#cost-control

Marchward is an Apache-2.0 open-source runtime authority for AI agents. It routes an agent's tool calls through one control point: credential mediation (the agent holds a single Marchward key and never your real downstream credentials), an inference spend cap enforced before the call reaches the provider, human-in-the-loop approval gates on irreversible actions, and a tamper-evident hash-chained audit log. Public repo and packages are live (npm @marchward/*, PyPI marchward, official MCP registry ai.marchward/mcp-server), with a runnable governed-LangGraph example in the repo.

Budget & cost control for AI agents: hard per-agent spend caps, rate limits, idempotency, and human-in-the-loop approval — enforced before each LLM call, not after the invoice. One hosted MCP endpoint (no proxy or self-hosting), settled via x402 (USDC on Base).

Preflight spend control for AI agents. Block runaway agent loops before they start - not after the bill arrives. Per-request cost ceilings, budget checks, and outcome-based metering in 2 MCP tool calls.

AI agents call LLMs, invoke tools, and hit APIs — but have no built-in way to cap spend. A single agent loop can burn hundreds of dollars before anyone notices. Cycles MCP Server gives any MCP-compatible agent a runtime budget authority: tools to check, reserve, spend, and release budget before and after every costly operation. Works with Claude Desktop, Claude Code, Cursor, Windsurf, and any MCP host. Supports per-tenant budgets, soft-landing caps, and automatic heartbeat for long-running operations.

Prevents runaway cloud costs from AI agent usage. Enforces hard budget limits with configurable actions: throttle, pause, alert, or kill. Spend projection and webhook alerts.