AI agent substrate: spend caps, rate limits, idempotency, reconciliation, approval bridges
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag β we're steadily working through the catalog.
π‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Spend caps, rate coordination, idempotency, and a human-in-the-loop gate for AI agents β enforced before the call, not after the invoice. One MCP endpoint, settled via x402 (USDC on Base). No proxy, no self-hosting, no infrastructure to deploy.
Listed on the Official MCP Registry as dev.gvnr/gvnr.
Agents cost 10β12Γ more than estimated in production. System prompts, retry loops, and tool calls multiply fast β a runaway agent can generate a $47,000 bill in 11 days. The usual fix, self-hosting a gateway like LiteLLM, means running infrastructure most developers won't set up.
Gvnr is the hosted alternative: an external authority your agent checks before it spends. Your agent asks "am I clear to make this call?" and acts on the answer.
Gvnr is not an LLM proxy β your tokens never pass through it, and you pay your model provider directly. Gvnr governs the decision to spend, in two independent meters:
1. The governance-operation quota β what you buy from Gvnr.
Your account holds a balance of governance operations (operations_remaining). One budget_clear burns one op. You top this up with USDC; it's decoupled from your LLM spend. get_balance reports it.
2. The spend envelope β a USD cap you set, per agent.
set_envelope(agent_id, limit_usd, window) gives an agent a daily or per-session USD ceiling. Gvnr tracks estimated spend against it and denies once it's exceeded β this is the runaway guardrail. No dollars move; it's an accounting limit you control.
A budget_clear is approved only when both hold: the account has ops left in the quota, and the agent is under its envelope. The loop:
budget_clear(agent_id, model, estimated_tokens) before each LLM request.{ approved: true, ... } or { approved: false, reason }.request_approval).reconcile(...) with the real token counts so the envelope tracks actual cost, not the estimate.New accounts include 25 free trial ops β enough to run the full loop (set an envelope, budget_clear, reconcile) before you fund anything. Your api_key is the credential for every call; account_id is just an internal reference for support. Account creation is credential-only by design (agent-native) β email is optional, set separately via POST /v1/account/notification-email, and used only for human approval notices.
Pay-as-you-go: 1,000 ops per $1, any amount (try the whole rail for $1), USDC on Base. Open the pay page, name your amount, and pass your API key:
Send USDC to the address shown and paste your tx hash β ops are credited proportional to the amount received, after on-chain verification. Programmatic clients can submit the hash directly:
Or settle in one round-trip with an x402 client (Base MCP, AgentKit, x402-fetch) β name your own amount:
budget_clear, then rate_checkidempotency_checkreconcile adjusts the spend envelope by the drift between your estimate and actual cost (the op quota is untouched). You don't pass the model again β reconcile reuses the one from your prior budget_clear. Anthropic, OpenAI, and Gemini all return usage fields with real token counts β pass those in to keep the envelope honest.
When an agent hits a denial or a sensitive action, pause for a human instead of failing:
The agent proceeds on approved, skips on denied, and handles timeout (no decision before expires_at) however it likes.
Add to Claude Desktop or any MCP-compatible client:
| Tool | Description |
|---|---|
budget_clear(agent_id, model, estimated_tokens) | Check clearance against the op quota + spend envelope; burns one op |
set_envelope(agent_id, limit_usd, window?) | Create or update an agent's USD spend cap |
get_balance() | Remaining governance-operation quota (operations_remaining) |
reconcile(agent_id, actual_input_tokens, actual_output_tokens) | Apply estimate-vs-actual drift to the spend envelope after the LLM responds |
set_rate_envelope(agent_id, provider, model, requests_per_minute) | Allocate a per-(agent, provider, model) rate share |
rate_check(agent_id, provider, model) | Approve or deny against the rate envelope; returns retry_after_ms on denial |
idempotency_check(key, ttl_seconds?) | Dedupe retries on a caller-supplied key; returns is_first_call |
request_approval(agent_id, action_summary, ttl_seconds?) | Open a human-in-the-loop approval request; returns an approval_id |
check_approval(approval_id) | Poll an approval: pending / approved / denied / timeout |
All endpoints except POST /v1/account require Authorization: Bearer bg_YOUR_KEY.
TypeScript users: generate full types from the live OpenAPI spec β npx openapi-typescript@latest https://gvnr.dev/openapi.json -o types/gvnr.d.ts. See TYPESCRIPT.md for the integration pattern (typed fetch, x402 topups, discriminated response unions).
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