MetaMCP lets you share MCP servers across multiple AI models. Connecting Scavio search to MetaMCP means Claude, GPT, Gemini, and local models all use the same search backend. This avoids duplicate API keys and inconsistent search quality across agents. Setup takes 5 minutes.
Prerequisites
- MetaMCP installed
- Python 3.8+ or Node.js 18+
- A Scavio API key from scavio.dev
- At least two AI model clients configured
Walkthrough
Step 1: Configure Scavio as a MetaMCP server
Add the Scavio search server to your MetaMCP configuration.
Python
import json, os
# MetaMCP configuration
metamcp_config = {
'servers': {
'scavio-search': {
'command': 'npx',
'args': ['-y', 'scavio-search-mcp'],
'env': {
'SCAVIO_API_KEY': os.environ.get('SCAVIO_API_KEY', 'your-key-here')
},
'description': 'Web search, extract, and TikTok data via Scavio API',
'shared_with': ['claude', 'gpt', 'gemini', 'local']
}
}
}
config_path = os.path.expanduser('~/.metamcp/config.json')
print(f'MetaMCP config path: {config_path}')
print(json.dumps(metamcp_config, indent=2))
print(f'\nThis shares one Scavio API key across all connected models.')
print(f'All models get: search, extract, and TikTok tools.')Step 2: Verify search works across models
Test that each connected model can use the search tool.
Python
import requests
API_KEY = os.environ['SCAVIO_API_KEY']
SH = {'x-api-key': API_KEY, 'Content-Type': 'application/json'}
def test_search(label, query):
"""Simulate a model calling the shared search tool."""
data = requests.post('https://api.scavio.dev/api/v1/search',
headers=SH, json={'query': query, 'country_code': 'us', 'num_results': 3}).json()
results = data.get('organic_results', [])
print(f' [{label}] "{query}" -> {len(results)} results')
if results:
print(f' Top: {results[0].get("title", "")[:50]}')
return len(results) > 0
print('=== MetaMCP Search Verification ===')
models = {
'Claude': 'latest anthropic sdk features',
'GPT': 'openai api new endpoints 2026',
'Gemini': 'google gemini api updates',
'Local': 'best local llm for coding',
}
successes = 0
for model, query in models.items():
if test_search(model, query):
successes += 1
print(f'\nAll models working: {successes}/{len(models)}')
print(f'Cost: ${len(models) * 0.005:.3f} (shared across all models)')Step 3: Monitor shared usage and costs
Track which models are using the most search queries.
Python
from collections import defaultdict
from datetime import datetime
class SearchUsageTracker:
def __init__(self):
self.usage = defaultdict(lambda: {'queries': 0, 'cost': 0.0})
def log(self, model, query):
self.usage[model]['queries'] += 1
self.usage[model]['cost'] += 0.005
def report(self):
print(f'\n=== MetaMCP Search Usage - {datetime.now().strftime("%Y-%m-%d")} ===')
total_queries = 0
total_cost = 0
for model, data in sorted(self.usage.items()):
print(f' {model:10} | {data["queries"]:5} queries | ${data["cost"]:.3f}')
total_queries += data['queries']
total_cost += data['cost']
print(f' {"TOTAL":10} | {total_queries:5} queries | ${total_cost:.3f}')
print(f'\n Monthly estimate: ${total_cost * 30:.2f}')
print(f' vs separate keys: ${total_cost * 30 * 1.5:.2f} (50% overhead from duplication)')
tracker = SearchUsageTracker()
# Simulate usage
for _ in range(10): tracker.log('Claude', 'various queries')
for _ in range(15): tracker.log('GPT', 'various queries')
for _ in range(5): tracker.log('Gemini', 'various queries')
for _ in range(8): tracker.log('Local', 'various queries')
tracker.report()Python Example
Python
import os, requests
SH = {'x-api-key': os.environ['SCAVIO_API_KEY'], 'Content-Type': 'application/json'}
def shared_search(model, query):
data = requests.post('https://api.scavio.dev/api/v1/search',
headers=SH, json={'query': query, 'country_code': 'us'}).json()
n = len(data.get('organic_results', []))
print(f'[{model}] {query}: {n} results')
shared_search('Claude', 'anthropic sdk 2026')
shared_search('GPT', 'openai api 2026')
print('Cost: $0.010 (shared key)')JavaScript Example
JavaScript
const SH = { 'x-api-key': process.env.SCAVIO_API_KEY, 'Content-Type': 'application/json' };
async function sharedSearch(model, query) {
const data = await fetch('https://api.scavio.dev/api/v1/search', {
method: 'POST', headers: SH,
body: JSON.stringify({ query, country_code: 'us' })
}).then(r => r.json());
console.log(`[${model}] ${query}: ${(data.organic_results || []).length} results`);
}
await sharedSearch('Claude', 'anthropic sdk 2026');Expected Output
JSON
=== MetaMCP Search Verification ===
[Claude] "latest anthropic sdk features" -> 3 results
Top: Anthropic SDK 2026: What's New in Claude API
[GPT] "openai api new endpoints 2026" -> 3 results
Top: OpenAI API Updates May 2026
[Gemini] "google gemini api updates" -> 3 results
[Local] "best local llm for coding" -> 3 results
All models working: 4/4
Cost: $0.020 (shared across all models)
=== MetaMCP Search Usage ===
Claude | 10 queries | $0.050
GPT | 15 queries | $0.075
Gemini | 5 queries | $0.025
Local | 8 queries | $0.040
TOTAL | 38 queries | $0.190