curl -fsSL https://cli.tavily.com/install.sh | bash && tvly login

undefined

undefined

{
  "query": "string",
  "answer": "string | null",
  "results": [
    {
      "url": "string",
      "title": "string",
      "content": "string (snippet, ~500-1500 chars)",
      "score": 0.0-1.0,
      "raw_content": "string | null (full page, only with --include-raw-content)"
    }
  ],
  "response_time": 0.0
}

{
  "results": [
    {
      "url": "string",
      "title": "string",
      "raw_content": "string (full page markdown)",
      "images": []
    }
  ],
  "failed_results": [],
  "response_time": 0.0
}

tvly search "query" --json 2>/dev/null | python3 -c "
import json, sys
data = json.load(sys.stdin)

**Heredoc mode** — for anything more complex. Single Bash call, clean multi-line Python, no escaping, no temp files:

```bash
python3 << 'PYEOF'
import json, subprocess
raw = subprocess.check_output(
    ['tvly', 'search', 'query', '--json'],
    stderr=subprocess.DEVNULL
)
data = json.loads(raw)
for r in data['results']:
    print(f"[{r['score']:.2f}] {r['title']}")
    print(f"  {r['url']}")
PYEOF

python3 << 'PYEOF'
import json, subprocess

raw = subprocess.check_output(
    ['tvly', 'search', 'solid-state battery commercialization 2025',
     '--include-raw-content', 'markdown', '--max-results', '8', '--json'],
    stderr=subprocess.DEVNULL
)
data = json.loads(raw)

Context receives: ~800 tokens of titles + snippets. The 300K of raw page content is in `/tmp/tavily_results.json`, untouched.

python3 << 'PYEOF'
import json

data = json.load(open('/tmp/tavily_results.json'))

print(f'## {r["title"]}')
print(f'URL: {r["url"]}\n')

# You write the filtering logic based on the query
# This example extracts paragraphs about specific companies
for para in raw.split('\n\n'):
    para = para.strip()
    if len(para) > 80 and any(kw in para.lower() for kw in
            ['toyota', 'quantumscape', 'samsung', 'commercializ', 'production']):
        print(para)
        print()

print('---\n')

Context receives: ~600 tokens of targeted content. You made the decision about what to keep.

python3 << 'PYEOF'
import json, subprocess

undefined

tvly search "Python 3.13 release date" --max-results 5 --json 2>/dev/null | python3 -c "
import json, sys
data = json.load(sys.stdin)
for r in data['results'][:3]:
    print(f'{r[\"title\"]}')
    print(f'{r[\"content\"][:300]}')
    print()
"

python3 << 'PYEOF'
import json, subprocess

raw = subprocess.check_output(
    ['tvly', 'search', 'NVIDIA Q4 2025 earnings revenue',
     '--include-raw-content', 'markdown', '--max-results', '5',
     '--json'],
    stderr=subprocess.DEVNULL
)
data = json.loads(raw)

for r in data['results']:
    raw_content = r.get('raw_content', '') or ''
    # For financial queries, look for lines with numbers
    financial_lines = [
        line.strip() for line in raw_content.split('\n')
        if any(kw in line.lower() for kw in
               ['revenue', 'eps', 'earnings', 'margin', 'guidance', 'billion'])
        and any(c.isdigit() for c in line)
        and len(line.strip()) > 30
    ]
    if financial_lines:
        print(f'## {r["title"]}')
        print(f'URL: {r["url"]}')
        for line in financial_lines[:15]:
            print(f'  {line}')
        print()
PYEOF

python3 << 'PYEOF'
import json, subprocess

**Turn 2** — you see the triage, pick the best sources, and extract:

```bash
python3 << 'PYEOF'
import json, subprocess

results = json.load(open('/tmp/eu_ai_results.json'))

    # Your filtering logic — tailored to this query
    print(f'## {r["title"]}')
    print(f'URL: {r["url"]}\n')

    for para in content.split('\n\n'):
        para = para.strip()
        if len(para) > 100 and any(kw in para.lower() for kw in
                ['high-risk', 'prohibited', 'deadline', 'obligation',
                 'compliance', 'penalty', 'fine', 'article']):
            print(para)
            print()

    print('---\n')
except Exception:
    continue

undefined

python3 << 'PYEOF'
import json, subprocess

Each turn, you save data to `/tmp/`, decide what to explore next, and write new filtering code as heredocs. The raw data accumulates on disk; your context stays lean.

print(f'## {title}')
print(f'URL: {url}')
print(relevant_content)
print()

try:
    raw = subprocess.check_output(['tvly', 'extract', url, '--json'],
                                   stderr=subprocess.DEVNULL, timeout=30)
except Exception:
    continue

tvly search "query" --json 2>/dev/null | jq '[.results[] | select(.score > 0.5) | {title, url, content}]'