Waifu Queue MCP Server

Generates asynchronous text responses using a distilgpt2 model, managed through a Redis queue and accelerated with GPU support, exposing an

Local serverstdioPython★ 1

What is the Waifu Queue MCP Server?

Generates asynchronous text responses using a distilgpt2 model, managed through a Redis queue and accelerated with GPU support, exposing an MCP-compliant API.

What the server does

This project implements an MCP (Model Context Protocol) server for a conversational AI "waifu" character, leveraging the OpenRouter API via a Redis queue for asynchronous processing. It utilizes the FastMCP library for simplified server setup and management.

  • Text generation via OpenRouter using model from ~/.model-openrouter or openrouter/free
  • Request queuing using Redis for handling concurrent requests asynchronously
  • MCP-compliant API using FastMCP
  • Job status tracking via MCP resources
  • Configuration via environment variables (.env file)
  • API key loading:

Credentials and setup notes

  • Python 3.7+ * pip or uv (Python package installer) * Redis server (installed and running) * An OpenRouter API Key You can find instructions for installing Redis on your system on the official Redis website: https://redis.io/docs/getting-started/ You can obtain an OpenRouter API key from: https://openrouter.ai/

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Maintainer setup documentation.

Configuration

  • Python 3.7+ * pip or uv (Python package installer) * Redis server (installed and running) * An OpenRouter API Key You can find instructions for installing Redis on your system on the official Redis website: https://redis.io/docs/getting-started/ You can obtain an OpenRouter API key from: https://openrouter.ai/
VariableDescriptionRequired
OPENROUTER_API_KEYCredential the server authenticates with.Yes
REDIS_URLEndpoint or connection string the server talks to.Yes

Example prompts to try

  • “Use Waifu Queue to Description.”
  • “Use Waifu Queue to Input.”
  • “Use Waifu Queue to Output.”

Frequently asked questions

While not strictly required, a CUDA-enabled GPU is highly recommended for significantly faster text generation.