Tuning Engines Cli
未申請CLI & MCP server for Tuning Engines — fine-tune LLMs on code repositories
インストール
npx -y --package tuningengines-cli@latest te auth status未申請リスティング
このMCPサーバーはあなたのものですか？
このリスティングは公開情報から自動的にインデックスされました。申請することで、ページの編集、互換性の設定、成長ツールのアンロックができます。2分以内に完了します。
このサーバーを申請するツール（40個）
call_inference
Call chat, Responses, embeddings, or Messages using the configured credential
cancel_evaluation
Cancel a running evaluation
cancel_job
Cancel a running/queued job
catalog_export_status
Check marketplace export progress
create_dataset
Create a dataset from S3
create_evaluation
Run an evaluation against a dataset
create_job
Fine-tune an LLM on a GitHub repo. Supports agent selection (Cody, SIERA), quality tier, base model, epochs, S3 export.
create_trace
Ingest a trace payload without secrets
dataset_status
Check dataset import/processing status
delete_dataset
Delete a dataset
delete_model
Delete a model from cloud storage
doctor_simulate
Simulate inference access, role, endpoint, policy, and resource checks
estimate_evaluation
Cost estimate for an evaluation
estimate_job
Cost estimate before training. Returns cost range, balance, sufficiency check.
evaluation_status
Live evaluation progress
get_catalog_model
Details of a marketplace item
get_inference_jwt
Get JWT token for direct API access
get_inference_token
Exchange an inference key for a short-lived inference JWT
inference_usage
Inference API usage statistics
job_status
Live status with GPU minutes, charges, delivery progress
list_catalog_models
Browse pre-built models and datasets
list_datasets
List datasets for training and evaluation
list_evaluations
List model evaluations
list_evaluators
Available evaluators (codeexecution, similarity, llmjudge, etc.)
list_inference_models
Models available for inference
list_insights
List Insight Loop recommendations
list_jobs
List training jobs with status filter
list_models
List trained and imported models
list_outcomes
List observed outcomes/goals normalized as success signals
list_supported_models
Available base models with GPU hours per epoch
list_traces
List runtime traces
model_status
Import/export progress
retry_job
Retry a failed job from its last checkpoint
send_agent_message
Send a governed A2A agent message
show_dataset
Dataset details and status
show_evaluation
Evaluation details, scores, and metrics
show_insight
Show one Insight Loop recommendation
show_job
Full job details including agent, model, GPU usage, cost, retry info
show_model
Model details (status, size, base model, training job)
show_trace
Show a trace with linked events, policy decisions, and approvals