Find where your AI spend leaks and where your agents are exposed.

What one check covers

• Cost and latency

  Tokvera measures your inference endpoint: Time to first token and latency percentiles at rising concurrency, error rates, cost per 1,000 requests, and whether repeated prompts are worth caching.

• Agent exposure

  Sievant reads your MCP client configuration and reports what a customer security review would flag: Credentials and secret values in MCP configuration files, servers given the filesystem root or your whole home directory, and remote servers with no credential or over plain HTTP.

• One fix plan

  Both tools' findings merge into one ranked list and a 30-day fix plan. The fix text is each tool's own: Halotrcer adds no advice of its own.

What stays on your machine

Halotrcer contacts only the target you give it (through Tokvera) and reads only the MCP configuration files Sievant reads, on this machine. It sends no telemetry. Secrets stay masked as each tool masks them; on top of that, Halotrcer drops URL credentials and query strings, hides environment values, shows your home directory as ~ and replaces your user name with <user>.

Two tools, one report

• Tokvera

  Find out where your LLM inference is slow, failing or expensive, in two commands.

• Sievant

  Sievant puts a security checkpoint between AI agents and the tools they call.

Two checks you can do now

• AI bill leak calculator

  Estimate your monthly LLM spend and how much of it goes on repeated, uncached input, from your own numbers.

• Is your MCP setup leaking?

  What sievant scan checks in the MCP servers your AI clients launch, and what a finding looks like.

Rather we ran it?

The AI Cost & Security Audit runs both tools on your system, leaves the instrumentation in place and hands you one combined report.

From $9,500, 2–3 weeks.