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Llm Usage & Cost Tracker MCP Server

@zhaoyue722

Repository

Basic information

License

MIT

Transports

stdio

Author

zhaoyue722

Submitted by

越越的糖

About Llm Usage & Cost Tracker MCP Server

A local-first, multi-provider cost meter for LLM usage, exposed as MCP tools. Captures every call into a local SQLite ledger and lets any coding agent query spend, compare providers, and get recommendations — no cloud, no account. First-class support for Chinese providers (Qwen,

#cost-tracking#llm#observability#pricing#local-first#anthropic#openai#deepseek#qwen

Llm Usage & Cost Tracker MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "llm-usage": {
      "command": "uvx",
      "args": [
        "llm-usage-mcp"
      ]
    }
  }
}

Llm Usage & Cost Tracker MCP Server tools

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Fetch the live tool list by running this server in a temporary sandbox using the button above.

Overview

What is Llm Usage & Cost Tracker?

Llm Usage & Cost Tracker is a local-first MCP server and CLI that captures LLM API calls across multiple providers (Anthropic, OpenAI, DeepSeek, Qwen), calculates costs, and answers spend queries through an agent or terminal. It is a cost meter, not a router.

How to use Llm Usage & Cost Tracker?

Install via uv tool install llm-usage-mcp (or clone from source). Set at least one provider API key as an environment variable. Run the capture proxy (llm-usage-proxy), which listens on 127.0.0.1:5525. Point your LLM client’s base URL to the proxy. Use the MCP server (e.g., claude mcp add llm-usage -- uv run llm-usage-mcp) to ask agent questions, or run CLI commands like llm-usage spend, llm-usage compare, and llm-usage recommend.

Key features of Llm Usage & Cost Tracker

  • Local-first SQLite storage, no telemetry.
  • Supports Anthropic, OpenAI, DeepSeek, and Qwen.
  • MCP server with seven query tools.
  • CLI with subcommands for spend, compare, recommend.
  • Capture proxy logs all API calls idempotently.
  • Cross-provider cost comparison and recommendation.
  • Works with streaming and non-streaming calls.
  • No SaaS signup or account needed.

Use cases of Llm Usage & Cost Tracker

  • Monitor daily, weekly, or monthly spend per provider or model.
  • Compare hypothetical workload costs across all priced models.
  • Get the cheapest model recommendation for a budget and workload.
  • Integrate with Claude Code, Cursor, or any MCP client.
  • Manually log usage when the capture proxy is not in use.

Frequently asked questions

1

What does it do vs a router?

It is a cost meter, not a router. It tells you what you spent and which provider fits a workload, but never changes your calls. It pairs happily alongside a router or a model-leaderboard tool.

2

What are the runtime requirements?

Python 3.13+, uv or pipx for installation. SQLite is built into Python, no extra database setup.

3

Where does my usage data live?

All data is stored locally in a SQLite file at `~/.llm-usage/usage.db`.

4

Which providers are supported?

Anthropic, OpenAI, DeepSeek, and Qwen are supported for both streaming and non-streaming. More providers (Gemini, Bedrock, Moonshot) are planned.

5

How do I authenticate and connect?

API keys are set as environment variables (e.g., `ANTHROPIC_API_KEY`). The proxy holds keys server-side; clients point their base URL at `http://127.0.0.1:5525` and never need keys directly.

Comments

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