Optimize SerpApi costs by reducing credit consumption and choosing the right plan.
Use when analyzing search usage, reducing monthly costs,
or implementing credit-saving strategies.
Trigger: "serpapi cost", "serpapi pricing", "reduce serpapi costs", "serpapi credits".
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Optimize SerpApi costs by reducing credit consumption and choosing the right plan.
Use when analyzing search usage, reducing monthly costs,
or implementing credit-saving strategies.
Trigger: "serpapi cost", "serpapi pricing", "reduce serpapi costs", "serpapi credits".
allowed-tools
Read, Grep
version
1.4.0
license
MIT
author
Jeremy Longshore <jeremy@intentsolutions.io>
tags
["saas","search","seo","serpapi"]
compatibility
Designed for Claude Code
SerpApi Cost Tuning
Overview
SerpApi charges per search (1 credit each). Plans: Free (100/mo), Developer ($75, 5K/mo), Business ($200, 15K/mo), Enterprise (custom). Key savings: caching, archive retrieval (free), and Google Light API.
Cost Strategies
Strategy 1: Aggressive Caching (Biggest Savings)
# Search results rarely change within an hour# Cache for 1 hour = up to 24x credit reduction for hourly queries# Cache for 1 day = up to 720x for queries checked every 2 minutesimport hashlib, json, redis, serpapi, os
r = redis.Redis.from_url(os.environ["REDIS_URL"])
client = serpapi.Client(api_key=os.environ["SERPAPI_API_KEY"])
defcached_search(ttl_seconds=3600, **params):
key = f"serpapi:{hashlib.md5(json.dumps(params, sort_keys=True).encode()).hexdigest()}"
cached = r.get(key)
if cached:
return json.loads(cached) # FREE: no credit consumed
result = client.search(**params) # 1 credit
r.setex(key, ttl_seconds, json.dumps(dict(result)))
return result
Strategy 2: Archive API (Free Retrieval)
# Every search result is stored in the archive# Retrieve by search_id at no cost
archived = client.search(engine="google", search_id="previous_id")
# 0 credits -- use for re-processing or delayed access
Strategy 3: Google Light API (Same Cost, Faster)
# Same 1 credit but faster response (~1s vs 3-5s)# Good for: organic results only, no knowledge graph needed
result = client.search(engine="google_light", q="query")
Strategy 4: Reduce num Parameter
# Default num=10 (10 results). If you only need top 3:
result = client.search(engine="google", q="query", num=3)
# Still 1 credit, but faster response
