// MCP TOOL REFERENCE
F Risk Grade Tuning Engines - LLM Fine-Tuning · worst category: Destructive

TUNING ENGINES - LLM FINE-TUNING TOOLS

73 tools from the Tuning Engines - LLM Fine-Tuning MCP Server, categorised by risk level.

View the Tuning Engines - LLM Fine-Tuning policy →
// ALL 73 TUNING ENGINES - LLM FINE-TUNING TOOLS
READ 47 tools
Read accept_insight Accept an Insight Loop recommendation as valid for review. Requires --enable-registry-writes. Does not chan... Read dataset_status Check the status of a dataset import or processing operation. Read deny_approval Deny a pending policy approval request. Requires tenant owner/admin API token. Read estimate_evaluation Get a cost estimate for an evaluation before running it. Read estimate_job Get a cost estimate for a fine-tuning job before submitting it. Returns estimated cost, cost range, current... Read evaluation_status Get live status of an evaluation including progress and current metrics. Read get_account Get your Tuning Engines account details and settings. Read get_balance Check your Tuning Engines account balance and recent transactions. Read get_catalog_model Get detailed information about a specific pre-built model or dataset from the Marketplace including descrip... Read get_inference_jwt Get a JWT token for authenticating with the Tuning Engines inference API. Read get_inference_token Exchange an inference key (sk-te-...) for a short-lived inference JWT. Read inference_capture_show Show request-capture settings for fine-tuning data capture. Secret values are not returned. Read inference_usage Get inference API usage statistics including request counts, token usage, and costs. Read job_status Get live status of a fine-tuning job including current status, GPU minutes used, estimated charges, remaini... Read list_agents List available agents configured for your organization. Agents are AI assistants with specific capabilities... Read list_approvals List policy approval requests for the current tenant. Requires tenant owner/admin API token. Read list_catalog_models List available pre-built models and datasets from the Tuning Engines Marketplace. Read list_datasets List datasets available for training and evaluation. Datasets can be uploaded from S3 and used for fine-tun... Read list_evaluations List model evaluations. Evaluations run your trained models against benchmark datasets using various evalua... Read list_evaluators List available evaluators for model evaluation. Evaluators measure different aspects of model quality like ... Read list_inference_models List models available for inference through the Tuning Engines inference API. Read list_insights List Insight Loop recommendations. Read list_jobs List fine-tuning training jobs on Tuning Engines. Returns recent jobs with status, base model, agent type, ... Read list_models List your trained and imported models on Tuning Engines. Read list_outcomes List observed outcomes, goals, workflow statuses, evals, and feedback normalized into success signals. Read list_policy_decisions List AGT YAML policy decisions for the current tenant. Requires tenant owner/admin API token. Read list_policy_templates List curated AGT YAML policy templates. Requires tenant owner/admin API token. Read list_supported_models List the supported base HuggingFace models available for fine-tuning on Tuning Engines. Optionally filter b... Read list_tenant_resources List tenant-admin resource names available through the public API. Internal proxy routes are intentionally ... Read list_traces List runtime traces emitted by LangGraph, Temporal, MCP, skills, agents, or custom runtimes. Requires a ten... Read model_status Check the status of a model import or export operation. Read render_policy_template Render a curated AGT YAML policy template into disabled/shadow YAML. Template params must not include secrets. Read retry_job Retry a failed fine-tuning job from its last checkpoint. Creates a new job that resumes training where the ... Read show_agent Get details of a specific agent including capabilities, tools, and configuration. Read show_approval Show one policy approval request with redacted context. Requires tenant owner/admin API token. Read show_dataset Get details of a specific dataset including status, source, and metadata. Read show_evaluation Get full details of a specific evaluation including status, scores, metrics, and comparison data. Read show_insight Show one Insight Loop recommendation. Read show_job Get full details of a specific fine-tuning job including status, base model, agent type, GPU minutes, cost,... Read show_model Get details of a specific trained model. Read show_policy_decision Show one policy decision with redacted context and metadata. Requires tenant owner/admin API token. Read show_trace Show one runtime trace by run_id, including events, policy decisions, and approvals when linked. Read tenant_resource_list List an allowlisted tenant resource. Requires tenant owner/admin API token. Read tenant_resource_show Show one allowlisted tenant resource. Secret values are not returned by the API. Read tenant_resource_validate Validate an unsaved guardrail or AGT governance policy without creating records. Requires tenant owner/admi... Read tenant_team_list List tenant members, pending invitations, and allowed email domains. Requires tenant owner/admin API token. Read test_governance_policy Dry-run an AGT YAML governance policy against a JSON context. Requires tenant owner/admin API token.
