tavily-research

tavily research

AI-powered deep research that gathers sources, analyzes them, and produces a cited report. Takes 30-120 seconds.

Before running

Research requires authentication. Run the requested command directly when tvly is already authenticated; do not add a status check to every invocation.

If tvly is missing, follow the tavily-cli setup. If an installed CLI reports an authentication error, use tvly login for authentication only, or tvly init --skip-skills when guided verification is also useful. Browser-based OAuth is preferred when an interactive user can complete it. --no-browser prints the sign-in link instead of opening it, but still waits for a localhost callback. In an unattended agent or CI environment, leave authentication to the user or use a securely provided TAVILY_API_KEY. Do not start a second login immediately after guided setup has completed.

When to use

• You need comprehensive, multi-source analysis
• The user wants a comparison, market report, or literature review
• Quick searches aren't enough — you need synthesis with citations
• Step 5 in the workflow: search → extract → map → crawl → research

Quick start

# Basic research (waits for completion)
tvly research "competitive landscape of AI code assistants"

# Pro model for comprehensive analysis
tvly research "electric vehicle market analysis" --model pro

# Stream results in real-time
tvly research "AI agent frameworks comparison" --stream

# Save report to file
tvly research "fintech trends 2025" --model pro -o fintech-report.json

# JSON output for agents
tvly research "quantum computing breakthroughs" --json

Options

Option	Description
--model	mini, pro, or auto (default)
--stream	Stream results in real-time
--no-wait	Return request_id immediately (async)
--output-schema	Path to JSON schema for structured output
--citation-format	numbered, mla, apa, chicago
--poll-interval	Seconds between checks (default: 10)
--timeout	Max wait seconds (default: 600)
-o, --output	Save the JSON response to a file
--json	Structured JSON output

Model selection

Model	Use for	Speed
mini	Single-topic, targeted research	~30s
pro	Comprehensive multi-angle analysis	~60-120s
auto	API chooses based on complexity	Varies

Rule of thumb: "What does X do?" → mini. "X vs Y vs Z" or "best way to..." → pro.

Async workflow

For long-running research, you can start and poll separately:

# Start without waiting
tvly research "topic" --no-wait --json    # returns request_id

# Check status
tvly research status <request_id> --json

# Wait for completion
tvly research poll <request_id> --json -o result.json

Tips

• Research takes 30-120 seconds — use --stream to see progress in real-time.
• Use --model pro for complex comparisons or multi-faceted topics.
• Use --output-schema to get structured JSON output matching a custom schema.
• For quick facts, use tvly search instead — research is for deep synthesis.
• Read from stdin: echo "query" | tvly research - --json

See also

• tavily-search — quick web search for simple lookups
• tavily-crawl — bulk extract from a site for your own analysis