AgentKavach
AgentKavach is a budget enforcement platform for AI agents that prevents runaway spending on large language model (LLM) API calls. It provides a Python SDK that wraps existing LLM clients from OpenAI, Anthropic, Google, and Mistral, intercepting every request to track token usage and cost in real time. Users define hard budget limits (daily, monthly, or total) per agent, and when the limit is reached, a configurable kill switch fires—optionally executing a user-defined callback to halt the agent. The platform also offers escalating alert notifications via email, Slack, PagerDuty, or webhooks at customizable thresholds (e.g., 50%, 80%, 95%, 100%). AgentKavach includes team dashboards that visualize spending across all agents and models, allowing teams to drill into usage trends and alert history. It supports organization-wide budget pools that can be shared among multiple agents, defined either programmatically or via YAML configuration files. Additional guardrails such as token limits, call count caps, runtime limits, and runaway loop detection help prevent abuse. The service is designed with security in mind, using TLS, API key authentication, rate limiting, and HMAC signing. AgentKavach claims not to store or log prompt or completion data, using only metadata for cost tracking.
- Category
- AI Agents
- Pricing
- Paid
Problem solved
Developers and teams using LLM APIs face unpredictable costs when autonomous agents make unbounded calls, potentially leading to massive bills. AgentKavach imposes hard budget limits with automatic shutdown, ensuring spending never exceeds defined thresholds.
Use cases
- Set daily spending limits for production AI agents
- Receive real-time Slack/email/PagerDuty alerts when agent costs exceed thresholds
- Implement emergency kill switches for runaway agents
- Consolidate cost tracking across multiple LLM providers in a single dashboard
- Define organization-wide budgets for all agents using YAML configuration
Audience
- Developers
- ML Engineers
- Product Managers
- Enterprise
- Startups
Pros
- Enforces hard budget limits with kill switch
- Supports multiple LLM providers (OpenAI, Anthropic, Google, Mistral) via one SDK
- Real-time alerts via Slack, email, PagerDuty, and custom webhooks
- Simple Python integration with low latency overhead
- Team dashboards for monitoring agent spending and trends
Cons
- Requires paid subscription for production use beyond free tier (3 agents, 1k events/day)
- Adds external dependency on AgentKavach service for budget enforcement
- Event limits on free and Pro plans may be insufficient for high-volume agents
- Only Python SDK available; no support for other languages
- Potential privacy concerns as requests are proxied through their service (though they claim no data logging)
Official website: https://www.agentkavach.com/
Canonical LambdaBase page: https://www.lambdabase.com/tools/agentkavach