Vonage AI Assist MCP Server
@micahman33
Vonage AI Assist MCP Server について
MCP server to assist with AI code generation using Claude Desktop, Claude Code or any coding tool that supports MCP servers to ensure you're always working from the most current Vonage SDKs and APIs
基本情報
設定
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"VonageAssist": {
"command": "npx",
"args": [
"-y",
"@smithery/cli",
"install",
"@micahman33/VonageAICodeAssist",
"--client",
"claude"
]
}
}
}ツール
ツールは検出されませんでした
ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
概要
What is Vonage AI Assist MCP Server?
Vonage AI Assist MCP Server is a Model Context Protocol (MCP) server that helps developers integrate Vonage API capabilities by providing AI‑assisted access to Vonage’s official documentation. It uses FastMCP and a dedicated tool (“Vonage‑Assist”) to search developer.vonage.com, retrieve relevant documentation, and return extracted text to any MCP‑compatible AI assistant (e.g., Claude). The server is built for developers who want to quickly find Vonage API information through natural‑language queries.
How to use Vonage AI Assist MCP Server?
Install automatically via Smithery (npx -y @smithery/cli install @micahman33/VonageAICodeAssist --client claude) or manually by setting up a Python 3.13+ environment, configuring the SERPER_API_KEY environment variable, installing dependencies (uv install), and running python main.py. Once running, the server exposes the Vonage‑Assist tool with two parameters: query (your search question) and library (currently only "vonage"). For example, ask an MCP‑compatible AI: “Use the Vonage‑Assist tool to find information about implementing two‑factor authentication with Vonage APIs.”
Key features of Vonage AI Assist MCP Server
- MCP‑based documentation search tool
- Integrates with Google Serper API for targeted searches
- Retrieves and extracts content from Vonage developer docs
- Compatible with Claude and other MCP‑compatible AI assistants
- Simple two‑parameter interface (query, library)
- Built with FastMCP, httpx, BeautifulSoup, and python‑dotenv
Use cases of Vonage AI Assist MCP Server
- Quickly find Vonage API documentation for SMS, Voice, Verify, or Video endpoints
- Get AI‑assisted answers about implementing two‑factor authentication
- Search Vonage developer docs without leaving your AI assistant
- Speed up integration by retrieving relevant documentation in natural language
FAQ from Vonage AI Assist MCP Server
What is the Vonage-Assist tool?
It is the main tool exposed by the server that searches Vonage’s official documentation (developer.vonage.com/en/documentation) using the Google Serper API and returns extracted text content to the user.
What are the required dependencies and runtime?
Python 3.13+ is required. You must set the SERPER_API_KEY environment variable. The server depends on FastMCP, httpx, BeautifulSoup, and python‑dotenv.
How do I install Vonage AI Assist MCP Server?
You can install it automatically via Smithery with the command npx -y @smithery/cli install @micahman33/VonageAICodeAssist --client claude, or manually by cloning the repository, setting up the environment variable, installing dependencies (uv install), and running python main.py.
What library parameter is supported?
Currently only the value "vonage" is supported for the library parameter.
Which AI assistants are compatible?
The server works with any AI assistant that supports the Model Context Protocol (MCP), notably including Claude.
「その他」の他のコンテンツ
Servers
modelcontextprotocolModel Context Protocol Servers
IDA Pro MCP
mrexodiaAI-powered reverse engineering assistant that bridges IDA Pro with language models through MCP.
Awesome-MCP-ZH
yzflyMCP 资源精选, MCP指南,Claude MCP,MCP Servers, MCP Clients
Unity MCP ✨
justinpbarnettUnity MCP acts as a bridge between AI assistants and your Unity Editor. Give your LLM tools to manage assets, control scenes, edit scripts, and automate tasks within Unity.
Production-ready MCP integrations for AI applications
Klavis-AIKlavis AI: MCP integration platforms that let AI agents use tools reliably at any scale
コメント