Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@agent-costcenter-mcp which agent costs the most?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP server for per-agent cost attribution and budget management. Answer "which agent costs the most?" across your entire AI agent fleet.
Per-agent cost tracking — register agents, log LLM and tool calls, get per-agent spend
Built-in pricing table — 11 models (Claude, GPT, Gemini, DeepSeek) with fuzzy name matching
Budget management — set caps and alerts, check remaining budget, warn or block on overspend
Cost reports — breakdown by agent, team, project, or all; includes model-level detail and percentages
Anomaly detection — automatically flag agents with 2x+ spending spikes
Model comparison — compare cost-per-1K-tokens across all models used
Related MCP server: AgentCost
npx agent-costcenter-mcp{
"mcpServers": {
"agent-costcenter": {
"command": "npx",
"args": ["agent-costcenter-mcp"]
}
}
}Tool | Description |
| Register agent with team, project, model, and budget cap |
| Log an LLM call — auto-calculates cost from pricing table |
| Log a tool/API call cost |
| Cost breakdown by agent, team, project, or all |
| Set spending threshold (warn or block) |
| Check if agent is within budget |
| Find agents with unusual spending spikes |
| Compare cost efficiency across models |
URI | Description |
| Current total spend across all agents |
| Built-in model pricing table |
Model | Input | Output |
claude-opus-4 | $15.00 | $75.00 |
claude-sonnet-4 | $3.00 | $15.00 |
claude-haiku-4 | $0.80 | $4.00 |
gpt-4o | $2.50 | $10.00 |
gpt-4o-mini | $0.15 | $0.60 |
gpt-4.1 | $2.00 | $8.00 |
gpt-4.1-mini | $0.40 | $1.60 |
gemini-2.5-pro | $1.25 | $10.00 |
gemini-2.5-flash | $0.15 | $0.60 |
deepseek-v3 | $0.27 | $1.10 |
deepseek-r1 | $0.55 | $2.19 |
Model names are fuzzy-matched (case-insensitive, strips version suffixes).
1. register_agent(agent_id="researcher", team="discovery", model="claude-sonnet-4", budget_cap_usd=10)
2. log_llm_call(agent_id="researcher", model="claude-sonnet-4", input_tokens=5000, output_tokens=2000)
3. log_tool_call(agent_id="researcher", tool_name="web_search", duration_ms=1200, cost_usd=0.01)
4. check_budget(agent_id="researcher")
5. get_cost_report(scope="all")
6. get_cost_anomalies()
7. compare_models()npm install
npm test
npm run dev # watch modeMIT
This server cannot be deployed
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