About Auxen
Auxen is a remote MCP server for managing private GPU instances that run open-source models. It is aimed at users provisioning dedicated model deployments and provides tools to inspect models, instances, and account credits.
Key features
- 01List available models
- 02Inspect instance status
- 03List account instances
- 04Check credits and subscriptions
- 05Provision model instances
- 06Destroy instances
Use cases
- 01Review models before deployment
- 02Check a deployed instance
- 03Track account credits
- 04Create or remove a model instance
MCP support
Auxen exposes model catalog, instance, balance, provisioning, and destruction tools to MCP clients through a remote StreamableHTTP server. Authentication supports OAuth 2.1 with PKCE or an Auxen API key.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://api.auxen.ai/mcpclaude mcp add --transport http ai-auxen-auxen https://api.auxen.ai/mcp{"mcpServers":{"ai-auxen-auxen":{"type":"http","url":"https://api.auxen.ai/mcp"}}}Open in Cursor{"servers":{"ai-auxen-auxen":{"type":"http","url":"https://api.auxen.ai/mcp"}}}Open in VS Code{"mcpServers":{"ai-auxen-auxen":{"type":"http","url":"https://api.auxen.ai/mcp"}}}{"mcpServers":{"ai-auxen-auxen":{"serverUrl":"https://api.auxen.ai/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
Tools
Details
From the project READMEAuxen MCP Server
This is the public manifest repo for the Auxen MCP (Model Context Protocol) server. The server itself runs at https://api.auxen.ai/mcp — this repo exists so registries (Smithery, Glama, the official MCP registry) have a canonical place to read metadata from.
Connect
The Auxen MCP server is a remote, StreamableHTTP server. Add it to your MCP client by URL:
https://api.auxen.ai/mcp
Authentication uses OAuth 2.1 + PKCE (recommended for browser-based clients) or a direct Auxen API key (auxen_live_* / auxen_test_*) sent as Authorization: Bearer <key>.
OAuth flow
The discovery metadata is at:
https://api.auxen.ai/.well-known/oauth-authorization-server(RFC 8414)https://api.auxen.ai/.well-known/oauth-protected-resource(RFC 9728)
Clients that support Dynamic Client Registration (RFC 7591) — including Claude.ai's Connectors Directory — can register themselves automatically. After registration the client redirects the user's browser to https://api.auxen.ai/oauth/authorize, the user logs in to Auxen and approves the connection on https://auxen.ai/oauth/authorize, and the client receives an authorization code that exchanges for an access token at https://api.auxen.ai/oauth/token.
Direct key (programmatic)
For agents that don't go through a browser, generate an auxen_live_* (or auxen_test_*) key at https://auxen.ai/dashboard/api-keys and send it as Authorization: Bearer <key> on every MCP call.
Tools
| Tool | Effect | Hint |
|---|---|---|
auxen_list_models | List available models, optionally filtered by size | read-only |
auxen_get_instance_status | Get status, endpoint, api_key for an instance | read-only |
auxen_list_instances | List all instances on the account | read-only |
auxen_get_balance | Read USD credits + active subscriptions | read-only |
auxen_provision_model | Provision a new model instance — spends money | destructive |
auxen_destroy_instance | Destroy an instance — irreversible | destructive |
What is Auxen?
Auxen provisions private, dedicated GPU instances running open-source models (Llama 3.1, Qwen 2.5, Mistral, Gemma 2, Phi-3). Each instance is fully private — no shared inference, no third-party routing. Pay-per-minute billing, no subscriptions.
For the human-facing documentation:
- Website: https://auxen.ai
- Architecture explainer: https://auxen.ai/architecture
- Agent reference: https://auxen.ai/agent-reference.md
- Concise reference for LLMs: https://auxen.ai/llms.txt
- OpenAPI 3.1 spec: https://api.auxen.ai/openapi.json
Support
- Email: [email protected]
- Status: https://status.auxen.ai
Comments
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.