Workflow

MCP Server Audit and Token Cleanup Workflow

Workflow to audit MCP server connections in your AI coding setup, identify redundant tools, and consolidate to reduce token overhead and cost.

Overview

Every MCP server you connect to an AI agent adds tool definitions to the system prompt, consuming tokens on every request. Developers with 5-10 MCP servers waste thousands of tokens per conversation on tool definitions that rarely get called. This workflow audits your MCP setup, identifies which tools are actually used, removes redundant servers, and consolidates search into a single Scavio MCP connection.

Trigger

Monthly audit, triggered manually.

Schedule

Monthly

Workflow Steps

1

Inventory MCP Connections

List all MCP servers configured in your IDE or agent setup. Count tool definitions per server.

2

Analyze Tool Usage Logs

Check which MCP tools were actually called in the last 30 days. Flag servers with zero or low usage.

3

Calculate Token Overhead

Estimate tokens consumed by each server's tool definitions per conversation. Multiply by daily conversation count.

4

Identify Consolidation Opportunities

Find servers that duplicate Scavio's capabilities: separate Google, YouTube, Amazon search tools can be replaced by one MCP.

5

Consolidate and Verify

Remove redundant MCP servers. Replace with Scavio MCP. Verify all previously-used tools still work.

Python Implementation

Python
import requests, os, json
from pathlib import Path

API_KEY = os.environ["SCAVIO_API_KEY"]
MCP_URL = "https://mcp.scavio.dev/mcp"
MH = {"Authorization": f"Bearer {API_KEY}", "Content-Type": "application/json"}

# Step 1: Read your MCP config (Claude Desktop format)
def audit_mcp_config(config_path: str) -> list:
    config = json.loads(Path(config_path).read_text())
    servers = config.get("mcpServers", {})
    audit = []
    for name, cfg in servers.items():
        audit.append({
            "name": name,
            "command": cfg.get("command", ""),
            "args_count": len(cfg.get("args", [])),
        })
    return audit

# Step 2: Test Scavio MCP covers the same capabilities
def test_scavio_mcp_coverage(queries: list) -> list:
    results = []
    for q in queries:
        payload = {
            "jsonrpc": "2.0", "id": 1,
            "method": "tools/call",
            "params": {"name": "search", "arguments": {"query": q["query"], "country_code": "us"}}
        }
        resp = requests.post(MCP_URL, headers=MH, json=payload, timeout=15)
        data = resp.json()
        results.append({
            "query": q["query"],
            "replaced_server": q["replaced_server"],
            "success": "result" in data,
            "result_size": len(str(data.get("result", ""))),
        })
    return results

test_queries = [
    {"query": "python logging best practices", "replaced_server": "google-search-mcp"},
    {"query": "best wireless mouse 2026", "replaced_server": "shopping-search-mcp"},
    {"query": "react hooks tutorial youtube", "replaced_server": "youtube-search-mcp"},
]

coverage = test_scavio_mcp_coverage(test_queries)
for c in coverage:
    status = "OK" if c["success"] else "FAIL"
    print(f"[{status}] {c['replaced_server']} -> scavio MCP: {c['query']}")

consolidated = sum(1 for c in coverage if c["success"])
print(f"\nCan consolidate {consolidated}/{len(coverage)} MCP servers into Scavio MCP")

JavaScript Implementation

JavaScript
const MCP_URL = 'https://mcp.scavio.dev/mcp';
const MH = {'Authorization': 'Bearer '+process.env.SCAVIO_API_KEY, 'Content-Type': 'application/json'};
const fs = await import('fs');

function auditMcpConfig(configPath) {
  const config = JSON.parse(fs.readFileSync(configPath, 'utf8'));
  const servers = config.mcpServers || {};
  return Object.entries(servers).map(([name, cfg])=>({name, command:cfg.command||'', argsCount:(cfg.args||[]).length}));
}

async function testScavioMcpCoverage(queries) {
  const results = [];
  for (const q of queries) {
    const payload = {jsonrpc:'2.0', id:1, method:'tools/call', params:{name:'search', arguments:{query:q.query, country_code:'us'}}};
    const r = await fetch(MCP_URL, {method:'POST', headers:MH, body:JSON.stringify(payload)});
    const data = await r.json();
    results.push({query:q.query, replacedServer:q.replacedServer, success:'result' in data, resultSize:JSON.stringify(data.result||'').length});
  }
  return results;
}

const testQueries = [
  {query:'python logging best practices', replacedServer:'google-search-mcp'},
  {query:'best wireless mouse 2026', replacedServer:'shopping-search-mcp'},
  {query:'react hooks tutorial youtube', replacedServer:'youtube-search-mcp'},
];

const coverage = await testScavioMcpCoverage(testQueries);
for (const c of coverage) {
  const status = c.success ? 'OK' : 'FAIL';
  console.log('['+status+'] '+c.replacedServer+' -> scavio MCP: '+c.query);
}
const consolidated = coverage.filter(c=>c.success).length;
console.log('\nCan consolidate '+consolidated+'/'+coverage.length+' MCP servers into Scavio MCP');

Platforms Used

Google

Web search with knowledge graph, PAA, and AI overviews

Frequently Asked Questions

Every MCP server you connect to an AI agent adds tool definitions to the system prompt, consuming tokens on every request. Developers with 5-10 MCP servers waste thousands of tokens per conversation on tool definitions that rarely get called. This workflow audits your MCP setup, identifies which tools are actually used, removes redundant servers, and consolidates search into a single Scavio MCP connection.

This workflow uses a monthly audit, triggered manually.. Monthly.

This workflow uses the following Scavio platforms: google. Each platform is called via the same unified API endpoint.

Yes. Scavio's free tier includes 250 credits per month with no credit card required. That is enough to test and validate this workflow before scaling it.

MCP Server Audit and Token Cleanup Workflow

Workflow to audit MCP server connections in your AI coding setup, identify redundant tools, and consolidate to reduce token overhead and cost.