Un servidor de Protocolo de Contexto de Modelo (MCP) para Claude que se integra con la API de Evolution para la automatización de WhatsApp.
Este servidor MCP permite a Claude interactuar con WhatsApp a través de la API Evolution, habilitando capacidades como:
Administrar instancias de WhatsApp
Envío de varios tipos de mensajes
Trabajar con contactos y grupos
Configuración de webhooks y ajustes
Related MCP server: Evolution API MCP Server
mcp-evo-api/
├── src/
│ ├── tools/ # MCP tools implementation for Evolution API
│ ├── utils/ # Shared utilities, including Evolution API client
│ ├── main.ts # Server entry point
│ └── types.ts # Shared type definitions
├── scripts/ # Helper scripts
├── biome.json # Linting configuration
├── tsconfig.json # TypeScript configuration
├── docker-compose.yml # Docker Compose configuration
├── Dockerfile # Docker build configuration
└── package.json # Project dependenciesCree un archivo .env con sus credenciales de API de Evolution:
EVOLUTION_API_URL=https://your-evolution-api-server.com
EVOLUTION_API_KEY=your-api-key-hereAmbiente | Pasos | Dominio |
Desarrollo local | 1. Clonar e instalar. 2. Ejecutar en modo de desarrollo. |
|
Producción local | 1. Clonar e instalar 2. Compilar y ejecutar |
|
Docker Compose | Ejecutar con Docker Compose |
|
Estibador | Construir y ejecutar el contenedor |
|
Agregue esto a su archivo de configuración de Claude Desktop (normalmente ubicado en ~/Library/Application Support/Claude/claude_desktop_config.json ):
{
"mcpServers": {
"evo-api": {
"command": "node",
"args": [
"/path/to/your/mcp-evo-api/dist/main.js"
]
}
}
}Si utiliza la implementación de Docker:
{
"mcpServers": {
"evo-api": {
"url": "http://localhost:3000"
}
}
}Categoría | Implementado | Pendiente de implementación |
API principal | ✅ Obtener información✅ Crear instancia✅ Obtener instancias✅ Conectar instancia✅ Reiniciar instancia✅ Estado de conexión✅ Cerrar sesión en instancia✅ Eliminar instancia✅ Establecer presencia | ❌ Revisa WhatsApp |
Webhook y configuraciones | ✅ Establecer webhook✅ Buscar webhook✅ Establecer ajustes✅ Buscar ajustes | |
Mensajería | ✅ Enviar texto sin formato✅ Enviar estado✅ Enviar multimedia✅ Enviar audio de WhatsApp✅ Enviar sticker✅ Enviar ubicación✅ Enviar contacto✅ Enviar reacción✅ Enviar encuesta✅ Enviar lista✅ Enviar botones | ❌ Marcar mensaje como leído❌ Marcar mensaje como no leído❌ Archivar chat❌ Eliminar mensaje para todos❌ Actualizar mensaje❌ Enviar presencia (Ctrl de chat) |
Chat y contactos | ✅ Buscar contactos ✅ Buscar chats | ❌ Actualizar estado de bloqueo❌ Obtener URL de imagen de perfil❌ Obtener Base64❌ Buscar mensajes❌ Buscar mensaje de estado |
Grupos | ✅ Buscar grupo por JID✅ Obtener todos los grupos✅ Buscar miembros del grupo | ❌ Crear grupo❌ Actualizar imagen del grupo❌ Actualizar asunto del grupo❌ Actualizar descripción del grupo❌ Obtener código de invitación❌ Revocar código de invitación❌ Enviar invitación al grupo❌ Buscar grupo por código de invitación❌ Actualizar miembros del grupo❌ Actualizar configuración del grupo❌ Activar/desactivar efímero❌ Salir del grupo |
Configuración del perfil | ❌ Obtener perfil de empresa❌ Obtener perfil❌ Actualizar nombre de perfil❌ Actualizar estado de perfil❌ Actualizar foto de perfil❌ Eliminar foto de perfil❌ Obtener configuración de privacidad❌ Actualizar configuración de privacidad | |
Integraciones de bots | ❌ Integraciones de Typebot ❌ Integraciones de OpenAI ❌ Bot Evolution ❌ Bot Dify ❌ Bot Flowise | |
Otras integraciones | ❌ Chatwoot ❌ Websocket ❌ SQS ❌ RabbitMQ |
Para obtener más información, consulte la documentación de la API de Evolution .
Hello tool
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | The name of the person to greet |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Hello tool' reveals nothing about whether this is a read/write operation, what permissions might be required, what side effects occur, or what the response format looks like. The description fails to provide any behavioral context beyond the minimal implication from the name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
While technically concise with only two words, this represents under-specification rather than effective conciseness. The description doesn't contain enough information to be useful, and the single phrase doesn't earn its place by providing meaningful guidance to an AI agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there are no annotations and no output schema, the description should provide more complete context about what this tool does and what to expect. A single-parameter tool with 100% schema coverage could get by with minimal description, but 'Hello tool' fails to explain the basic purpose and behavior adequately for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already fully documents the single 'name' parameter. The description adds no additional parameter information beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no parameter information in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Hello tool' is essentially a tautology that restates the tool name without specifying what it does. It doesn't provide a clear verb+resource combination or explain the actual function. While the name suggests greeting functionality, the description fails to articulate this explicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides absolutely no guidance about when to use this tool, what context it's appropriate for, or any prerequisites. There are no sibling tools mentioned, but even basic usage context is completely missing from the description text.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
hello_toolScored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools, as there are no other tools to compare it against. The single tool's purpose is inherently distinct by default.
A single tool cannot demonstrate inconsistency, as there are no other tool names to compare it to. The naming pattern for 'hello_tool' (snake_case) is consistent within the set, albeit trivially so.
A single tool is generally too few for most server purposes, as it limits functionality and suggests an incomplete or trivial implementation. While it might be appropriate for a minimal 'hello world' server, it is inadequate for any substantive domain coverage.
With only one tool named 'hello_tool', it is impossible to infer a meaningful domain or assess coverage. There are obvious gaps, as no CRUD operations, lifecycle management, or typical API interactions are present, making the surface severely incomplete for any practical purpose.
WhatsMCP connects Claude and other MCP-compatible AI agents directly to WhatsApp. Send and receive text, images, documents, and voice notes; manage groups (create, add/remove members, promote admins); look up contacts and profiles; follow channels; and read call and message history — all through a standard MCP interface. For voice use cases, WhatsMCP offers SIP-based calling plans (inbound-only, or full inbound/outbound) so AI voice agents can answer and place WhatsApp calls, plus low-latency WebSocket integrations with voice agent providers like ElevenLabs. Multiple WhatsApp accounts can be paired and managed per workspace, with webhook support for real-time inbound message delivery to your own infrastructure.
Atendio is a WhatsApp AI assistant for businesses in Latin America, on the official WhatsApp Business Platform. This MCP server lets Claude (or any MCP client) list and read WhatsApp conversations, view analytics and assistant settings, and create, edit or delete the rules your AI assistant follows. Remote, OAuth 2.1; the business always reviews and publishes rule changes.
Let Claude or ChatGPT search, read and send your WhatsApp messages over MCP. OAuth sign-in.
Hosted MCP server for your own WhatsApp accounts: messages, contacts, groups, channels, calls.
