agentpay-x402 0.2.2

Economic intelligence for AI agents — quickstart() in one line, 17 free tools, hard budget caps, session receipts, x402 on Stellar or Base

AgentPay —

If you are wondering how autonomous software entities discover, trust, pay, meter, and coordinate with each other safely —

AgentPay is the economic intelligence layer for MCP servers and AI agents.

Agents spend money. Most don't know how much, or why, until the session ends and the bill arrives.

AgentPay gives agents economic intelligence — the ability to reason about cost while they work, not after.

It starts with a budget. Every session opens with a hard cap enforced at the payment layer — not in code a model can ignore, but at the point where money moves. The agent knows from the first call exactly what it has to spend.

Before calling a tool, it knows what that call costs. Mid-task, it can check what's left and route to a cheaper alternative if the math doesn't work. When the session ends, a receipt captures every call, every cost, every decision — not a debug log, but proof of economic accountability.

The developer sees all of it: spending patterns per agent, anomaly flags when something loops or spikes, policy controls that enforce exactly which tools an agent can use and how much it can spend on each.

The result is an agent that doesn't just have a budget. It knows how to use one.

Start free: 18 tools, no USDC needed, no wallet setup required.
Live gateway: https://agentpay.tools

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Install

pip install agentpay-x402            # core (Stellar)
pip install "agentpay-x402[base]"    # + pay tools that settle on Base

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Quickstart — 3 lines, zero setup

17 free tools. No USDC, no wallet, no API keys, no human. quickstart() registers an agent, mints a wallet, and returns a ready, budget-capped session.

from agentpay import quickstart

s = quickstart()                                   # registers + mints a wallet
print(s.call("token_price", {"symbol": "ETH"})["result"]["price_usd"])
print(s.spending_summary())                        # receipt: every call, cost, tx

Set a hard budget, or bring your own funded wallet to pay for tools:

s = quickstart(max_spend="0.50")                   # cap this run at $0.50
s = quickstart(secret_key="S...", base_key="0x...")  # your wallet (Stellar + Base)

Every call is session-tracked, and the cap is enforced before any payment is signed.

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18 Tools (17 Free)

Every call is session-tracked — you get a receipt showing every tool called, every cost, and every timestamp.

Tool	Parameters	Returns
url_reader	url	Clean markdown content of any web page
web_search	query	Top 5 results with full content
market_snapshot	—	S&P 500, Treasury yield, BTC, ETH, gas in one call
token_price	symbol (BTC, ETH, SOL…)	price_usd, change_24h_pct, market_cap_usd
gas_tracker	—	slow/standard/fast gwei, base_fee_gwei
fear_greed_index	limit (days of history, default 1)	value 0–100, value_classification, history[]
token_market_data	token_a, token_b	volume_24h_usd, market_cap_usd, price_usd
wallet_balance	address, chain (ethereum/stellar)	token balances
whale_activity	token, min_usd (default 100k)	large_transfers[] with direction, total_volume_usd
defi_tvl	protocol (optional, e.g. "uniswap")	tvl, change_1d, change_7d, chains[]
token_security	contract_address, chain	risk_level, is_honeypot, buy_tax, sell_tax
open_interest	symbol (BTC, ETH…)	total_oi_usd, oi_change_1h/24h_pct, long_short_ratio
orderbook_depth	symbol (e.g. ETHUSDT)	best_bid/ask, spread_pct, slippage at $10k/$50k/$250k
funding_rates	asset (optional)	funding_rate_pct, annualized_rate_pct, sentiment per exchange
crypto_news	currencies (e.g. "ETH,BTC"), filter	headlines[] with title, url, sentiment, score
yield_scanner	token, chain (optional), min_tvl	top 10 pools by APY with protocol, tvl_usd, risk_level
dune_query	query_id, limit, fast_only	rows[], columns[], row_count from Dune Analytics
session_create	agent_address, max_spend, label	session_id, budget config, gateway_url, receipt — $0.001

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Session Intelligence

This is the economic intelligence layer in practice. The Session gives your agent — and you — real visibility into what happened, what it cost, and why.

from agentpay import quickstart, BudgetExceeded

# quickstart() registers + mints a wallet; the returned session is also a
# context manager, so you can `with` it for a printed receipt on exit.
with quickstart(max_spend="0.10") as session:

    # Check cost before committing
    session.tool_cost("dune_query")        # "Free"
    session.remaining()                    # "$0.1"

    # Find a cheaper alternative if needed
    alt = session.suggest_cheaper("dune_query")
    # {"name": "token_price", "price": "Free"}

    # Call tools — budget enforced automatically
    result = session.call("token_price", {"symbol": "ETH"})

    # Full receipt after any call
    print(session.spending_summary())
    # {
    #   "calls": 1,
    #   "spent": "$0",
    #   "remaining": "$0.1",
    #   "budget": "$0.1",
    #   "tools": ["token_price"],
    #   "breakdown": [{"tool": "token_price", "cost": "Free", "tx_hash": ""}]
    # }

Policy parameters

Control exactly what your agent is allowed to do:

with Session(wallet,
             gateway_url="https://agentpay.tools",
             max_spend="0.10",
             allowed_tools=["token_price", "gas_tracker", "web_search"],
             max_per_tool={"dune_query": 0.02},
             rate_limit=10) as session:    # max 10 calls/min
    ...

