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.