mcpField
T
Tavily-Anet-MCP Server

Tavily-Anet-MCP Server

Local
github.com/marekkucakSearch0Updated 83w ago

About Tavily-Anet-MCP Server

Tavily-Anet-MCP Server is a Rust MCP server for AI agent and research systems that need current web information. It provides Tavily search and URL content extraction over NATS transport.

Key features

  1. 01Tavily web search
  2. 02Extract content from URLs
  3. 03Filter by domain and time range
  4. 04Choose search topic and depth
  5. 05NATS message transport
  6. 06JSON-RPC 2.0 API

Use cases

  1. 01Finding recent web information for an AI agent
  2. 02Searching news within a selected time range
  3. 03Retrieving page content from a list of URLs

MCP support

Exposes Tavily search and URL extraction as tools for MCP clients. Requests are carried over NATS, with a JSON-RPC 2.0-compatible API.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

Tavily-Anet-MCP Server

A Rust implementation of the Model Control Protocol (MCP) server that provides Tavily search and content extraction capabilities via a standardized protocol.

This server integrates the powerful Tavily API with the Anet MCP framework, enabling AI agents to perform web searches and extract content from URLs. It is designed for developers building AI agent systems, LLM-based tools, or research automation that requires up-to-date web information.


Features

  • ✅ Tavily Search integration with comprehensive parameters
  • 📄 Tavily Extract for content retrieval from URLs
  • 🔄 NATS transport layer for message passing
  • 🛠️ JSON-RPC 2.0 compatible API
  • ⚡ Asynchronous request handling with Tokio
  • 🔍 Advanced search capabilities including domain filtering, time ranges, and topic selection

Requirements

  • Rust 1.70+
  • NATS server running locally or accessible via network
  • Tavily API Key (get one from Tavily's website)

Installation

Clone the repository and build the server:

git clone https://github.com/yourusername/tavily-anet-mcp.git
cd tavily-anet-mcp

Add your Tavily API key to a .env file:

TAVILY_API_KEY=your_api_key_here
NATS_URL=nats://localhost:4222
MCP_SUBJECT=mcp.requests

Getting Started

Running the Server
# Start a NATS server in another terminal or ensure one is already running
# Example:
nats-server

# Run the Tavily MCP server
cargo run
Testing the Server

You can test the server using the included test client:

cargo run --example test_client

This will send various requests to the server (initialize, listTools, search, extract) and print the responses.


Available Tools

1. Tavily Search

A powerful web search tool that provides comprehensive, real-time results using Tavily's AI search engine.

Parameters:

  • query (required): Search query string
  • search_depth: "basic" or "advanced" (default: "basic")
  • topic: "general" or "news" (default: "general")
  • days: Number of days back for results (for news topic)
  • time_range: "day", "week", "month", "year"
  • max_results: 5-20 (default: 10)
  • include_images: Boolean
  • include_raw_content: Boolean
  • include_domains: Array of domains to include
  • exclude_domains: Array of domains to exclude

Example:

{
  "name": "tavily-search",
  "arguments": {
    "query": "Latest developments in AI",
    "max_results": 5,
    "topic": "news",
    "days": 7
  }
}
2. Tavily Extract

A tool for extracting raw content from web pages.

Parameters:

  • urls (required): Array of URLs to extract content from
  • extract_depth: "basic" or "advanced" (default: "basic")
  • include_images: Boolean (default: false)

Example:

{
  "name": "tavily-extract",
  "arguments": {
    "urls": ["https://www.rust-lang.org/"],
    "extract_depth": "advanced",
    "include_images": true
  }
}

Architecture

The server follows a modular design:

  • tools – Tavily Search and Extract implementations
  • models – Tavily API response structures
  • utils – Formatting and helper functions
  • transport – NATS message transport layer

Development

Adding New Features

To extend the server with additional Tavily capabilities:

  1. Define response structures in src/models/tavily.rs
  2. Implement the tool in src/tools/ following the Tool trait
  3. Add formatting functions in src/utils/formatter.rs
  4. Register the tool in src/main.rs

Troubleshooting

  • Ensure your Tavily API key is valid and correctly set in the environment variables
  • Check that the NATS server is running and accessible
  • Verify the request format matches the expected input schema for each tool

License

MIT License


Acknowledgements

This project is built on top of the Anet MCP Server framework and integrates with the Tavily API.

Comments

Markdown supported

New to MCP?

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.