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

Compresses spreadsheets into compact encodings, enables Q&A on sheet content, and extracts structured order data via LLM calls.

Provides a secure FastMCP gateway to Google Analytics Admin and Data APIs, deployable on Coolify with OAuth protection and encrypted storage.

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.

Read-only MCP server for extracting data across multiple CallTrackingMetrics sub-accounts using a single parent API key. Enables cross-account call data, reports, numbers, contacts, and configuration analysis for resellers and agencies via Claude.

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.

MCP server enabling AI agents to read, write, and manage Google Sheets, including sheet manipulation, row/column operations, dropdowns, checkboxes, and conditional formatting.

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 LLMs to interact with Google Analytics Admin and Data APIs to retrieve account summaries, property details, and custom metrics. It allows users to run core and real-time reports to analyze website performance and configuration via natural language.

Enables comprehensive integration with Google Analytics 4, allowing users to read analytics reports and send custom events through both the Data API and Measurement Protocol v2.

An MCP server implementation for accessing Google Analytics 4 (GA4) data, built using the Model Context Protocol TypeScript SDK.

A Model Context Protocol server that enables searching Google Patents information via the SerpApi Google Patents API, allowing users to query patent data with various filters and sorting options.

Enables LLMs to interact with Google Analytics 4 data through the Google Analytics Data API, supporting standard reports, real-time data, and metadata retrieval.

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 an interface to access Google Analytics Data API through Model Context Protocol (MCP), allowing users to retrieve reports and realtime data from Google Analytics 4 properties.

Syncs Google Search Console performance data into a local ClickHouse database and exposes prepared SEO analysis tools to AI agents. Enables diagnosing traffic drops, finding striking-distance keywords, detecting cannibalization, auditing indexing, and generating weekly SEO reports through natural language.

Enables AI agents to interact with Google Analytics 4 data, providing tools for historical reporting, real-time activity monitoring, and property management. It supports secure service account authentication to access metrics like traffic summaries, user acquisition, and custom dimensions.

Enables natural language-powered ETL workflows using Airflow, AWS Glue, Athena, and S3, allowing LLM agents to control and monitor data infrastructure.

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.

Enables AI agents and MCP-compliant clients to extract visual data from charts and graphs into structured markdown tables using deterministic, zero-dependency Python.

Exposes a synthetic issue tracker and pipeline warehouse as callable tools so an agent can answer operational questions about tickets, pipeline health, runs, incidents, and governed metrics with every claim cited to the exact tool call it came from. All writes are proposal-only, requiring human approval through a gated apply path that logs each step for audit.