Unsloth MCP Server

export_model

Export fine-tuned Unsloth models to GGUF, Ollama, vLLM, or Hugging Face formats for deployment, supporting quantization to optimize file size and performance.

Instructions

Export a fine-tuned Unsloth model to various formats

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "model_path": "<model_path>",
      "export_format": "<export_format>",
      "output_path": "<output_path>"
    },
    "name": "export_model"
  }
}

Input Schema

Name	Required	Description
`model_path`	Yes	Path to the fine-tuned model
`export_format`	Yes	Format to export to (gguf, ollama, vllm, huggingface)
`output_path`	Yes	Path to save the exported model
`quantization_bits`	No	Bits for quantization (for GGUF export)

Schema Changelog

Changes observed during successful MCP inspections.

First observedAug 15, 2025

TDQS

B3.1/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool exports models but doesn't describe what the export entails (e.g., file creation, format conversion, potential data loss, permissions required, or rate limits). For a tool with 4 parameters and no annotations, this leaves significant gaps in understanding its behavior and side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose ('Export a fine-tuned Unsloth model') and adds necessary detail ('to various formats'). There is no wasted verbiage, and it's appropriately sized for the tool's complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 4 parameters with full schema coverage but no annotations and no output schema, the description is minimally adequate. It covers the basic purpose but lacks behavioral context, usage guidelines, and output details. For a tool that likely involves file operations and format conversions, more completeness would be beneficial, but it meets a bare minimum.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds minimal value beyond the schema by mentioning 'various formats,' which aligns with the 'export_format' enum but doesn't provide additional syntax or usage details. Baseline 3 is appropriate as the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Export') and resource ('a fine-tuned Unsloth model'), specifying the target formats ('various formats'). It distinguishes from siblings like 'finetune_model' or 'load_model' by focusing on export rather than creation or loading. However, it doesn't explicitly differentiate from all siblings (e.g., 'generate_text' is clearly different, but the distinction is implicit rather than explicit).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a fine-tuned model first), exclusions (e.g., not for raw models), or comparisons to sibling tools like 'list_supported_models' for checking export options. Usage is implied by the action but lacks explicit context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server