Note: The actual implementation currently only provides a basic greeting functionality (hello_tool), which appears to be a placeholder. The full Evolution API integration described below is not yet available.
This MCP server is intended to enable Claude to automate WhatsApp interactions through Evolution API integration. The planned capabilities include:
Instance Management: Create, connect, restart, logout, delete, and monitor WhatsApp instances
Messaging: Send text, media, audio, stickers, locations, contacts, reactions, polls, lists, and buttons
Contact & Chat Management: Find contacts and chats
Group Operations: Find groups by JID, fetch all groups, and find group members
Webhook & Settings: Configure webhooks and instance settings
Status Updates: Send status messages and set presence
The current implementation appears incomplete or represents an early development version.
Integration with Chatwoot is mentioned as a pending implementation in the documentation.
Integration with OpenAI is mentioned as a pending implementation under Bot Integrations.
Integration with RabbitMQ is mentioned as a pending implementation in the documentation.
Enables interaction with WhatsApp through Evolution API, supporting capabilities like managing instances, sending various message types (text, media, audio, stickers, locations, contacts, reactions, polls, lists, buttons), working with contacts and groups, and configuring webhooks.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@MCP Evolution API send a message to +1234567890 saying 'Meeting at 3 PM tomorrow'"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
A Model Context Protocol (MCP) server for Claude that integrates with Evolution API for WhatsApp automation.
This MCP server allows Claude to interact with WhatsApp through the Evolution API, enabling capabilities like:
Managing WhatsApp instances
Sending various types of messages
Working with contacts and groups
Configuring webhooks and settings
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 dependenciesCreate a .env file with your Evolution API credentials:
EVOLUTION_API_URL=https://evo-api.decisao.ai/
EVOLUTION_API_KEY=REPLACE_WITH_YOUR_REAL_KEYNote: you provided the API URL and a key. For security, never commit real API keys to the repository or share them publicly. Use a local .env file or a secrets manager in production.
Environment | Steps | Command |
Local Development | 1. Clone and install2. Run in dev mode |
|
Local Production | 1. Clone and install2. Build and run |
|
Docker Compose | Run with Docker Compose |
|
Docker | Build and run container |
|
Add this to your Claude Desktop config file (typically located at ~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": {
"evo-api": {
"command": "node",
"args": [
"/path/to/your/mcp-evo-api/dist/main.js"
]
}
}
}If using the Docker deployment:
{
"mcpServers": {
"evo-api": {
"url": "http://localhost:3000"
}
}
}Category | Implemented | Pending Implementation |
Core API | ✅ Get Information✅ Create Instance✅ Fetch Instances✅ Instance Connect✅ Restart Instance✅ Connection State✅ Logout Instance✅ Delete Instance✅ Set Presence | ❌ Check is WhatsApp |
Webhook & Settings | ✅ Set Webhook✅ Find Webhook✅ Set Settings✅ Find Settings | |
Messaging | ✅ Send Plain Text✅ Send Status✅ Send Media✅ Send WhatsApp Audio✅ Send Sticker✅ Send Location✅ Send Contact✅ Send Reaction✅ Send Poll✅ Send List✅ Send Buttons | ❌ Mark Message As Read❌ Mark Message As Unread❌ Archive Chat❌ Delete Message for Everyone❌ Update Message❌ Send Presence (Chat Ctrl) |
Chat & Contacts | ✅ Find Contacts✅ Find Chats | ❌ Update Block Status❌ Fetch Profile Picture URL❌ Get Base64❌ Find Messages❌ Find Status Message |
Groups | ✅ Find Group by JID✅ Fetch All Groups✅ Find Group Members | ❌ Create Group❌ Update Group Picture❌ Update Group Subject❌ Update Group Description❌ Fetch Invite Code❌ Revoke Invite Code❌ Send Group Invite❌ Find Group by Invite Code❌ Update Group Members❌ Update Group Setting❌ Toggle Ephemeral❌ Leave Group |
Profile Settings | ❌ Fetch Business Profile❌ Fetch Profile❌ Update Profile Name❌ Update Profile Status❌ Update Profile Picture❌ Remove Profile Picture❌ Fetch Privacy Settings❌ Update Privacy Settings | |
Bot Integrations | ❌ Typebot Integrations❌ OpenAI Integrations❌ Evolution Bot❌ Dify Bot❌ Flowise Bot | |
Other Integrations | ❌ Chatwoot❌ Websocket❌ SQS❌ RabbitMQ |
For more information, refer to the Evolution API Documentation.
examples/hono-bun/ - pequeno servidor Hono para Bun (exemplo salvo). Veja examples/hono-bun/README.md para instruções de execução.
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.
Drive WhatsApp from any MCP client: pair devices, send text and media, manage contacts and groups.
Drive your real WhatsApp inbox from Claude — send, reply, label, assign, and triage via TimelinesAI.
A comprehensive Model Context Protocol (MCP) server that enables AI assistants to interact with yo…
Model Context Protocol server for the Apideck Unified API. Connect any MCP-compatible agent framework to 100+ accounting systems, HRIS platforms, file storage providers, and more through one integration. More information https://www.apideck.com/mcp-server
