dataset merging.

The Excel to JSON MCP provides a standardized interface for converting Excel and CSV data into JSON format using the Model Context Protocol.

Provides UI architecture analysis for converting Figma designs or web pages into reusable UI code blocks with effort estimation in CSV format.

The JSON to Excel MCP provides a standardized interface for converting (1)JSON data (2)URL pointing to JSON files into CSV format

Provides tools for interacting with SQL Server databases, enabling users to retrieve paginated table data, inspect schemas, and count records. It features enforced pagination and secure configuration options to manage database operations efficiently through natural language.

An MCP server for interacting with SQL Server databases that enables schema inspection, record counting, and paginated data retrieval. It provides tools to explore table structures and fetch specific records while enforcing safety limits on data volume.

An MCP server that enables AI agents to retrieve detailed GitHub Pull Request information using git commit hashes, branch names, or PR numbers. It automatically detects repositories and extracts comprehensive PR data including descriptions, labels, and reviews via the GitHub CLI.