About MCP2Tavily
MCP2Tavily is a Python MCP server that uses the Tavily API for web searches. It is intended for MCP clients and agent frameworks that need search tools, and offers two query tools with different descriptions.
Key features
- 01Web search through Tavily API
- 02Two search tools for queries
- 03Python 3.11+ and UV setup
Use cases
- 01Searching the web from an MCP client
- 02Giving an agent access to Tavily search
- 03Testing search tools with MCP Inspector
MCP support
The server exposes `search_web` and `search_web_info` as MCP tools. MCP clients can use them to submit queries to the Tavily API.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEMCP2Tavily
A MCP protocol server that implements web search functionality using the Tavily API.
Prerequisites
- Python 3.11+
- UV package manager
- Tavily API key
Installation
- Clone the repository
git clone <repository-url>
cd mcp2tavily
- Create and edit the
.envfile
# Create .env file
touch .env
# Add your Tavily API key to .env
echo "TAVILY_API_KEY=your_api_key_here" > .env
- Set up virtual environment with UV
# Create and activate virtual environment
uv venv
source .venv/bin/activate # On Windows use: .venv\Scripts\activate
- Install dependencies
uv sync
Usage
Install as Claude extension
fastmcp install mcp2tavily.py
Development mode with MCP Inspector
To test the functionality using MCP Inspector:
fastmcp dev mcp2tavily.py
Once running, you can access the MCP Inspector at: http://localhost:5173
Available Tools
search_web(query: str): Search the web using Tavily APIsearch_web_info(query: str): Same as above, with Chinese description
Environment Variables
TAVILY_API_KEY: Your Tavily API key (required)
Step-by-Step Guide
手动添加Cline Continue Claude
Cline Continue Claude的MCP JSON FILE
"mcp2tavily": {
"command": "uv",
"args": [
"run",
"--with",
"fastmcp",
"--with",
"python-dotenv",
"--with",
"tavily-python",
"fastmcp",
"run",
"C:\\Users\\你的真实路径\\mcp2tavily.py"
],
"env": {
"TAVILY_API_KEY": "API密钥"
}
}
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EXAMPLE

Comments
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From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.