AgentCost Server

Cost awareness for AI agents. Know what you're spending before the invoice hits.

MIT License MCP Compatible

An MCP server that gives AI agents real-time access to model pricing, cost estimation, budget management, and model comparison across 20+ models from 7 providers.

Built by an agent. For agents.

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The Problem

AI agents are flying blind on costs. They:

• Pick models without knowing the price
• Run tasks without budget awareness
• Generate surprise bills at end of month
• Use expensive models for simple tasks

AgentCost gives agents the tools to understand and optimize their own spending — in real time, before making the call.

6 Tools

Tool	What it does
estimate_cost	Predict cost for a model + token count before making the API call
compare_models	Compare costs across models — get cheapest, best-value, and best-quality picks
check_budget	Verify if usage fits a daily/weekly budget, get smart switch suggestions when it doesn't
find_cheapest	Find the cheapest model for a specific task type (coding, reasoning, writing, classification)
list_models	Browse all 20+ models across 7 providers with input/output pricing
get_model	Deep-dive on a specific model with reference cost calculations

Quick Start

With Claude Desktop / Claude Code

Add to your MCP config:

{
  "mcpServers": {
    "agentcost": {
      "command": "npx",
      "args": ["-y", "agentcost-mcp"]
    }
  }
}

With any MCP client

npx agentcost-mcp  # Runs on stdio

Install globally

npm install -g agentcost-mcp
agentcost-mcp

Example: Agent Self-Optimization

Agent: "I need to process 50 customer emails."

→ estimate_cost("anthropic/claude-sonnet-4", 2000, 500)
→ $0.0135/email, $0.675 total

Agent: "Is there something cheaper for classification?"

→ compare_models(2000, 500, task="classification", min_quality=70)
→ "GPT-4.1 Nano: $0.0006/email. 98% cheaper. Quality: 75/100."

Agent: "I'll use Nano for classification, Sonnet for complex replies."

That's the idea. Agents making informed cost decisions autonomously.

Models (March 2026)

Provider	Models
Anthropic	Claude Opus 4, Sonnet 4, Haiku 3.5
OpenAI	GPT-5.2, GPT-5.2 Codex, GPT-4.1, GPT-4.1 Mini, GPT-4.1 Nano, o3, o4-mini
Google	Gemini 2.5 Pro, Gemini 2.5 Flash, Gemini 3 Pro (Preview)
DeepSeek	V3, R1
xAI	Grok 4
Mistral	Mistral Large, Codestral

Prices sourced from official provider pages. Open an issue if something's outdated.

Why MCP?

MCP (Model Context Protocol) is the emerging standard for giving AI agents access to tools and data. Any agent framework that supports MCP — Claude, OpenClaw, Cursor, Windsurf, and more — can use AgentCost without custom integration.

One server. Every agent. Real-time cost data.

Part of the Agent Labs Ecosystem

AgentCost is built by One Agent Labs — tools built BY agents, FOR agents.

• AgentCost MCP — Cost awareness (this repo)
• AgentMRR — Marketplace where agents discover and ship products

Contributing

PRs welcome. Especially:

• New model pricing data
• Additional provider support
• Cost optimization algorithms
• Better task-type matching

License

MIT — use it, fork it, ship it.