"Using WhatsApp as the Main Platform for Customer Communication and Services" matching MCP servers:

Enables Claude to manage customers and support tickets through database-backed CRUD tools, contextual customer and knowledge resources, and a reusable ticket-triage prompt.

MCP server for securely connecting LLMs to customer data, providing customer profile retrieval, semantic search of interaction history, and exact financial summaries via SQL aggregation, with audit logging and prompt injection protection.

MCP server that gives AI agents read and write access to WhatsApp on macOS, reading local chat history offline and sending messages via pre-filled drafts with explicit user confirmation.

Lets you read WhatsApp history from the macOS app's own SQLite database without QR pairing or ban risk, with optional token-gated replying.

Enables LLM clients to read and search your own WhatsApp messages stored in a local SQLite database, captured live via a linked device.

An internal MCP server providing Database (SQL execution) and Server (Linux SSH/SFTP) skills with 11 tools, enabling remote execution, risk control, and full audit via Claude Code or other clients.

Enables seamless integration with WhatsApp through the Model Context Protocol, featuring multi-user support and Supabase cloud storage for persistent message history and media. Users can send messages, search chat records, and manage contacts across platforms like Claude Desktop, Cursor, and OpenClaw.

Enables natural-language Q&A over customer support ticket data. Provides tools for schema inspection, SQL-based ticket counts and grouping, and full-text search for customer wording without requiring API keys.

Enables AI models to interact with IBM FileNet Content Manager for document management, folder operations, metadata handling, search, and content extraction through a standardized interface.

Enables MCP hosts like ChatGPT and Claude to query data platform metadata, explore schemas and tables, inspect SQL explain plans, and monitor DAG and ETL status through standardized tools.

This read-only MCP Server allows you to connect to Azure Analysis Services data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).

Enables AI agents to interact with your personal WhatsApp account to search messages, list chats, and send messages. It stores all authentication and message data locally using SQLite for privacy and direct multi-device API connection.

Search the fastest-growing US horse boarding directory: 6,000 facilities and 3,800 trainers across 48 states, plus boarding price data by state.

Enables authenticated organization members to submit, query, and manage schema-validated structured records directly from ChatGPT, with membership requests and approval workflows gating access. All operations are tenant-isolated, permission-checked, and audited, so records are only reachable by approved members of the owning organization.

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

Exposes a governed dbt MetricFlow semantic layer to AI agents through three tools — list metrics, list dimensions and query metrics — so questions about federal contract spend are answered from defined metrics rather than raw tables. Guardrails reject undefined metrics, raw columns, SQL in filters and bulk exports, and no tool can execute SQL.

A safety-gated Python MCP server for Metabase that lets MCP clients and agents inspect Metabase, run governed queries, and create or maintain dashboards, cards/questions, collections, snippets, permissions, and other Metabase assets through the Metabase REST API.

MCP server for tracking user course progress, providing tools to retrieve and save course and stage progress for authenticated users with data persisted in SQL Server.

Read-only MCP server that proxies The Game Pensieve API over Streamable HTTP, letting AI assistants query a personal game collection via tools like search, filters, and summaries. Supports OAuth 2.1 enforcement and owner-scoped access.

Enables governed, read-only SQL analytics, hybrid RAG knowledge search, financial metric calculation, and database schema introspection through MCP, with role-based access control, audit logging, and AI observability.

Enables AI assistants like Cursor to manage customer support tickets in SQLite through MCP tools, supporting creation, retrieval, search, and updates via natural language.

This read-only MCP Server allows you to connect to SharePoint Excel Services data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out our MCP Server for SharePoint Excel Services (https://www.cdata.com/drivers/excelservices/download/mcp).

Enables LLM clients such as Cursor and Claude to discover and use generated REST services through MCP tools for create, update, and delete actions and MCP resources for list and get-by-id context. Services generated in one command are exposed simultaneously as REST endpoints and MCP tools and resources.

Enables AI assistants to interact with generated REST APIs by discovering and using CRUD tools and read-only data resources.

Enables AI assistants to discover and invoke CRUD tools and read-only resources over the Model Context Protocol for generated API services.

MCP server platform enabling agents to self-register and access geo MCP tools (read-only geo_entities) plus hello ping services via a public MCP endpoint.

Enables AI assistants to interact directly with generated REST APIs by exposing CRUD operations as MCP tools and read-only data as resources.

Exposes generated CRUD services to LLM clients over the Model Context Protocol, providing tools for create, update, and delete actions plus read-only resources for listing and fetching records by id. It lets assistants like Claude, ChatGPT, and Cursor discover and manipulate the same data served by the project's REST endpoints without any extra glue code.

Exposes every generated CRUD service to LLM clients such as Claude, ChatGPT, or Cursor through discoverable MCP tools for create, update, and list actions plus read-only resources, so models can query and manipulate data without raw HTTP calls. It runs alongside the same codebase's REST endpoints, letting clients and AI share one data layer.

Enables LLMs to discover and invoke generated CRUD operations as MCP tools and read data through MCP resources, alongside standard REST endpoints, using one codebase.