Tuning Engines
Kick off domain-specific LLM fine-tuning on your data through Tuning Engines from an MCP-connected agent without standing up training infra.
Overview
Tuning Engines (cerebrixos fine-tuning) is a MCP server for the Build phase that runs domain-specific LLM fine-tuning on your data with managed infrastructure.
What is this MCP server?
- Domain-specific LLM fine-tuning positioned as sovereign models on your data
- Hosted training path advertised as zero infrastructure for the builder
- tuningengines-cli npm package 0.3.5 with stdio MCP and TE_API_KEY authentication
- Same GitHub org CLI repo as the governed runtime line but focused on fine-tuning in this registry entry
- Registry version 0.3.5 for io.github.cerebrixos/tuning-engines
- npm identifier tuningengines-cli with stdio MCP transport
- Required TE_API_KEY secret for all connections
Community signal: 2 GitHub stars.
What problem does it solve?
You need a model that understands your domain but cannot afford to own fine-tuning pipelines, GPUs, and experiment tracking as a team of one.
Who is it for?
Indie builders creating vertical AI products who want managed fine-tuning reachable from their coding agent.
Skip if: Teams only seeking runtime policy and traces without training new weights, or those with strict on-prem-only training requirements not met by the hosted service.
What do I get? / Deliverables
After MCP registration with TE_API_KEY, your agent can orchestrate Tuning Engines fine-tuning jobs and obtain sovereign models trained on your datasets.
- Fine-tuned domain-specific model artifacts via Tuning Engines
- Agent-driven training orchestration without self-managed GPU infra
- Integration path from MCP host to Tuning Engines training APIs
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Journey fit
Custom model creation is Build work when you are shaping the intelligence layer of an agent product before ship. Agent-tooling fits because fine-tuning produces a model artifact agents will call, alongside skills and MCP tools.
How it compares
Fine-tuning-focused Tuning Engines MCP entry, not the cerebrixos-org governance and analytics variant.
Common Questions / FAQ
Who is Tuning Engines fine-tuning MCP for?
Solo builders and small product teams who need custom LLMs for niche domains and want to trigger training from Claude Code or Cursor.
When should I use Tuning Engines fine-tuning MCP?
Use it during Build when generic models fail on your terminology and you are ready to supply training data to a managed fine-tuning service.
How do I add Tuning Engines fine-tuning MCP to my agent?
Add stdio MCP for tuningengines-cli 0.3.5, export TE_API_KEY from tuningengines.com or te auth login, then invoke training workflows through exposed MCP tools.