Skip to main content
Glama

save_blueprint

Persist a Blueprint asset to disk using the native UnrealMCP bridge, avoiding Python save_asset crashes. Optionally only saves if the package is dirty.

Instructions

Persist a Blueprint package to disk using the UnrealMCP C++ bridge.

This invokes the native save_blueprint MCP command, which writes the package via UEditorLoadingAndSavingUtils::SavePackages (UnrealEd). It does not call Python unreal.EditorAssetLibrary.save_asset / save_loaded_asset, which has crashed with EXCEPTION_ACCESS_VIOLATION in EditorScriptingUtilities on some UE 5.6 sessions.

Typical flow after editing a BP via MCP:

  1. compile_blueprint(blueprint_name=...) — marks modified (plugin safe path)

  2. save_blueprint(blueprint_name=...) — writes .uasset

Optional: only_if_dirty=True maps to the engine's "only save dirty packages" behavior; default False saves the listed package regardless.

Args: blueprint_name: Blueprint asset name (e.g. "BP_Cabal") only_if_dirty: If True, only persist if the package is dirty

KB: see knowledge_base/10_WORLD_BUILDING.md#overview Example: save_blueprint(blueprint_name="/Game/MCP_Test/BP_Example")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
only_if_dirtyNo
blueprint_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.9/5.0
Behavior5/5

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

With no annotations present, the description carries the full transparency burden and does so thoroughly. It discloses the native C++ bridge implementation, the underlying engine call (UEditorLoadingAndSavingUtils::SavePackages), the deliberate avoidance of the crash-prone Python API, and the exact semantics of only_if_dirty including the default false behavior. This is rich, actionable behavioral context for a mutating operation.

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

Conciseness4/5

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

The description is well-organized: purpose first, then implementation detail, workflow, parameter semantics, and example. It is slightly longer than strictly necessary due to repeating the only_if_dirty explanation in both prose and the Args block, but every sentence adds useful information and no vague filler exists.

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

Completeness5/5

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

The tool description covers what the operation does, how it works, why it is preferred over the Python equivalent, when it fits into a larger editing workflow, the meaning of both parameters, and a concrete invocation example. Since an output schema exists, return-value documentation is not required here, making this functionally complete for an agent.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must explain both parameters itself. It does: blueprint_name is described as a Blueprint asset name with examples ('BP_Cabal') and a full path example at the end, while only_if_dirty is explained in plain terms with its engine mapping and default behavior. The description fully compensates for the schema's lack of parameter documentation.

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

Purpose5/5

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

The description opens with a specific verb and resource: 'Persist a Blueprint package to disk using the UnrealMCP C++ bridge.' It clearly distinguishes the tool from related operations like compile_blueprint by explaining it writes the .uasset via SavePackages, and even contrasts it with Python save functions. An agent can immediately understand what this tool does and how it differs from nearby editing/saving workflows.

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

Usage Guidelines5/5

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

The description gives a concrete typical flow: compile_blueprint first to mark modified, then save_blueprint to write the asset. It also explicitly warns against the Python-based save path due to a crash risk, providing clear selection guidance. The only_if_dirty parameter behavior is explained, so the agent knows how to control when the save is skipped.

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

Deploy Server

Other Tools