Letting an AI agent use paid external services always gets stuck at the same place: arranging payment. One contract for a search API, another for data retrieval, another for image generation ─ contracts and API keys pile up, and the invoices scatter. Vaaya takes over that entry point as a “credit account for agents.” It calculates a credit line from your public GitHub activity history and issues a credit account for agents without requiring a credit card. Its defining trait is that search, data, LLM inference, image and video generation, scraping, and compute ─ a large number of providers ─ can all be called on a usage-based basis through a single MCP / API connection.
Key Features
- A credit line calculated from public GitHub activity: Public contributions, merged pull requests, issues, and account age are turned into a score from 300 to 850, and an unsecured credit line (up to $5,000) is issued. No access to private repositories and no write permissions are requested
- Many providers consolidated into one account: LLM routers, web search and scraping, lead and company data, image, video, and audio generation, browser automation, sandbox and GPU compute, storage, and more can be called without individual contracts
- Spending controls the human side sets: You can set a monthly cap per key (per agent), a per-call cap, and the categories that may be used. A price is quoted before each call, and failed calls are not billed
- Both MCP and HTTP API: A remote MCP server (OAuth 2.1 + PKCE), a local stdio connection via
npx @vaaya/mcp install, and direct HTTP API calls are all supported. Coding agents such as Claude Code, Cursor, and Codex can use it as-is - Automatic selection of payment rails: Several payment methods ─ x402 (USDC on Base), MPP, and ordinary provider accounts ─ are chosen automatically on the backend, while the user sees only a single balance and transaction history
- A unified ledger and repayment management: Every call is recorded together with the provider, the price, the result, and the agent that made it. Charges are collected from the card on file weekly, or once the balance passes $50
Pricing
There is no fixed monthly subscription; you pay only the actual cost of each call. Three ways to fund the account are provided.
| How to fund | Amount | Notes |
|---|---|---|
| Welcome credit | $2 for a personal account / $10 for an Instinct account | Can be started without registering a card |
| Prepaid packs | $10 / $30 / $100 | Purchased upfront. No expiry |
| GitHub-linked credit line | Starts at roughly $0–$150 depending on the score, expanding up to $5,000 | Requires a card on file to begin using |
As a rough guide to per-call prices: LLM responses start around 0.1 cents, web search and scraping cost about 1 cent, deep research runs 10–30 cents, media generation such as images starts around 33 cents, and compute is billed by the second. Only when an agent registers itself does it receive a $1 starter credit (expiring in 24 hours) as a trial allowance until the account’s owner is confirmed.
Pricing is as of September 2026. Unit prices vary by provider, so please check the official site for the latest details.
Pros & Cons
✅ Pros
- You are freed from managing per-provider contracts, API keys, and invoices, and expense handling comes down to a single line
- You can start trying paid services on your GitHub track record alone, without putting up funds first
- Because the caps and categories stay in human hands, you can hand an agent a wallet and let it run without worrying about runaway charges
- Failed calls are not billed, so trial-and-error during development does not generate wasted spending
- The ledger records which agent spent how much on what, so usage can be audited afterwards
⚠️ Cons
- Because the credit line depends on public GitHub activity, individuals and organizations with little GitHub presence will start from close to zero
- The credit line tops out at $5,000, so large corporate usage will likely need a separate conversation
- Some payments go through crypto rails such as x402 (USDC / Base), which can feel opaque to users unfamiliar with crypto
- There is no separate sandbox mode for testing; the design has you make real, billable calls using the welcome credit
- Both the company and the product only launched in 2026, so the operational track record is still building
Comparison with Similar Services
| Service | How it differs from Vaaya |
|---|---|
| Skyfire | An agent-to-service payment network built around agent identity verification (KYA) and payments (KYAPay). It starts from signed identities rather than the GitHub-based credit Vaaya uses |
| Coinbase x402 | A crypto-native payment protocol based on USDC / Base. Vaaya uses x402 as one of its internal payment rails while layering an integrated provider catalog and credit on top |
| Crossmint | Offers agent payments as a multi-chain Web3 wallet platform. GitHub-based credit and consolidating a service catalog are not its focus |
Who Is It For
- AI product teams that want their agents to use usage-based services such as search, data, and generative AI without per-vendor contracts
- Development teams that want to give internal agents a budget for research, scraping, and infrastructure while keeping control
- Solo developers who want to try paid tools from Claude Code, Cursor, or Codex without juggling multiple paid API keys and billing accounts
- Businesses that want to audit transaction history in one place while enforcing a spending policy on autonomously running agents
Summary
Once you reach the stage of delegating real work to agents, the next thing that trips you up is how to hand over payment. Vaaya turns public GitHub activity into credit material so you can take that first step without a card or an upfront deposit. Since caps and categories remain in human hands, much of the fear around automatic execution falls away. On the other hand, it is worth keeping in mind that the service is newly launched and that the credit line hinges on how much GitHub activity you have. A sensible start is to make a few real calls from your own agent within the welcome credit and see how the ledger reads and how the cap settings feel to operate.