← Back to skills↗↗↗
Research & retrieval · Search Data Extraction · mcp
Tavily MCP
Integrates with the Tavily API to enable advanced search and content extraction operations, facilitating web research and up-to-date information access for AI applications.
Overall score
72
mcpnodesearch data extractionregistry validated
Setup difficulty
Easy
Install method
npm · local
Supported providers
Any provider
Supported hosts
MCP-compatible host
Permission posture
low
Last verified
Apr 10, 2026
Score breakdown
Utility80
Compatibility61
Ease of setup88
Reliability68
Docs quality71
Adoption60
Safety & maintenance56
Scores combine benchmark signals, product experience, and editorial weighting. Use them as a practical guide, not an absolute truth claim.
Best for
ResearchAgent automation
Works with
MCP-compatible hostscommunity registry validated
Capabilities
SearchSearchContextSearchQNAExtract
Sources & trust
Verified registry fields
SummaryRepository
This entry is live under the scaled catalog policy: maintainer repo + community registry metadata are visible, but VerdictLens did not treat it as fully official-field verified.
Tavily MCP repo
GitHub · Tier 4 · Apr 10, 2026
Repository
Awesome MCP Registry listing
Community registry · Tier 3 · Apr 10, 2026
SummaryDescriptionSubcategoryInstall methodCapabilities
Tavily MCP VerdictLens scale review
Manual review · Tier 3 · Apr 10, 2026
Best-fit guidanceWorks-with guidancePermission postureOverall score
Strengths
- Clear MCP-server-shaped capability boundary from a maintainer-controlled repository and structured registry entry.
- Imported from a community registry entry marked as validated/runnable, so it clears a higher live-catalog bar than generic discovery-only listings.
Things to watch
- VerdictLens has not manually reviewed every operational claim for this entry; trust the repo and source links more than the editorial score.
- Community validation is still weaker than direct official-document verification, so production teams should inspect permissions and install instructions before rollout.
Best for
Research synthesis & analyst workflows
Prioritize source grounding, multilingual reading, long-context reasoning, and a retrieval stack that stays inspectable.
Agent automation & operations
Prioritize tool reliability, composability, secret handling, and robust state management across long-running flows.