"Using MySQL's MySQL Connector/Python (mcp) with Cursor" matching MCP servers:

Enables LLMs to query live data from over 250+ sources via CData Python Connectors using natural language. Wraps connectors as a Model Context Protocol server.

Enables LLMs to query and analyze data across multiple MySQL databases with enterprise data federation, intelligent caching, cross-system analytics, and automated schema discovery for comprehensive business intelligence.

Provides AI agents with a single OAuth-protected MCP endpoint to query Wind financial data across stocks, funds, indexes, economics, and documents using 31 read-only tools, with serial API-key failover and fail-closed behavior.

MCP server that exposes NocoDB bases, tables, records, and linked records as tools, enabling Claude to read/write NocoDB data. Supports both stdio and HTTP for local and cloud deployments.

Enables exposing third-party data sources as Model Context Protocol servers with shared HTTP, rate limits, retries, caching, validation, and observability through thin per-source adapters.

MCP server that turns operator-authorized local or synthetic source records into auditable research briefs, with every finding linked to exact excerpts and hashes. Exposes a single build_research_brief tool over deterministic, no-network stdio.

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.

A small Python MCP server that lets Cursor's agent browse databases and tables, inspect columns, run read-only SQL, and register new sources or cache tables against a Zetaris instance. It is paired with a project rule that steers the agent to do all its data work through this server rather than going around it.

A resilient MCP server wrapping FiinQuant/FiinQuantX Python SDK for Claude Desktop and Cursor, providing market data, fundamental analysis, screening, and technical indicators via stdio with timeouts, error envelopes, and free-tier guards.

Enables AI assistants to query and optionally modify AJEMS workspaces, including apps, forms, and records, without requiring user login.

A cryptocurrency price service that provides real-time crypto pricing information through an MCP (Model Context Protocol) framework with CoinMarketCap API integration.

Enables ChatGPT to query and analyze Mixpanel analytics data in real-time. Provides live access to event segmentation and detailed analytics data from your Mixpanel project through natural language.

Enables AI agents to securely connect to and query Microsoft SQL Server databases with read-only access, schema discovery, and relationship mapping. Features advanced security protections, health monitoring, and bulk operations for production environments.

Enables AI assistants to load CSV datasets, compute summary statistics, filter rows, rank columns, and compute correlations through the Model Context Protocol.

Aggregates AI/ML/data-engineering developments from free public sources into a ranked, deduplicated, categorized feed for Claude.

MCP server providing seamless integration with Trino and Iceberg for advanced data exploration, querying, and table maintenance.

Enables MCP-capable agents to inspect, validate, search, and manage Apache Hop pipelines and workflows, with guarded editing, backup, and optional local or Hop Server execution.

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.

Read-only SQL across PostgreSQL, MySQL, S3-compatible buckets and folders of Parquet, CSV and JSON files — and one query can join across all of them, federated in-process by DuckDB. Sources are given as connection strings at startup, and no tool writes: they are absent rather than disabled.

Enables interaction with an Airbyte instance through natural language, supporting workspaces, sources, destinations, connections, jobs, logs, tags, streams, and connector definitions.

MCP server that exposes local Python scripts as tools for AI clients (e.g. Claude Desktop), enabling directory tree generation, Excel-to-text conversion, Python code extraction, and text file merging.

Enables querying, inserting, and managing unstructured data in RawTree via SQL, JSON ingestion, and log inspection through MCP clients like Claude Code, Cursor, and Claude Desktop.

An MCP server for AddressPenny address validation that enables users to validate postal addresses, bulk-clean address lists, and extract addresses from unstructured text through Claude Desktop, Cursor, and other MCP-compatible agents.

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.

An MCP server that provides KOSPI/KOSDAQ stock data using FastMCP.

MCP server for converting OEM energy telemetry payloads into ODS-E records and validating them via the odse Python package.

It gives AI agents a ranked, token-budgeted digest of what changed since their last cursor, with drill-down handles and cursor acknowledgement, read from a local database of file and SQL source changes. It enables agents to act on current business state without re-reading and diffing everything themselves.

Enables AI agents to discover and query data federated across MySQL/MariaDB, PostgreSQL, ClickHouse, S3 and Kafka with SQL, exposing tools to list databases, schemas, tables and connections, describe columns, search objects, inspect table statistics, run EXPLAIN, and execute arbitrary statements. It runs locally over stdio against a PostgreSQL-wire endpoint and returns structured results or SQLSTATE-coded errors.

Connects AI assistants to the Riveter API so users can run data enrichments, build datasets, scrape webpages, and manage monitors directly from Claude, ChatGPT, or Cursor.

Enables querying and mutating data across multiple sources (CSV, Google Sheets, SQLite, PostgreSQL, MySQL, MongoDB, Oracle) through a dynamic GraphQL API, with flexible filtering, batching, persisted queries, and dynamic source switching.