"Creating MCP Servers Using Open Data APIs" matching MCP servers:

An MCP Server that enables interaction with Google's Data Labeling API, allowing users to manage datasets, annotations, and labeling tasks through natural language commands.

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.

Enables loading and statistical analysis of .xlsx and .csv files with visualization capabilities using matplotlib and plotly to generate various graphs and charts.

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.

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.

Enables AI assistants to query and interact with Treasure Data through a secure interface, supporting SQL queries, database exploration, CDP segment management, and workflow monitoring across multiple regions.

A governed MCP server enabling LLM agents to query BigQuery, inspect GCS, trigger Airflow DAGs, and run data-quality checks with built-in security guardrails like allow-lists, cost ceilings, and audit trails.

Provides a unified interface to access UNHCR's open data across statistics, RDF, and IATI MCP servers, enabling aggregated queries, cross-domain analytics, and dataset discovery.

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.

An MCP server that connects AI agents to cloud-native geospatial data via STAC metadata and DuckDB with H3 spatial indexing, enabling zero-configuration SQL queries on terabyte-scale datasets over S3.

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.

Connects AI coding assistants like Claude Code, Cursor, and Windsurf to enterprise data sources (databases, files, APIs, etc.) via a single binary, with 45+ connector categories and built-in memory tools.

Enables fetching market and options data including OHLCV prices, option chains, Greeks, and corporate events through a pluggable FastAPI service. Supports creating aligned training datasets for financial analysis and uses yfinance by default with support for custom data providers.

Middleware that converts existing APIs/DBs into MCP tools with secure credential injection, data scoping, and immutable audit logs.

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.

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

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.