Skip to main content
Glama

call_function

Call a UFunction on an Unreal Engine object with JSON arguments and get its result, enabling AI-driven game function invocation.

Instructions

Call a UFunction on an object with positional JSON args and return its result. Refused when allow_writes = false.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
refYes
argsNo
functionYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

A3.8/5.0
Behavior4/5

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

The refusal condition ('Refused when allow_writes = false') reveals that the tool may perform write operations, which is useful behavioral info. However, it does not elaborate on side effects, error behavior, or whether it is read-only in other cases.

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 concise, two sentences, with no redundant information. It directly states the purpose and a key constraint.

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?

The description covers core action and a refusal condition, but lacks details on expected output format, error handling, or prerequisites for calling functions. It is adequate for a simple call but not fully comprehensive.

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

Parameters2/5

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

The phrase 'positional JSON args' clarifies the 'args' parameter, but 'ref' and 'function' are not explicitly explained. Since the schema has no descriptions, the description only partially compensates for parameter semantics.

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 clearly states the action: calling a UFunction on an object with positional JSON arguments and returning the result. It distinguishes itself from sibling tools like get_property or set_property by focusing on function invocation.

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

Usage Guidelines3/5

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

The description mentions a refusal condition based on allow_writes, but does not explicitly guide when to use this tool over alternatives such as eval_lua or list_functions. The condition gives some context but lacks direct comparative guidance.

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

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/littleRabbit94/ue-bridge'

If you have feedback or need assistance with the MCP directory API, please join our Discord server