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Solution

Stop AI Agents from Overspending on Search

An AI agent running an autonomous research loop makes 50+ search API calls in a single session, burning through a month of search budget in minutes. There is no native cap in LangC

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The Problem

An AI agent running an autonomous research loop makes 50+ search API calls in a single session, burning through a month of search budget in minutes. There is no native cap in LangChain, CrewAI, or similar frameworks.

The Scavio Solution

Wrap the search function in a credit counter that raises an exception and returns partial results when the session limit is hit. One decorator, zero framework changes required.

Before

Agent starts a research task. Each subtask spawns more searches. After 80 calls, the monthly credit allotment is gone. The agent completes but the bill is 4x expected. No warning was issued.

After

Agent is initialized with a 20-credit cap. After 20 searches, BudgetExceeded is raised. The agent catches it, returns the research gathered so far, and stops. Total session cost: $0.10.

Who It Is For

Developers building autonomous agents with LangChain, CrewAI, or custom loops where search is called in unbounded loops without cost visibility.

Key Benefits

  • Hard cap prevents runaway spend regardless of agent loop depth
  • Partial results are returned gracefully instead of failing silently
  • Works with any search provider that charges per call
  • Per-session or per-run budget, configurable at call time

Python Example

Python
import functools
import requests

class BudgetExceeded(Exception): pass

class SearchBudget:
    def __init__(self, cap): self.cap = cap; self.used = 0
    def charge(self):
        self.used += 1
        if self.used > self.cap: raise BudgetExceeded(f"{self.used}/{self.cap} credits used")

def make_capped_search(cap_credits):
    budget = SearchBudget(cap_credits)
    def search(query, **kwargs):
        budget.charge()
        r = requests.post("https://api.scavio.dev/api/v1/search",
                          json={"query": query, "num_results": kwargs.get("n", 5)},
                          headers={"x-api-key": "your-scavio-api-key"}, timeout=15)
        r.raise_for_status()
        return r.json().get("organic_results", [])
    search.budget = budget
    return search

# Usage
search = make_capped_search(cap_credits=20)
try:
    results = search("best python frameworks 2026")
except BudgetExceeded as e:
    print(f"Stopped: {e}")

JavaScript Example

JavaScript
function makeCappedSearch(cap, apiKey) {
  let used = 0;
  return async function search(query, n = 5) {
    used++;
    if (used > cap) throw new Error(`Budget exceeded: ${used}/${cap}`);
    const res = await fetch('https://api.scavio.dev/api/v1/search', {
      method: 'POST',
      headers: { 'Content-Type': 'application/json', 'x-api-key': apiKey },
      body: JSON.stringify({ query, num_results: n })
    });
    return (await res.json()).organic_results ?? [];
  };
}

Platforms Used

Frequently Asked Questions

An AI agent running an autonomous research loop makes 50+ search API calls in a single session, burning through a month of search budget in minutes. There is no native cap in LangChain, CrewAI, or similar frameworks.

Wrap the search function in a credit counter that raises an exception and returns partial results when the session limit is hit. One decorator, zero framework changes required.

Developers building autonomous agents with LangChain, CrewAI, or custom loops where search is called in unbounded loops without cost visibility.

Yes. Scavio's free tier includes 50 credits on signup with no credit card required. That is enough to validate this solution in your workflow.

Stop AI Agents from Overspending on Search

Wrap the search function in a credit counter that raises an exception and returns partial results when the session limit is hit. One decorator, zero framework changes required.

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