# Arcade Agent MCP Lets any MCP-capable AI agent (Claude Desktop, Claude Code, etc.) use **Arcade** — a USDC-native DEX + bonding-curve launchpad on Circle's **Arc** L1. The agent discovers markets, gets best-execution quotes, and receives **ready-to-sign contract-call descriptors**. The agent signs them with its **own wallet** (e.g. a Circle developer-controlled wallet via `createContractExecutionTransaction`). This server never holds keys. ## Configure (Claude Desktop / Claude Code) Add to your MCP config (no install needed, `npx` fetches it): ```json { "mcpServers": { "arcade": { "command": "npx", "args": ["-y", "arcade-agent-mcp"], "env": { "ARCADE_API_BASE": "https://www.arcade.trading" } } } } ``` `ARCADE_API_BASE` defaults to `https://www.arcade.trading`; point it at `http://localhost:3000` for local dev. **From source** (development): `git clone https://github.com/obseasd/arcade-agent-mcp && cd arcade-agent-mcp && npm install`, then use `"command": "node", "args": ["/absolute/path/to/index.mjs"]`. ## Tools | Tool | What it does | |------|--------------| | `arcade_markets` | reference tradeable tokens on Arc | | `arcade_trending` | launchpad tokens by market cap | | `arcade_portfolio` | known-token balances for a wallet | | `arcade_quote` | best-execution price quote (read-only) | | `arcade_swap` | build approve + swap descriptors to sign | | `arcade_launchpad` | build bonding-curve buy/sell or create-token descriptors | | `arcade_multiswap` | build a basket-converge swap (aggregator) | ## How an agent executes a build result Every build tool returns `{ ok, executable, calls: [...] }` where each call is: ```json { "contractAddress": "0x...", "abiFunctionSignature": "swapExactTokensForTokens(uint256,uint256,address[],address,uint256)", "abiParameters": ["1000000", "990000", ["0x...","0x..."], "0xAGENT", "1750000000"] } ``` Feed each call, in order, to Circle's `createContractExecutionTransaction` (blockchain `ARC-TESTNET`, your agent wallet). Run the `approve` call first, then the action call. See `../docs/AGENT_API.md` for the full architecture and a worked example.