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

Enables Claude to interact with WhatsApp on macOS through the Model Context Protocol. It allows reading messages, searching contacts, listing chats, and sending replies via natural conversation.

MCP server for 一沐日 beverage ordering, enabling users to query menus, place, list, update, delete, and analyze duplicate drink orders through natural language.

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

Enables querying eight keyless French and international public APIs for addresses, communes, holidays, school calendars, BODACC announcements, European VAT, and exchange rates through read-only MCP tools.

MCP server for interacting with the official Meta WhatsApp Business Platform/Cloud API, enabling sending messages, managing contacts, templates, and handling webhook callbacks.

A shared communication bus for multiple agents using NATS and MCP, enabling MCP clients to list, message, and query agents.

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.

Enables fetching weather forecasts for the USA via NWS API and for Israel via browser automation using Playwright.

Enables AI-driven customer support ticket processing, including classification, response generation, and automated email sending and Google Sheets logging.

Converts REST APIs into MCP tools using Gradio, demonstrated with a local IBM Granite model via Ollama. Enables LLM clients to interact with any REST API endpoint through the MCP protocol.

Fetches web pages and converts them to clean, readable markdown format by extracting main content while removing navigation, ads, and other non-essential elements to minimize token usage.

Run DeepSeek as a real sub-agent inside Claude Code / Codex CLI — not just a single LLM call. DeepSeek gets its own 7-tool agent loop (Read/Write/Edit/Bash/Glob/Grep/NotebookEdit) inside a sandboxed workspace.

Deterministic SNAP eligibility logic, exposed as auditable Model Context Protocol tools. An AI agent can read, reason, and orchestrate, but the eligibility determination itself is made by versioned, tested, cited code that a caseworker, an auditor, or a court can inspect.

Lets an AI assistant read and write business records in plain language, including looking up people, creating and updating tasks, logging time, and pulling utilization reports through a synthetic ops platform or an optional ClickUp adapter.

Manage WhatsApp Business templates and send messages from Claude, ChatGPT, Cursor, VS Code Copilot, or any MCP-compatible client — powered by the Meta Cloud API.

Enables AI assistants to read and send WhatsApp messages on Windows through the official WhatsApp Desktop application using Edge WebView2 CDP automation.

A read-only MCP server that enables AI agents to act as GCP platform engineers, allowing them to investigate incidents, take inventory, and find cost-optimization opportunities in Google Cloud projects without mutating any infrastructure.

Enables interaction with Adobe Commerce Catalog Services to retrieve product variants, price overrides, category permissions, and environment details via MCP.

Delegates work from MCP clients (like Claude Code) to the Codex CLI, allowing spawning of autonomous Codex subagents for tasks.

Provides a SQLite-backed MCP server that records agent memory as history, enabling explicit consolidation, source checks, revisions, narrative versions, and accountable forgetting.

Exposes product-style completion tools (OpenAI chat-completions-shaped and Anthropic messages-shaped) that are fulfilled by sampling the host agent's own LLM over MCP, so no model API keys are ever needed. Also offers a model listing endpoint aliasing the host's model.

Score your agent's governance (0-100), lint MCP tool definitions, and estimate costs across all major models. Free diagnostic tools with no API key needed. Expert skill files on governance, economics, and system architecture available with free tier.

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.

MCP server for WhatsApp via GREEN-API gateway, enabling agents to read chat history and send messages and files.

A Python-based MCP server that automates WhatsApp Web using Playwright to manage chats and messages. It enables users to list conversations, send messages, and retrieve history through a local browser automation interface.

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 structured learning with a verified loop: define goals as observable claims, learn through teach-lab-test-gate per claim, and get independently graded by an adversarial examiner to ensure genuine progress.

Lets a volunteer view their own Planning Center serving schedule, team members and contacts, order of service, and song attachments, and add, remove or skip blockout dates. It authenticates with the user's Personal Access Token so it only exposes what they can already see in Planning Center.

Enables sending messages, images, documents and more on WhatsApp directly from any MCP-compatible AI, with tools for chat management, groups, and webhooks.

Enables sending WhatsApp Business messages including text, media, interactive lists/buttons, and template management through the WhatsApp Business API via Nango integration.