AnyQuery MCP

AnyQuery MCP transforms the way you interact with data by enabling SQL queries across 40+ different apps and services through a single interface. Instead of learning multiple APIs or switching between platforms, you write standard SQL to query GitHub repositories, Notion databases, Apple Notes, and dozens of other services.

The core innovation is treating every data source as a SQL table. Want to find all GitHub issues assigned to you across multiple repositories? SELECT * FROM githubissues WHERE assignee = 'yourusername'. Need to analyze your Apple Notes from the past month? SELECT title, content FROM applenotes WHERE createddate > '2026-02-01'. AnyQuery translates these SQL queries into the appropriate API calls.

Built on SQLite, AnyQuery provides a familiar MySQL-compatible interface that works with existing SQL tools and workflows. The plugin architecture allows extending support to new data sources - the community has contributed connectors for everything from financial APIs to social media platforms.

What makes AnyQuery particularly powerful in 2026 is Model Context Protocol (MCP) integration. LLMs like ChatGPT and Claude can connect directly to your AnyQuery instance, letting them query your actual data in real-time. Ask your AI assistant 'What are my top GitHub repositories by star count?' and it executes the SQL query against live data.

Competitive Advantages vs Alternatives

Unlike Zapier or Retool which require monthly subscriptions and cloud data processing, AnyQuery runs entirely locally with zero ongoing costs. While Informatica Cloud charges $50,000+/year for enterprise data integration, AnyQuery provides similar SQL-based querying capabilities for free. Unlike commercial platforms that lock you into proprietary query languages, AnyQuery uses standard SQL that any developer knows.

Compared to custom API integration scripts, AnyQuery eliminates the need to learn 40+ different API specifications. Where building a single GitHub + Notion integration might take 2-3 days of development, AnyQuery enables the same functionality with simple SQL queries in minutes.

Free vs. Paid: The Real Cost Analysis

AnyQuery's open-source model delivers substantial savings compared to commercial alternatives:

• Zapier Pro: $29.99/month (750 tasks) = $359.88/year
• Retool: $12/user/m $144/year per developer
• Microsoft Power Automate: $15/user/m $180/year
• For a 5-person team: $720-1,800/year in platform fees alone

• Informatica Cloud: $50,000+/year for basic plans
• Talend Data Management: $12,000+/user/year
• AWS Glue: $0.44/million objects + compute costs = $2,000-10,000/year typical usage

The tool runs locally as a single binary, ensuring data privacy. Unlike cloud-based integration platforms, your data never leaves your machine unless you explicitly query external APIs. This local-first approach addresses privacy concerns while providing powerful data access capabilities.

ROI Calculation: When AnyQuery Pays Off

• Current approach: Manual data export/import from 5 systems (4 hours/week)
• Developer hourly rate: $75/hour
• Annual manual cost: 4 hours × 52 weeks × $75 = $15,600
• AnyQuery setup time: 8 hours ($600 one-time)
• Annual savings: $15,000

• You need data from 3+ different APIs regularly
• Your team includes SQL-comfortable developers
• Privacy requirements prevent cloud data processing
• Budget constraints make paid tools ($360-1,800/year) too expensive

• You need visual workflow builders (use Zapier/Power Automate)
• Team lacks SQL skills and needs GUI interfaces (use Retool)
• You require complex write operations across multiple services
• Enterprise support SLAs are mandatory

Installation is straightforward - download the binary for your platform and start querying. No complex setup, no Docker containers, no cloud dependencies. The tool includes pre-built plugins for popular services and a plugin development framework for custom integrations.

AnyQuery excels at data exploration, reporting, and automation tasks where you need unified access to multiple data sources. Business analysts can create reports combining customer data from CRM systems with development metrics from GitHub. Researchers can analyze data across platforms without building custom integrations.