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Tavily Search

This Tavily search MCP server, developed by Tomatio13, provides an interface for AI assistants to perform web searches using the Tavily API. It enables AI agents to query Tavily and retrieve structured search results including AI-generated answers, URLs, and titles through a controlled MCP server. Built in Python, the implementation handles API authentication and request formatting. By leveraging Tavily's AI-powered search capabilities, this server allows AI systems to access real-time web information in a safe manner. It is particularly useful for AI assistants needing to conduct research, answer questions based on current information, or provide relevant search results while maintaining a clear separation between the AI model and external data sources. The implementation includes Docker support for easy deployment in various environments.

Cognium trust score

50%

Tier

Unverified

Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately.

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Metadata

Version: 1.0.0
Skill type: atomic
Execution layer: mcp-remote
Category: cloud-infra
Source: PulseMCP
Repository: github.com/tomatio13/mcp-server-tavily
Author type: human
Updated: 2026-04-25

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MCP

Resolve Tavily Search from your agent

Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.

One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.

claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp

Swap --scope user for --scope project to commit it to .mcp.json.

Your client Same endpoint everywhere; only the config key differs. The full list is in the descriptor.

Claude Desktop · Settings → Connectors → Add custom connector

https://api.skillsregistry.net/mcp

Paste the URL as the connector endpoint. No authentication.

ChatGPT · Settings → Connectors → Create (developer mode) → MCP server URL

https://api.skillsregistry.net/mcp

Authentication: none. Works in chat and deep research — the server exposes the connector search and fetch tools.

Codex CLI · ~/.codex/config.toml

[mcp_servers.skillsregistry]
url = "https://api.skillsregistry.net/mcp"