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Purple Flea MCP: Add 6 Financial Tools to Any AI Agent in One Config

#ai #mcp #crypto #agents

Purple Flea MCP: Add 6 Financial Tools to Any AI Agent in One Config

MCP (Model Context Protocol) lets AI agents discover and call tools at runtime. Purple Flea exposes all 6 of its financial services as MCP endpoints — which means any MCP-compatible agent framework can use them without writing a single line of integration code.

Here is the full config:

{
  "mcpServers": {
    "purpleflea-casino": {
      "url": "https://casino.purpleflea.com/mcp"
    },
    "purpleflea-trading": {
      "url": "https://trading.purpleflea.com/mcp"
    },
    "purpleflea-wallet": {
      "url": "https://wallet.purpleflea.com/mcp"
    },
    "purpleflea-domains": {
      "url": "https://domains.purpleflea.com/mcp"
    },
    "purpleflea-faucet": {
      "url": "https://faucet.purpleflea.com/mcp"
    },
    "purpleflea-escrow": {
      "url": "https://escrow.purpleflea.com/mcp"
    }
  }
}
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Add that to your mcp.json (or equivalent config for your runtime), and your agent immediately has access to:

  • Casino tools: place_bet, get_balance, verify_outcome, get_referral_code
  • Trading tools: open_position, close_position, get_pnl, set_stop_loss, copy_trade
  • Wallet tools: get_addresses, send_funds, check_balance, swap_assets
  • Domains tools: search_domain, purchase_domain, add_dns_record
  • Faucet tools: register_agent, claim_credits, check_claim_status
  • Escrow tools: create_escrow, deposit_funds, release_funds, dispute_escrow

Why MCP?

The REST APIs are available too — but MCP gives your agent something REST cannot: self-describing tools. When an LLM calls an MCP server, it gets back a schema describing what each tool does, what parameters it accepts, and what it returns. The agent can then decide which tool to call based on the task at hand.

This is especially powerful for financial tasks. An agent working on "maximize returns" can evaluate whether to call place_bet, open_position, or create_escrow — based on context, risk parameters, and available balance — without any hard-coded logic.

Claude Example 

import anthropic

client = anthropic.Anthropic()

# Claude will discover Purple Flea tools from the MCP servers
# configured in your environment
response = client.messages.create(
    model="claude-opus-4-6",
    max_tokens=1024,
    messages=[{
        "role": "user",
        "content": "Check my Purple Flea wallet balance, then if I have more than 10 USDC, place a coinflip bet for 1 USDC."
    }]
)
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With the MCP config above, Claude will automatically discover get_balance from the wallet server and place_bet from the casino server, then chain them appropriately.

Smithery Registration

Both the faucet and escrow MCP servers are registered on Smithery:

Smithery-compatible runtimes can discover these automatically without manual config.

Getting Started

  1. Visit purpleflea.com and register
  2. Get your API key
  3. Add the MCP config above to your agent framework
  4. Start with the faucet — claim free credits to test without risk

All 6 services, one config block. That is the whole onboarding flow.

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