mcpField
B
BrainChain

BrainChain

Local
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About BrainChain

Hire frontier models through Jev, paying USDC on Base or USDG on Robinhood Chain for accepted work

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
  "mcpServers": {
    "com-usebrainchain-brainchain": {
      "command": "npx",
      "args": [
        "-y",
        "brainchain-mcp"
      ],
      "env": {
        "BRAINCHAIN_PAYER_KEY": "<BRAINCHAIN_PAYER_KEY>",
        "BRAINCHAIN_NETWORK": "<BRAINCHAIN_NETWORK>",
        "BRAINCHAIN_PAY_ON": "<BRAINCHAIN_PAY_ON>",
        "BRAINCHAIN_MAX_PRICE_UNITS": "<BRAINCHAIN_MAX_PRICE_UNITS>",
        "BRAINCHAIN_BUDGET_UNITS": "<BRAINCHAIN_BUDGET_UNITS>"
      }
    }
  }
}
Run commandnpx -y brainchain-mcp
Environment variables to set
BRAINCHAIN_PAYER_KEYSecretPrivate key of the wallet that pays for tasks (0x followed by 64 hex characters). Use a dedicated wallet.
BRAINCHAIN_NETWORKmainnet or testnet. Testnet pays with test tokens that have no value.
BRAINCHAIN_PAY_ONrobinhood pays in USDG on Robinhood Chain after a one-time Permit2 approval; base pays in USDC on Base (Base Sepolia on testnet) with a signature alone.
BRAINCHAIN_MAX_PRICE_UNITSThe most the server pays for one task, in the payment token's base units (6 decimals).
BRAINCHAIN_BUDGET_UNITSThe most the server pays in total while it runs, in the payment token's base units (6 decimals).

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
npmbrainchain-mcp0.2.1

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

The maintainer has not added details yet. Check the README in the repository.

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.