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., "@Venice MCP Server generate an image of a sunset over mountains"
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.
A Model Context Protocol (MCP) server for Venice AI. Gives AI assistants like Claude access to Venice's text generation, image creation, text-to-speech, embeddings, and account management APIs.
This MCP server lets Claude (or any MCP-compatible assistant) use Venice AI's features directly:
Chat with Llama, DeepSeek, Qwen, and other open models
Generate images using Stable Diffusion, FLUX, and more
Create speech from text with natural-sounding voices
Generate embeddings for search and RAG applications
Manage API keys and monitor rate limits
Related MCP server: Mistral MCP Server
Sign up at venice.ai and create an API key in Settings → API.
npm install -g venice-mcpAdd to your config file:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
Linux: ~/.config/Claude/claude_desktop_config.json
{
"mcpServers": {
"venice": {
"command": "npx",
"args": ["-y", "venice-mcp"],
"env": {
"VENICE_API_KEY": "your-api-key-here"
}
}
}
}Restart Claude Desktop. You'll see Venice tools available in the 🔧 menu.
Tool | Description |
| Chat with Venice AI language models |
| Generate images from text descriptions |
| Upscale and enhance images |
| Convert text to spoken audio |
| Generate text embeddings |
Tool | Description |
| List available models (text, image, code) |
| List character personas |
Requires an admin-level API key:
Tool | Description |
| List all API keys |
| Create a new API key |
| Get details for a key |
| Delete an API key |
| View rate limits and usage |
| View rate limit history |
Ask Claude to generate an image:
"Use Venice to create an image of a sunset over mountains"
Chat with a specific model:
"Ask Venice's DeepSeek model to explain quantum computing"
Check your usage:
"Show my Venice API rate limits"
Language Models: Llama 3.3 70B, DeepSeek R1, Qwen 3, Mistral, and more
Image Models: Stable Diffusion 3.5, FLUX, Fluently XL
Embeddings: BGE-M3 (1024 dimensions)
TTS: Kokoro with multiple voice options
Run venice_list_models to see all currently available models.
Node.js 18+
Venice AI API key
git clone https://github.com/georgeglarson/venice-mcp.git
cd venice-mcp
npm install
npm run buildnpm test # Run tests
npm run test:watch # Watch mode
npm run test:coverage # Coverage reportContributions are welcome! Please see CONTRIBUTING.md for guidelines.
Venice AI - Platform home
Venice API Docs - API reference
MCP Documentation - Protocol spec
MIT - see LICENSE
Send a message to Venice AI and get a response from an LLM
Inputs: message (required), model, max_tokens, temperature, +1 more.
Create a new API key
Inputs: description (required), expiresAt, apiKeyType, consumptionLimit.
Generate text embeddings for semantic search and RAG
Inputs: input (required), model.
Delete an API key
Inputs: key_id (required).
Generate an image from a text prompt using Venice AI
Inputs: prompt (required), size, model, style_preset, +1 more.
Get rate limit usage history logs
Inputs: no named parameters.
Get current rate limits, usage, and account information
Inputs: no named parameters.
List all API keys on the account (requires admin API key)
Inputs: no named parameters.
List available Venice AI character personas for roleplay
Inputs: limit.
List available Venice AI models by type
Inputs: type.
Get details for a specific API key
Inputs: key_id (required).
Convert text to speech audio using Venice AI
Inputs: text (required), model, voice.
Upscale an image using Venice AI
Inputs: image (required), scale.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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Scored across 13 tools
Each tool has a unique purpose (chat, API key CRUD, embeddings, image generation, TTS, etc.) with no overlap, making it easy for an agent to select the correct tool.
All tools follow a consistent 'venice_verb_noun' pattern (e.g., venice_create_api_key, venice_list_models), which is predictable and clear.
13 tools covering chat, image, embeddings, TTS, API key management, and monitoring is well-scoped for an AI API server without being excessive.
Core functionalities are covered (chat, images, embeddings, TTS, API key CRUD minus update, rate limits). Minor gaps like no streaming or API key update do not hinder basic workflows.
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