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parallelix-mcp

v0.1.1

Published

MCP server for the ParalleliX Compute API. Offload parallel inference sub-tasks to a distributed GPU network, paid in $PRLX credits.

Readme

parallelix-mcp

An MCP (Model Context Protocol) server for the ParalleliX Compute API. It gives an MCP client (Claude Code, Claude Desktop) tools to offload parallel inference sub-tasks to the ParalleliX network, paid in $PRLX credits.

The pattern: your frontier agent orchestrates and reasons; the distributed open-source fleet runs the cheap, embarrassingly-parallel parts. Bulk classify, extract, summarize, or translate hundreds of items in one parallel_map call instead of burning frontier tokens on a loop.

What you need

  1. An API key. Create one in the ParalleliX app under Developers (connect a wallet, add $PRLX credits, create a key). The key looks like pk_live_… and is shown once.
  2. Node 18 or newer.

Tools

  • parallel_map(items, instruction, model?) Run the same instruction over many items in parallel across the network. Returns one result per item with a Proof-of-Execution hash.
  • infer(prompt, model?) Run a single prompt on the network. Returns the completion, the serving node id, and its PoE hash.
  • network_status() List the models the network currently serves.
  • usage() Show this key's request count, $PRLX credits spent, and remaining balance.

Use with Claude Desktop

Add this to claude_desktop_config.json:

{
  "mcpServers": {
    "parallelix": {
      "command": "npx",
      "args": ["-y", "parallelix-mcp"],
      "env": {
        "PARALLELIX_API_KEY": "pk_live_your_key_here"
      }
    }
  }
}

Use with Claude Code

claude mcp add parallelix --env PARALLELIX_API_KEY=pk_live_your_key_here -- npx -y parallelix-mcp

Configuration

| Env var | Required | Default | Notes | | --- | --- | --- | --- | | PARALLELIX_API_KEY | yes | none | Your pk_live_… key. | | PARALLELIX_BASE_URL | no | https://api.parallelix.io | Point at a local coordinator for testing. |

Honest notes

  • The network runs open-source models (currently 7B-class, e.g. qwen2.5:7b). It is not a frontier model and is not meant to replace one. It is a cheap parallel executor for bulk independent sub-tasks.
  • Capacity is real and finite. Large batches queue; usage and network_status show you what's available.
  • Credits are metered off-chain by the coordinator (deposit $PRLX once on-chain, no per-call gas). v1 is custodial.

License

MIT