Cost Guard
Tracks API call costs and enforces spending limits within MCP environments. It logs usage data, calculates expenses based on provider rates, and interrupts excessive calls to avoid overruns. Developers and AI engineers use it to manage budgets in tool-integrated workflows.
Overview
Cost Guard is an MCP server that monitors and controls costs for API interactions in model context protocols. It integrates with MCP setups to track token usage, query volumes, and other billable metrics across connected tools and services, providing real-time cost visibility and automated safeguards.
Key Capabilities
- Cost tracking for API calls: Captures usage metrics and computes costs using configured provider pricing.
- Budget enforcement: Sets hard limits on spending and blocks further calls upon thresholds.
- Usage reporting: Exports logs and summaries for analysis and reconciliation with billing statements.
No specific endpoint tools are exposed; capabilities operate at the MCP server level to oversee all protocol traffic.
Use Cases
- Production AI deployments: Monitor OpenAI or Anthropic API costs in a chatbot service, halting queries when monthly budget hits 90% to prevent surprise invoices.
- Batch processing pipelines: Track costs during large-scale data analysis runs via MCP tools, generating daily reports for cost allocation across teams.
- Development testing: Enforce per-session budgets while prototyping with multiple AI providers, logging expenses to optimize tool selection.
- Multi-tenant apps: Isolate and limit costs per user in shared MCP environments, ensuring fair usage without overages.
Who This Is For
AI developers integrating paid APIs into applications, DevOps engineers managing cloud spending in model workflows, and teams running cost-sensitive LLM inference at scale.