mcpbeat

AI Cost Analyzer MCP Server

local only

AI Cost Analyzer runs on your own machine — the client starts it, so there is no endpoint to ping. 8 installs a week from npm.

Analyze LLM API costs: token waste detection, caching savings estimates, model comparison

8
Installs / week
npm · ai-cost-analyzer
Stars
on GitHub
Last commit
0 releases in 90 days
License
language unknown

Connect this server

This server runs on your own machine — install it with the package manager and the client starts it for you. Package name taken from the official registry entry.

run in your terminal
claude mcp add ai-cost-analyzer -- npx -y ai-cost-analyzer
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "ai-cost-analyzer": {
      "args": [
        "-y",
        "ai-cost-analyzer"
      ],
      "command": "npx"
    }
  }
}
~/.codex/config.toml
[mcp_servers.ai-cost-analyzer]
command = "npx"
args = ["-y", "ai-cost-analyzer"]
.cursor/mcp.json
{
  "mcpServers": {
    "ai-cost-analyzer": {
      "args": [
        "-y",
        "ai-cost-analyzer"
      ],
      "command": "npx"
    }
  }
}
.vscode/mcp.json
{
  "mcpServers": {
    "ai-cost-analyzer": {
      "args": [
        "-y",
        "ai-cost-analyzer"
      ],
      "command": "npx"
    }
  }
}

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AI Cost Analyzer — questions

Answers built from our own checks of this server.

Why is there no uptime for AI Cost Analyzer?
AI Cost Analyzer runs on your own machine over stdio — there is no network address to reach, so uptime cannot be measured for it by anyone. What can be measured is adoption: the npm package ai-cost-analyzer was installed 8 times last week.
How do I connect AI Cost Analyzer?
Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It runs locally, so the command pulls ai-cost-analyzer straight from npm; nothing to host, nothing to sign up for.
How many people use AI Cost Analyzer?
The npm package ai-cost-analyzer was installed 8 times in the last week. We show installs rather than GitHub stars on purpose: a star is a bookmark, an install is someone actually running it.