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"How to create documents in Confluence" matching MCP connectors:

Matching Connector Tools:

  • AMZScout Skill + MCP gives AI agents live access to real Amazon marketplace data across 14 Amazon marketplaces. Analyze any ASIN, validate product ideas, research niches, compare competitors, discover profitable keywords, and build data-driven PPC strategies using trusted Amazon insights instead of AI assumptions. Works with Claude, ChatGPT, Cursor, and any other MCP-compatible AI client. To connect, you'll need an AMZScout API plan and authorize your account. Get access and view pricing here: https://learn.amzscout.net/amazon-product-api-for-ai-agents

  • Build, validate, deploy — HTTP APIs, cron jobs, webhooks and MCP tools — from your AI client. Air Pipe MCP token as a bearer credential, e.g. 'Authorization: Bearer <token>'. Create one at https://app.airpipe.io/

  • Find novel, statistically validated patterns in tabular data — hypothesis-free.

  • Auto-discover validation rules from data — scan, profile, health-score. No rules to write.

  • Executes SQL in a real ephemeral database: rows, typed errors with suggestions, plans, diffs.

  • Resolve Japanese food names to nutrition facts. All 2,538 foods from Japan's official tables.

  • AI access to Quadratic spreadsheets: open files, run Python/SQL, query connected databases.

  • It connects with Smart Data models database with more than 1000 open licensed data models and helps you to create applications and systems interoperable with existing standards or real applications

  • Connect your AI to your Well financial data - invoices, companies, contacts.

  • Create, manage, and query your Google Cloud SQL resources.

  • A unified biomedical graph database that integrates 50+ primary data sources — genes, proteins, compounds, diseases, pathways, and clinical data — into a single queryable graph with billions of cross-reference edges. Its native MCP server gives LLMs direct access to structured, authoritative biomedical data, complementing their reasoning with reliable identifiers and up-to-date database content.

  • Provides tools to manage Memorystore for Valkey instances and backups.

  • The BigQuery remote MCP server is a fully managed service that uses the Model Context Protocol to connect AI applications and LLMs to BigQuery data sources. It provides secure, standardized tools for AI agents to list datasets and tables, retrieve schemas, generate and execute SQL queries through natural language, and analyze data—enabling direct access to enterprise analytics data without requiring manual SQL coding.

  • Analytical memory for AI agents: a real Postgres queried in plain English over MCP. One command.

  • Connect your AI to any database — PostgreSQL, MySQL, or SQL Server — in seconds.

  • Managed MCP gateway for PostgreSQL. Connect Cursor, Claude Desktop, VS Code, and Windsurf to your database with per-table permissions, encrypted credentials, and a full query audit trail. OAuth 2.0 authentication, free tier available.

  • Read, create, update and delete records; inspect objects, fields and schema in your Knack database.

  • Backend for vibe coders. Connect Butterbase to any MCP-compatible AI coding tool and provision a full backend automatically — database, authentication, file storage, edge functions, and real-time — from a natural language prompt. No SQL, no configuration, no backend knowledge required. Free to start at butterbase.ai.

  • An MCP server for converting data between 16 formats including JSON, YAML, TOML, CSV, XML, Markdown, HTML, Excel, PDF, and more. Supports single transforms, batch fan-out to multiple targets in one call, and JSON reshaping with dot-notation path mapping. 240 conversion pairs, zero config.

  • Chrysai provides a hosted MCP server for AI-driven data operations. After connecting an MCP client to the endpoint, you can use MCP tools such as create_app, list_apps, read_data, write_data, update_data, delete_data, and update_app, plus schema resources, to manage persistent structured data through natural language.