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OWL x WhatsApp MCP Server Integration

@Bipul70701

代码仓库

基本信息

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沟通协作

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stdio

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Bipul70701

关于 OWL x WhatsApp MCP Server Integration

暂无概览

#whatsapp#mcp#integration#ai-agents

OWL x WhatsApp MCP Server Integration 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "WhatsApp_MCP_Server": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        "venv"
      ]
    }
  }
}

OWL x WhatsApp MCP Server Integration 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is OWL x WhatsApp MCP Server?

OWL x WhatsApp MCP Server integrates the WhatsApp MCP server with the OWL multi‑agent framework, enabling AI agents to access, search, and send WhatsApp messages through a Streamlit user interface. It is built for developers who want to combine WhatsApp data with autonomous agent workflows.

How to use OWL x WhatsApp MCP Server?

Clone the repository, create and activate a Python virtual environment, install dependencies with pip install -r requirements.txt, and rename .env_template to .env with the required API keys. Then set up and run the WhatsApp MCP server separately. Finally, launch the Streamlit app with streamlit run project.py.

Key features of OWL x WhatsApp MCP Server

  • Multi‑agent collaboration using CAMEL‑AI and OWL frameworks
  • Access and search personal WhatsApp messages including media
  • Send messages to individuals or groups directly
  • Real‑time web search for up‑to‑date information
  • Intuitive Streamlit user interface

Use cases of OWL x WhatsApp MCP Server

  • Automate responses to incoming WhatsApp messages using AI agents
  • Search and retrieve personal chat history for analysis
  • Dispatch scheduled or automated messages to contacts or groups
  • Combine web search results with WhatsApp data for enriched responses

常见问题

1

What dependencies are required?

Python, CAMEL‑AI, OWL, Streamlit, and a separate WhatsApp MCP server (follow setup instructions from the linked repository).

2

How do I configure the environment variables?

Rename `.env_template` to `.env` and fill in the required API keys and configurations.

3

Can I send messages through the app?

Yes, the app includes message dispatch functionality to send messages to individuals or groups.

4

Is web search available?

Yes, the SearchToolkit provides real‑time web search capabilities.

5

What does the Streamlit interface do?

It captures user tasks and displays results in real‑time for seamless interaction with the agents.

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