"MCP server for reading and analyzing multi-sheet Google Spreadsheets" matching MCP servers:

Provides comprehensive control over Google Sheets to read, write, format, and manage spreadsheets directly through natural language. It includes extensive tools for data manipulation, conditional formatting, and cell protection, along with integrated PostgreSQL database query capabilities.

MCP server for storing and safely auto-filling tabular data. Enables AI agents to read objects, identify empty fields, collect values, and write them back without overwriting existing data.

Local Model Context Protocol server for reading and writing Google Sheets through Google Sheets API v4.

This MCP server enables safe local access to tables and spreadsheets for AI agents, providing typed tools for reading, previewing, and committing table changes through a permission-brokered interface.

Enables AI assistants to access, search, and analyze Google Spreadsheets through the Model Context Protocol. Supports both OAuth 2.0 for private sheets and API key authentication for public sheets, with tools for listing, reading, and searching spreadsheet data.

Enables full CRUD over Google Sheets through a service account, including reading tabs and rows, finding rows by column value, appending, updating, deleting rows, and managing tabs.

This MCP server enables AI assistants to automatically sync Google Sheets data to a local database and perform natural language queries and analysis on spreadsheet data.

Read-only MCP server for querying PostgreSQL, MySQL, and SQLite from AI agents — multi-database, safe by default.

A knowledge graph memory server using SQLite to provide persistent, isolated contexts for organizing information into searchable categories like work and personal projects. It features unique ID-based operations and a token-efficient serialization format designed to optimize interactions with LLMs.

Enables read-only SQL queries across several named MySQL/MariaDB/Aurora and Postgres databases from one place, with tools to list databases, tables, and describe schemas. It enforces safety by requiring non-local hosts to be read replicas and by running every statement in a rolled-back read-only transaction.

Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.

A Model Context Protocol (MCP) connector that allows AI agents to directly interact with Google Sheets, enabling creation, reading, and modification of spreadsheets through natural language.

Enables querying multiple SQL Server, Azure SQL, or Synapse databases through a single MCP interface, with support for read-only targets and various authentication methods.

A multi-purpose MCP server for AI-powered healthcare assistance that processes clinical data through configurable LLM providers. Maintains webhook endpoints for patient data processing with PostgreSQL logging and OpenAPI documentation.

An MCP server for managing multiple MySQL and MariaDB database connections simultaneously, allowing users to run SQL queries and manage schemas through AI-powered tools. It features dynamic connection management, persistent configuration, and granular tools for database, table, and index operations.

Official Google Analytics MCP Server

Enables AI coding agents to read, write, and query Google Sheets as a database through the Model Context Protocol.

Enables AI agents to query and explore multiple MonetDB column-store databases from one server, using named config labels or runtime credentials via dynamic connect. Provides SQL execution, schema/table inspection, health checks and EXPLAIN plans, with read-only defaults and per-project restriction flags like --label and --no-dynamic.

A Model Context Protocol server that connects to Google Cloud services, allowing users to query logs, interact with Spanner databases, and analyze Cloud Monitoring metrics through natural language interaction.

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