"Informational MCP Servers with Croissant Dataset Format Support" matching MCP servers:

Validates MLCommons Croissant dataset metadata (JSON-LD) for schema compliance, as a stateless MCP server.

Enables dataset curation by removing duplicate entries, rebalancing class distributions, and detecting and removing poisoned or malicious entries.

An MCP server that searches HuggingFace/Kaggle for datasets, detects their domain, and generates a matching preprocessing script. It turns natural-language dataset queries into runnable, domain-aware preprocessing pipelines.

Enables AI agents to import datasets from Hugging Face or Parquet, CSV, JSON, JSONL and DuckDB sources, map them onto a user-defined schema with per-row metadata, then preview, sample and write the converted rows into DuckDB files. Also exposes schema management, split lookup and target listing so an entire conversion pipeline can run in one call.

Enables automated dataset processing and onboarding using Google Drive integration. Provides metadata extraction, data quality assessment, and contract generation for CSV/Excel files through natural language interactions.

An MCP server that enables advanced CSV analysis and data visualization using Google's Gemini AI and Plotly. It allows users to perform exploratory data analysis, generate interactive charts, and conduct complex reasoning on tabular data.

Enables AI to interact with Microsoft Access (.mdb, .accdb) and SQLite 3 databases, including read-only support for Access 97 databases. Supports executing SQL queries, importing/export data from CSV and Excel files, and storing notes about database files.

Provides MCP tools for scanning, redacting, and packaging dataset/model directories for public release, leveraging Presidio for PII detection and generating Hugging Face cards and EU AI Act training-data summaries.

Superhuman data-driven science. Allows agents to upload any tabular dataset, specify a target column, and get validated predictive patterns (with p-values, effect sizes, and context from literature) that surface feature interactions and subgroup effects you'd otherwise miss. Many discoveries already made, free for open data!

Enables users to convert a vendor partner directory (such as PartnerPage or the Shopify Partner Directory) or a trade body member list into one company row per listing, each carrying website, domain, tier, tags, and location for Clay-ready output. It runs the extraction on Apify, returning dataset rows for up to 20 directory URLs with optional deduping, detail enrichment, and a cost cap.

Enables looking up mobile phone numbers for a list of contacts by chaining your own Prospeo, Lusha, ContactOut, and FullEnrich keys until a provider returns a number. Returns one row per contact with the number in E.164 format, line type, country, a Do Not Call flag where reported, and the provider credits spent.

Parses NACHA/ACH files into structured JSON and summaries, performing structural and arithmetic validation with IAT support, enabling automated file inspection and validation through MCP clients.

A simple and efficient MCP server that provides Base64 encoding and decoding functionality for both text and images with support for Data URL format.

Enables AI agents to read and work with Wildberries, Ozon, and Yandex Market seller accounts through typed tools, multi-account support, unified data schemas, rate limiting, audit, and encrypted credential storage.

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

Enables SQL lineage analysis, including table-level and column-level lineage, field-level tracing, and support for multiple SQL dialects via sqlglot.

A Model Context Protocol server that lets LLM clients answer business questions in natural language over a Databricks dataset without writing SQL by hand.

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

A Model Context Protocol server that lets you fetch Microsoft Clarity analytics data through Claude for Desktop or other MCP-compatible clients, with support for filtering by dimensions and retrieving various metrics.

Enables users to query a governed data catalog for dataset ownership, contracts, columns, classifications, LF-tag validity, and whether tag-based grants reach a dataset or its columns, without returning any data rows.

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

Enables deterministic aggregation, BM25 keyword search, and report generation over a large IT ticket-history dataset through MCP tools, prompts, and client-model sampling.

Enables scientists and their agents to build type-checked, reproducible, interoperable analysis workflows over stamped data along arbitrary parametric axes, with content-addressed artifacts, provenance, dataset pipelines, and session-aware statistics.

Converts JSON data to TOON (Token-Oriented Object Notation) format and back, reducing token usage by 30-60% for more efficient LLM applications.

An MCP server for dataset exploration and analysis, enabling LLM clients to perform summary, correlation, distribution, missing value analysis, data cleaning, and statistical tests directly on CSV files.

Enables AI agents to safely describe, query, and compute metrics across SQL databases using open-format semantic models, custom context, and skills, with read-only and dialect-checked execution.

A server that provides tools and utilities to support the implementation of Jij Modeling, featuring easy configuration and an extensible architecture for custom modeling workflows.

A Model Context Protocol (MCP) server that provides tools for reading Excel (xlsx) files, enabling extraction of data from entire workbooks or specific sheets with results returned in structured JSON format.

Enables MCP clients to inspect, validate, transform, and query CityJSON models, with support for conversion, persistence, and 3D geometry validation.

A Model Context Protocol server that enables working with Building Information Modeling (BIM) files by converting IFC files to fragment format and querying BIM data by category.