Tavily Alternatives for Structured Search
Tavily returns AI summaries, not structured data. For agents needing typed fields (price, rating, URL), alternatives like Scavio and Serper return raw SERP JSON.
Tavily was acquired by Nebius for $275M in February 2026, and the roadmap is now uncertain for teams that built on their search API. Four structured alternatives exist in 2026: Scavio for multi-platform structured search at $0.005/credit, SearXNG for free self-hosted metasearch, Serper for cheap Google-only at $0.30-1.00 per 1k, and Exa for semantic retrieval at $7/1k searches.
Why Tavily's acquisition matters
Nebius (the Yandex spinoff) acquired Tavily primarily for its agent search infrastructure. Post-acquisition, pricing and API stability are in question. Teams that integrated Tavily for structured web search in agent workflows need alternatives that are either self-hosted (no acquisition risk) or backed by clear pricing models without VC-driven pivot risk.
Alternative comparison
alternatives = {
"Scavio": {
"cost_1k": 5.00, # $0.005/credit, 1 credit per search
"free_tier": "250/mo",
"platforms": ["Google", "YouTube", "Amazon", "Walmart", "Reddit", "TikTok"],
"output": "Structured JSON with SERP features",
"agent_ready": True, # MCP server available
"self_hosted": False,
"best_for": "Multi-platform structured search, agent workflows via MCP",
},
"SearXNG": {
"cost_1k": 0.00, # Free (server cost only)
"free_tier": "unlimited",
"platforms": ["70+ search engines"],
"output": "JSON via API (requires parsing)",
"agent_ready": False, # No native MCP, need custom wrapper
"self_hosted": True,
"best_for": "Privacy-first, zero API cost, full control",
},
"Serper": {
"cost_1k": 1.00, # $50/50k credits
"free_tier": "2,500 one-time",
"platforms": ["Google only"],
"output": "Structured JSON",
"agent_ready": False,
"self_hosted": False,
"best_for": "High-volume Google-only at lowest per-query cost",
},
"Exa": {
"cost_1k": 7.00, # $7/1k searches
"free_tier": "1,000/mo",
"platforms": ["Exa's own index (web-wide)"],
"output": "Structured JSON with content extraction",
"agent_ready": True,
"self_hosted": False,
"best_for": "Semantic/meaning-based retrieval for RAG pipelines",
},
}
for name, d in sorted(alternatives.items(), key=lambda x: x[1]["cost_1k"]):
print(f"{name}: ${d['cost_1k']:.2f}/1k -- {d['best_for']}")Migration from Tavily: code diff
import requests, os
# BEFORE: Tavily search
def tavily_search(query: str) -> list:
resp = requests.post(
"https://api.tavily.com/search",
json={"api_key": os.environ["TAVILY_API_KEY"], "query": query},
timeout=10,
)
return resp.json().get("results", [])
# AFTER: Scavio search (drop-in replacement)
def scavio_search(query: str) -> list:
resp = requests.post(
"https://api.scavio.dev/api/v1/search",
headers={"x-api-key": os.environ["SCAVIO_API_KEY"]},
json={"query": query, "platform": "google", "country_code": "us"},
timeout=10,
)
# Normalize to Tavily-compatible shape if needed
return [
{
"title": r.get("title", ""),
"url": r.get("link", ""),
"content": r.get("snippet", ""),
}
for r in resp.json().get("organic_results", [])
]When each alternative wins
SearXNG wins if you have DevOps capacity and want zero API cost. It aggregates 70+ engines but returns inconsistent JSON that needs parsing, and instance maintenance is nontrivial. Serper wins for pure Google search at scale -- at $0.30/1k on their largest pack, nothing is cheaper for structured Google results. Scavio wins when you need multiple platforms under one API (Google + Reddit + YouTube + Amazon) and want consistent JSON across all of them. Exa wins for semantic retrieval where traditional keyword search falls short -- finding conceptually similar documents rather than keyword matches.
Agent integration: MCP support
# Scavio MCP server for Claude, Cursor, or any MCP-compatible agent
# Add to your MCP config:
# {
# "mcpServers": {
# "scavio": {
# "url": "https://mcp.scavio.dev/mcp",
# "headers": {
# "Authorization": "Bearer YOUR_SCAVIO_KEY"
# }
# }
# }
# }
# Exa also offers MCP integration
# SearXNG and Serper require custom MCP wrappers
# For agent workflows, MCP reduces integration friction from
# "write HTTP client code" to "add a config block"Decision matrix
- Budget is primary concern, Google only: Serper ($0.30-1.00/1k)
- Need multi-platform structured data: Scavio ($5/1k)
- Zero cost, own infrastructure: SearXNG (free + server cost)
- Semantic retrieval for RAG: Exa ($7/1k)
- Tavily drop-in replacement with MCP: Scavio (closest feature match)
- High-volume batch processing: DataForSEO queue ($0.60/1k)
If you built on Tavily, the migration is straightforward for any of these alternatives. The response shapes differ, but the integration pattern is the same: POST with query, get structured JSON back. Add a normalizer layer and you can swap providers without touching downstream code.