WRITE 17 tools
Write apply_insight Apply or queue the approved action for an accepted Insight Loop recommendation. Requires --enable-registry-... Write approve_approval Approve a pending policy approval request. Requires tenant owner/admin API token. Write catalog_export_status Check the status of a Marketplace export operation. Returns status, charge info, and any error messages. Write create_dataset Create dataset metadata for fine-tuning or evaluation. Write create_evaluation Create a new model evaluation. Run your trained model or a base model against a dataset using selected eval... Write create_job Fine-tune an LLM on a GitHub repository using Tuning Engines. Write create_trace Ingest or update a runtime trace. Include run_id/request_id and normalized event types when possible. metad... Write generate_policy_draft Generate an AI-assisted AGT YAML draft. Drafts are disabled/shadow and must be reviewed/tested/saved explic... Write inference_capture_update Update request-capture settings. Use credential_source_id references; raw cloud secrets are refused by MCP. Write map_outcome Create an outcome mapping rule for events that omitted outcome_key/goal_key. Requires --enable-registry-wri... Write tenant_domains_update Replace the tenant Write tenant_resource_create Create an allowlisted tenant resource using non-secret JSON. MCP refuses raw secret fields and inference-ke... Write tenant_resource_update Update an allowlisted tenant resource using non-secret JSON. MCP refuses raw secret fields; use CLI/web UI ... Write tenant_team_disable Disable a tenant member and block API access. Requires tenant owner/admin API token. Write tenant_team_enable Re-enable a disabled tenant member. Requires tenant owner/admin API token. Write tenant_team_invite Invite a tenant member by email. Invitation token is emailed by the app and is never returned. Write tenant_team_set_inference_role Assign or clear an inference role for a tenant member. Requires tenant owner/admin API token.
DESTRUCTIVE 7 tools
Destructive cancel_evaluation Cancel a running or queued evaluation. Destructive cancel_job Cancel a running or queued fine-tuning job. The job will be charged for any GPU time already used. Destructive delete_dataset Delete a dataset from the platform. Destructive delete_model Delete a trained model from cloud storage. Destructive tenant_invitation_cancel Cancel a pending tenant invitation. Requires tenant owner/admin API token. Destructive tenant_resource_delete Delete or revoke an allowlisted tenant resource. Requires tenant owner/admin API token. Destructive tenant_team_remove Remove a tenant member. Requires tenant owner/admin API token.
EXECUTE 2 tools
Execute doctor_simulate Run an Inference Doctor simulation for access, role, endpoint, policy, and resource debugging. Execute record_outcome Record an outcome or goal success signal for a run. Requires --enable-registry-writes because it writes tel...
// RUNNING THIS SERVER

The managed route: connect Tuning Engines - LLM Fine-Tuning through the PolicyLayer gateway — every tool call above is checked against your policy before it runs, with a full audit log.

DIRECT INSTALL (UNMANAGED) npx -y tuningengines-cli

Route Tuning Engines - LLM Fine-Tuning through PolicyLayer and every one of its 73 tools is checked against your policy before it runs.

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// FAQ
How many tools does the Tuning Engines - LLM Fine-Tuning MCP server have? +

The Tuning Engines - LLM Fine-Tuning MCP server exposes 73 tools across 4 categories: Read, Write, Destructive, Execute.

How do I enforce policies on Tuning Engines - LLM Fine-Tuning tools? +

Route the Tuning Engines - LLM Fine-Tuning server through the PolicyLayer gateway. Define allow, deny, or approval rules per tool in the dashboard; they are enforced on every call before it reaches the server.

What risk categories do Tuning Engines - LLM Fine-Tuning tools fall into? +

Tuning Engines - LLM Fine-Tuning tools are categorised as Read (47), Write (17), Destructive (7), Execute (2). Each category has a recommended default policy.

Enforce policy on every Tuning Engines - LLM Fine-Tuning tool call.

Start from Tuning Engines - LLM Fine-Tuning, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

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