llama-diffusion-mcp
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@llama-diffusion-mcp Chat with diffusion about the meaning of dreams"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Llama Diffusion MCP Bridge
A robust, bidirectional Model Context Protocol (MCP) server that allows Large Language Models (like Claude) to seamlessly interact with diffusion-based LLMs (e.g., DiffusionGemma, LLaDA, RND1) via llama-diffusion-cli.
✨ Features
Bidirectional Interactive Chat: Spawns and manages a persistent background instance of
llama-diffusion-clito maintain conversation context and avoid reloading heavy GGUF weights on every turn.Graceful Lifecycle Management: Includes tools for the LLM to cleanly terminate (
/exit) and restart the background process when you ask to start a new chat session.Zero-Setup Execution: Configured with
uvandpyproject.tomlso it can be run directly from the repository without manually managing virtual environments.Fully Configurable: Supports all standard
llama.cppdiffusion parameters (steps, algorithms, temperature, batch sizing) directly through initialization arguments.
Related MCP server: FLUX MCP Server
🛠️ Prerequisites
Python 3.10+
uv (Recommended package manager)
llama-diffusion-cli: Must be compiled from the
llama.cpprepository.
🚀 Quick Start & Installation
uv run --with git+https://github.com/hkbu-kennycheng/llama-diffusion-mcp.git llama-diffusion-mcp -hf unsloth/diffusiongemma-26B-A4B-it-GGUF:Q4_K_M -ngl 99 -n 128000
🔌 Connecting to Claude Desktop
To use this bridge with Claude Desktop (or any other MCP Client), add the server to your configuration file.
Path:
Mac:
~/Library/Application Support/Claude/claude_desktop_config.jsonWindows:
%APPDATA%\Claude\claude_desktop_config.json
Example Configuration (LLaDA 8B)
{
"mcpServers": {
"llama-diffusion-chat": {
"command": "uv",
"args": [
"run",
"--with", "git+https://github.com/hkbu-kennycheng/llama-diffusion-mcp.git",
"llama-diffusion-mcp",
"-hf", "unsloth/diffusiongemma-26B-A4B-it-GGUF:Q4_K_M",
"-ngl", "99",
"-n", "128000"
],
"env": {
"LLAMA_DIFFUSION_CLI_PATH": "/absolute/path/to/llama.cpp/build/bin/llama-diffusion-cli"
}
}
}
}
Note: Restart Claude Desktop after updating the config.
⚙️ Configuration Options
The MCP server accepts standard llama-diffusion-cli arguments:
Argument | Description |
| (Required) Path to the GGUF model file. |
| Run in interactive mode (Highly recommended for this bridge). |
| Context size. |
| Maximum sequence length (ubatch size). |
| Number of diffusion steps (e.g., 256). |
| Algorithm for token selection (0-4). |
| Temperature for sampling. |
Advanced MCP Settings
Argument | Description |
| The string the CLI prints when waiting for input (Default: |
| Environment variable pointing to your CLI executable. Defaults to |
🛠️ Exposed MCP Tools
Once connected, your LLM will have access to the following tools:
chat_with_diffusion(prompt: str)Sends a message to the persistently running Diffusion LLM and returns the generated text.restart_chat_session()Gracefully exits the current chat process using the/exitcommand and spins up a fresh session. The LLM will use this if you ask it to clear context or start over.
Available Tools
1 toolgenerate_diffusion_textA
Generates text using a diffusion-based LLM. This is a one-shot process.
Inputs: prompt (required). Returns: result
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 1 tool
With only one tool, there is no ambiguity. An agent can clearly identify the sole purpose of generating diffusion text.
Although only one tool exists, its name 'generate_diffusion_text' follows a clear verb_noun pattern, which is consistent and predictable.
A single tool is appropriate for a very narrow scope like one-shot text generation, but it borders on being too thin for a more general-purpose diffusion server.
The tool covers the entire stated purpose of generating diffusion-based text. There are no obvious missing operations given the 'one-shot' description.
Related MCP Connectors
LLM chat, text tools, image generation, editing, batch image jobs, and asynchronous video generation
Talk to your public-facing AI from any MCP client — Claude, ChatGPT, Cursor, Cline, Windsurf.
Connect ChatGPT and Claude to your Mac, Windows or Linux with secure MCP remote access.
Real-time chat hub for AI agents — Claude Code, Cursor, Cline, Codex over MCP or REST.
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