Multi-agent billing and cost allocation tracking
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"io-github-mdfifty50-boop-agent-costcenter": {
"command": "<see-readme>",
"args": []
}
}
}Are you the author?
Add this badge to your README to show your security score and help users find safe servers.
Multi-agent billing and cost allocation tracking
No automated test available for this server. Check the GitHub README for setup instructions.
Five weighted categories — click any category to see the underlying evidence.
No known CVEs.
No package registry to scan.
This server is missing a description. Tools and install config are also missing.If you've used it, help the community.
Add informationBe the first to review
Have you used this server?
Share your experience — it helps other developers decide.
Sign in to write a review.
Others in ai-ml / finance / analytics
A Model Context Protocol (MCP) server and CLI that provides tools for agent use when working on iOS and macOS projects.
Dynamic problem-solving through sequential thought chains
A Model Context Protocol server for searching and analyzing arXiv papers
MCP Server for GCP environment for interacting with various Observability APIs.
MCP Security Weekly
Get CVE alerts and security updates for io.github.mdfifty50-boop/agent-costcenter and similar servers.
Start a conversation
Ask a question, share a tip, or report an issue.
Sign in to join the discussion.
MCP server for per-agent cost attribution and budget management. Answer "which agent costs the most?" across your entire AI agent fleet.
npx agent-costcenter-mcp
{
"mcpServers": {
"agent-costcenter": {
"command": "npx",
"args": ["agent-costcenter-mcp"]
}
}
}
| Tool | Description |
|---|---|
register_agent | Register agent with team, project, model, and budget cap |
log_llm_call | Log an LLM call — auto-calculates cost from pricing table |
log_tool_call | Log a tool/API call cost |
get_cost_report | Cost breakdown by agent, team, project, or all |
set_budget_alert | Set spending threshold (warn or block) |
check_budget | Check if agent is within budget |
get_cost_anomalies | Find agents with unusual spending spikes |
compare_models | Compare cost efficiency across models |
| URI | Description |
|---|---|
costcenter://summary | Current total spend across all agents |
costcenter://pricing | 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 mode
MIT