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chenzhaoxuan0

tavily-mcp

by chenzhaoxuan0
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Python
Remote

tavily-mcp

A web search and extraction MCP server powered by Tavily, built on Dedalus.

Tools

Tool

Description

smoke_ping

Verify the Dedalus MCP server can be invoked without external Tavily dispatch

tavily_search

Search the web with AI-generated answer synthesis

tavily_extract

Extract clean content from URLs

tavily_qna_search

Ask a question and get a direct answer with sources

Related MCP server: Tavily Web Search MCP Server

Environment Variables

Variable

Required

Description

TAVILY_API_KEY

Yes

Tavily API key (tvly-...)

DEDALUS_API_KEY

Yes

Dedalus platform API key

DEDALUS_API_URL

No

Dedalus API base URL

DEDALUS_AS_URL

No

Dedalus auth server URL (default: https://as.dedaluslabs.ai)

MCP_SERVER_SLUG

No

Marketplace slug used to derive the default connection name (default: Zx/tavily-mcp)

TAVILY_CONNECTION_NAME

No

Explicit connection name override. For slug calls, prefer Zx-tavily-mcp

Quick Start

# Install dependencies
uv sync

# Set environment variables
cp .env.example .env
# Edit .env with your keys

# Run the server
uv run python src/main.py

Testing

# Unit tests (no API key needed)
uv run pytest tests/test_tools.py

# Live connection tests (requires TAVILY_API_KEY)
uv run pytest tests/test_connection_live.py

Source Decision

Decision: Build native (Python)

The official tavily-ai/tavily-mcp is implemented in TypeScript using @modelcontextprotocol/sdk. Since our infrastructure requires Python with Dedalus DAuth integration, we build natively using dedalus-mcp. The official implementation served as a functional specification for tool definitions and API endpoints.

License

MIT

This server cannot be installed

A
license - permissive license
-
quality - not tested
C
maintenance

How are these scores calculated?

Maintenance

–Maintainers
–Response time
–Release cycle
–Releases (12mo)
Commit activity

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  • Tavily Web Search MCP Server

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    license
    B
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    Enables web search capabilities through the Tavily API, allowing users to search the internet for information using natural language queries. Serves as a demonstration and educational project for building MCP servers with external API integrations.
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