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Agentpay

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Budget-capped x402 payments for AI agents: verifiable receipts, trust routing, 17 free tools.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "agentpay-5": {
      "command": "npx",
      "args": [
        "-y",
        "agentpay-5"
      ]
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing AlternativesπŸ’° More in Finance & Fintech

Documentation Overview

AgentPay

Tests PyPI Python License: MIT MCP Live gateway x402-list

Most agent-payment tools are a wallet β€” they move money. AgentPay is the layer that decides whether to spend it at all.

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 β€” 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 β€” 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 β€” 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: 20 tools (17 free), no USDC needed, no wallet setup required.
Live gateway: https://agentpay.tools


Install

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

Quickstart β€” 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.

server.ts
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:

python
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.


20 Tools (17 Free + 3 Paid)

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

ToolParametersReturns
url_readerurlClean markdown content of any web page
web_searchqueryTop 5 results with full content
market_snapshotβ€”S&P 500, Treasury yield, BTC, ETH, gas in one call
token_pricesymbol (BTC, ETH, SOL…)price_usd, change_24h_pct, market_cap_usd
gas_trackerβ€”slow/standard/fast gwei, base_fee_gwei
fear_greed_indexlimit (days of history, default 1)value 0–100, value_classification, history[]
token_market_datatoken_a, token_bvolume_24h_usd, market_cap_usd, price_usd
wallet_balanceaddress, chain (ethereum/stellar)token balances
whale_activitytoken, min_usd (default 100k)large_transfers[] with direction, total_volume_usd
defi_tvlprotocol (optional, e.g. "uniswap")tvl, change_1d, change_7d, chains[]
token_securitycontract_address, chainrisk_level, is_honeypot, buy_tax, sell_tax
open_interestsymbol (BTC, ETH…)total_oi_usd, oi_change_1h/24h_pct, long_short_ratio
orderbook_depthsymbol (e.g. ETHUSDT)best_bid/ask, spread_pct, slippage at $10k/$50k/$250k
funding_ratesasset (optional)funding_rate_pct, annualized_rate_pct, sentiment per exchange
crypto_newscurrencies (e.g. "ETH,BTC"), filterheadlines[] with title, url, sentiment, score
yield_scannertoken, chain (optional), min_tvltop 10 pools by APY with protocol, tvl_usd, risk_level
dune_queryquery_id, limit, fast_onlyrows[], columns[], row_count from Dune Analytics
session_createagent_address, max_spend, labelsession_id, budget config, gateway_url, receipt β€” $0.01
pre_trade_checksymbol, size_usd, side, token_address?one-call trade verdict (ok/caution/avoid): slippage at YOUR size, side-aware funding carry, OI crowding, optional security β€” $0.01
verified_routeneed, budget_usd?, chain?buyer-side trust oracle: sweeps the x402 marketplace, collapses sybil/factory clusters, ranks real providers by usage Γ— delivery scores β†’ one vetted recommendation + ready_to_pay challenge β€” $0.01

Session Intelligence

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

server.ts
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.
# Budget caps are exact: max_spend=0.10 (float) == "0.10" (str).
with quickstart(max_spend=0.10) as session:

    # Price an entire multi-tool plan BEFORE spending anything (free, no wallet)
    plan = session.estimate_plan(["token_price", "pre_trade_check", "session_create"])
    plan["total_usdc"], plan["fits_budget"]   # per-step costs + cheaper alternatives inside

    # Reason about cost before committing (use the *_usd Decimals for comparisons)
    if session.would_exceed(session.tool_cost_usd("dune_query")):
        alt = session.suggest_cheaper("dune_query")   # {"name": ..., "price": ...}

    # Call a tool β€” budget enforced before any payment is signed
    r = session.call("token_price", {"symbol": "ETH"})
    r.data["price_usd"]    # inner tool output  (r["result"]["price_usd"] still works)
    r.cost                 # payment amount, e.g. "0"
    r.network              # settlement chain, e.g. "stellar-mainnet" / "base"

    session.remaining_usd()   # Decimal('0.10')

    # For an external x402 tool that offers several chains, pick one:
    # session.call("https://some-x402-tool/endpoint", {}, chain="base")

    # Full receipt β€” every call, cost, tx hash, and settlement chain
    print(session.spending_summary())
    # {
    #   "calls": 1, "spent": "$0", "remaining": "$0.1", "budget": "$0.1",
    #   "breakdown": [
    #     {"tool": "token_price", "cost": "Free", "tx_hash": "", "network": "stellar-mainnet"}
    #   ]
    # }

Policy parameters

Control exactly what your agent is allowed to do:

server.ts
from agentpay import AgentWallet, Session

wallet = AgentWallet(secret_key="S...", network="mainnet")   # or quickstart()'s minted wallet
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,                # max 10 calls/min
             prefer_chain="base") as session:   # Base is the default; pass "stellar" to override
    ...

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.


Example: Market intelligence agent

Five free tools, one session, full receipt.

server.ts
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())

Use it in your agent

Agent Skills (one command, any agent)

Terminal
npx skills add romudille-bit/agentpay

Installs the agentpay-route skill (find, judge, and pay for the best paid x402 tool within a budget) and agentpay-session (hard spend cap + verifiable receipts) into Claude Code, Codex, Droid, OpenCode, or any skills-CLI-compatible runtime. Pair with the MCP below for keyless routing out of the box; add AGENTPAY_BASE_KEY + AGENTPAY_MAX_SPEND for capped, in-place paid calls.

Claude Code plugin (one command)

Code
/plugin marketplace add romudille-bit/agentpay
/plugin install agentpay@agentpay

Read the full README β†’View source on GitHub β†’

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Reviews

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Frequently Asked Questions about Agentpay

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "agentpay": { "command": "npx", "args": ["-y", "agentpay"] } }

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Technical Specs & Signals

CategoryπŸ’°Finance & Fintech
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimeNode.js
Last updatedSep 7, 2026
Views0
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Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
27Quality signal: Emerging Β· 27/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership8/20
Documentation & tools11/30
Adoption & activity1/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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