BudgetExceeded fires before any payment goes out if a tool would push you over the cap, isn't on the allowlist, or exceeds its per-tool limit.

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Example: Market intelligence agent

Five free tools, one session, full receipt.

from agentpay import quickstart

with quickstart() as session:

    snapshot = session.call("market_snapshot", {})
    rates    = session.call("funding_rates",    {"asset": "ETH"})
    oi       = session.call("open_interest",    {"symbol": "ETH"})
    fg       = session.call("fear_greed_index", {})
    whales   = session.call("whale_activity",   {"token": "ETH", "min_usd": 500_000})

    m = snapshot["result"]
    print(f"S&P:       {m['sp500_price']:,.0f}  ({m['sp500_change_pct']:+.2f}%)")
    print(f"ETH:       ${m['eth_price_usd']:,.0f}")
    print(f"Gas:       {m['gas_standard_gwei']} gwei")

    avg_rate = sum(e["funding_rate_pct"] for e in rates["result"]["rates"]) / len(rates["result"]["rates"])
    print(f"Funding:   {avg_rate:+.4f}%/8h")
    print(f"OI 24h:    {oi['result']['oi_change_24h_pct']:+.2f}%")
    print(f"Sentiment: {fg['result']['value_classification']}")
    print(f"Whale vol: ${whales['result']['total_volume_usd']:,.0f}")

    print(session.spending_summary())

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MCP Server

AgentPay ships an MCP server that gives Claude Desktop direct access to all 18 tools. 17 are free — no USDC required.

npx @romudille/agentpay-mcp

Or configure manually in claude_desktop_config.json:

{
  "mcpServers": {
    "agentpay": {
      "command": "python",
      "args": ["/path/to/agentpay/gateway/mcp_server.py"],
      "env": {
        "AGENTPAY_GATEWAY_URL": "https://agentpay.tools"
      }
    }
  }
}

Listed on Glama.

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Paid tool: session_create

One tool costs money today: session_create ($0.001 USDC per session). It opens a budget-capped session with a hard max_spend limit — for autonomous agents that need spend enforcement across multiple calls. All 17 data tools remain free.

When metered inference ships, it works through the same Session interface — your agent checks cost, decides if it's worth it, and pays in USDC on Stellar or Base.

# Future — inference as a Session tool
remaining = session.remaining()
infer_cost = session.tool_cost("inference")   # e.g. "$0.02"

if remaining >= infer_cost:
    result = session.call("inference", {"prompt": "...", "model": "claude-haiku"})
else:
    result = session.call("url_reader", {"url": summary_url})  # cheaper path

To fund a wallet for session_create: send USDC to a Stellar wallet (S... key, issuer GA5ZSEJYB37JRC5AVCIA5MOP4RHTM335X2KGX3IHOJAPP5RE34K4KZVN) or a Base wallet (0x..., contract 0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913).

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Architecture

AgentPay is an x402 payment gateway and economic intelligence layer — agents call tools within a hard budget cap, pay USDC on-chain when tools cost money, and accumulate a full session receipt as they work. Free tools skip the payment step entirely; the session tracking and cost awareness are always on.

agent (Python SDK)
    │
    │  POST /tools/{name}/call
    │  ← 200 {result: ...}              ← free tools return directly
    │  ← 402 {payment_id, amount, ...}  ← paid tools (inference, coming soon)
    │  → USDC on Stellar (~3–5s) or Base (~2s)
    │  → retry with X-Payment header
    │  ← 200 {result: ...}
    ▼
gateway (FastAPI on Railway)
    │
    ├── registry/registry.py   — 18-tool catalog (17 free, session_create $0.001)
    ├── gateway/stellar.py     — Stellar payment verification via Horizon
    ├── gateway/base.py        — Base payment verification via JSON-RPC
    └── gateway/services/tools_runtime.py — real API dispatchers
            ├── Jina Reader       url_reader
            ├── Jina Search       web_search
            ├── Yahoo+CoinGecko   market_snapshot
            ├── CoinGecko         token_price, token_market_data
            ├── Etherscan V2      gas_tracker, whale_activity, wallet_balance
            ├── DeFiLlama         defi_tvl, yield_scanner
            ├── alternative.me    fear_greed_index
            ├── Reddit            crypto_news
            ├── Dune Analytics    dune_query
            ├── GoPlus            token_security
            └── Binance+Bybit+OKX funding_rates, open_interest, orderbook_depth

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Discovery

Directory	Status
PyPI	✅ agentpay-x402
x402scout	✅ indexed, health-checked every 15min
Glama MCP	✅ listed
awesome-x402	✅ listed
npm	✅ @romudille/agentpay-mcp
402index.io	✅ domain verified, 17 tools synced
xpay.tools	🔜 submission in progress

Agent-readable endpoints:

Endpoint	Purpose
/.well-known/agentpay.json	AgentPay manifest
/.well-known/agent.json	A2A agent card
/llms.txt	LLM-readable service description
/.well-known/l402-services	402index.io discovery format