mcpField
A

Animica

Local
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About Animica

Animica chain data, free keyless AI inference, quantum randomness, x402 discovery, mining stats

Configuration

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

mcp.json · Universal config
{
  "mcpServers": {
    "dev-animica-animica": {
      "command": "uvx",
      "args": [
        "animica-mcp"
      ],
      "env": {
        "ANIMICA_API_KEY": "<ANIMICA_API_KEY>",
        "ANIMICA_RPC_URL": "<ANIMICA_RPC_URL>",
        "ANIMICA_BASE_URL": "<ANIMICA_BASE_URL>",
        "ANIMICA_POOL_URL": "<ANIMICA_POOL_URL>",
        "ANIMICA_BEACON_URL": "<ANIMICA_BEACON_URL>",
        "ANIMICA_MODEL": "<ANIMICA_MODEL>",
        "ANIMICA_MCP_TIMEOUT_S": "<ANIMICA_MCP_TIMEOUT_S>"
      }
    }
  }
}
Run commanduvx animica-mcp
Environment variables to set
ANIMICA_API_KEYSecretOptional Animica API key (anm_live_...) for higher AI rate limits. The server works without it.
ANIMICA_RPC_URLAnimica node JSON-RPC endpoint (read-only allow-listed methods only).
ANIMICA_BASE_URLOpenAI-compatible /v1 base URL used for AI inference (chat, models, embeddings). https://animica.dev/v1 is the free keyless endpoint.
ANIMICA_POOL_URLMining-pool stats API base URL.
ANIMICA_BEACON_URLQuantum randomness beacon base URL (/beacon/* endpoints).
ANIMICA_MODELDefault model id for the animica_ai_ask tool.
ANIMICA_MCP_TIMEOUT_SHTTP timeout in seconds for backend calls. The network is volunteer-served, so allow generous time.

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
pypianimica-mcp0.2.2

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.