"A search engine for OECD statistics and data" matching MCP servers:

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.

Provides secure, agentic Excel analysis and calculation capabilities, enabling users to inspect workbook structure, perform statistical computations, write formulas, and generate outputs through whitelisted MCP tools with audit trails and backups.

Enables AI agents to discover official public data sources, inspect their metadata and endpoint parameters, and execute live queries through a unified response envelope with a 500 ms budget.

This server enables multi-agent conversations for interacting with Cirro's biological data platform through its OpenAPI interface, auto-generated using AG2's MCP builder.

Give your AI agent the entire China A-share market: 55 datasets of prices, financials, capital flows, corporate events and futures/options, stored locally and queryable with read-only SQL. Built point-in-time with delisted stocks kept, so backtests don't lie — no account, no API key.

Enables LLMs to profile and analyze tabular data files (CSV, Parquet, Excel, JSON) by extracting schema, statistics, data quality issues, and dtype suggestions, returning structured JSON.

Enables AI agents to discover, request access to, and query data products in Data Mesh Manager, enforcing governance policies while retrieving business data from platforms like Snowflake and Databricks.

50 tools and 400 functions for working with Excel/.xlsx spreadsheets — read/write, recalculate formulas, diff, repair broken references, and audit. Built for AI agents.

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.

Bootstrap MCP server for future data exploration and querying across multiple databases, currently only provides a hello_world tool with no actual data connectivity.

Enables read-only collection and comparison of Google Search Console and Bing Webmaster data, conservative URL protection, content auditing, reviewed-build verification, and private report generation through ten typed tools over stdio.

A Model Context Protocol server for data wrangling that provides standardized interfaces for data preprocessing, transformation, and analysis tasks including data aggregation and descriptive statistics.

A production-ready MCP server that provides comprehensive dbt project quality assessment for any GitHub repository, enabling AI agents to analyze dbt models, check metadata coverage, and map data lineage.

Lets MCP clients safely investigate live business data across multiple enterprise APIs by giving each subject a consistent scoped pseudonym and surfacing disagreements between sources as findings.

Enables AI agents to query structured data refined from unstructured web sources, including developer breaking changes, B2B pricing matrices, regulatory compliance, semantic search, and on-demand URL refinement.

Enables autonomous data quality inspection and repair workflows. It scans DuckDB warehouses for anomalies, generates and verifies fixes in a dry-run copy, then applies them after validation, with full audit logging.

A fast, safe MCP server for YNAB providing read-only budget access by default, with 28 tools for budgets, transactions, categories, payees, accounts, scheduled transactions, and server-computed analytics.

Enables MCP clients like Claude Desktop, Claude Code and Cursor to safely explore local CSV, Excel, Parquet and SQLite files by running guarded read-only DuckDB SQL over a sandboxed data directory. It also supports data profiling, chart generation as image content, and exporting query results, without ever allowing writes or access outside the configured folder.

MCP server for cleaning messy CSV data via a single clean_csv tool. Uses an agentic workflow with rule-based or LLM planners to transform data safely.

MCP server that connects AI assistants to Redash, enabling listing of assets, read-only query execution, dashboard inspection, and alert management through the Redash API.

Enables local offline machine learning workflows, including CSV profiling and cleaning, classifier and neural network training, hyperparameter optimization, evaluation metrics, confusion matrix plots, Streamlit dashboards, and HTML reports through MCP tools.

An open-source MCP server that aggregates Taiwan public data sources (data.gov.tw, TWSE, MOEA, CWA, etc.) and exposes them through the Model Context Protocol, enabling AI agents to query Taiwan data with a single configuration line.

An MCP server that gives AI assistants the ability to connect to, query, profile, and monitor data sources — turning any LLM into an interactive data engineering copilot.

Enables AI agents to index and search across SQLite databases and CSV files to discover table schemas and column metadata. It provides a unified MCP API for data source management and structural exploration through natural language.

Enables conversational analysis of CSV and Parquet files through natural language, providing statistics, summaries, data type information, and comprehensive multi-step data analysis.

Unified financial data access for US, A-share, HK stocks, and FX rates with automatic fallback across multiple data sources.

An MCP server with 66+ tools for data engineering, enabling AI assistants to interact with Kafka, databases, AWS, data pipelines, infrastructure, and more.

Enables an AI client to track a watch list of contacts and retrieve only what changed since the last run — departures, new employers, replacements, and new hires after a role closed — each row carrying match evidence, source dates, and ready-to-use outreach payloads. It runs the analysis on Apify using the caller's own provider keys, supports stored or caller-held state, and can push results to a signed webhook.

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

Enables access to SORACOM IoT platform data including Harvest sensor data, file storage, SoraCam camera footage/events, and SIM statistics through authenticated API calls.