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Flux-Point-Studios

Unreal Engine MCP Server

observe

Monitor Unreal Engine runtime by querying logs, capturing snapshots during playtests, and generating structured reports for debugging and feedback.

Instructions

Runtime observability and playtest feedback. Start PIE playtests, capture snapshots at intervals, query logs, correlate events, and generate structured reports. Actions: query_logs, get_log_summary, start_playtest, capture_snapshot, stop_playtest, get_playtest_report, run_scenario, get_runtime_state.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNoNumber of log entries to return (default: 50)
labelNoLabel for the playtest session or scenario
sinceNoISO timestamp — only return logs after this time
actionYesrun_scenario automates: start PIE → capture snapshots at intervals → stop → report. query_logs reads from disk log and internal buffer.
statusNoFinal status when stopping playtest
categoryNoLog category filter (partial match)
durationNoScenario duration in seconds (default: 10)
intervalNoSnapshot capture interval in seconds (default: 3)
severityNoMinimum severity filter for logs
Behavior3/5

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

Annotations are all false, so the description carries the burden. It discloses mutating actions like 'Start PIE playtests' and 'stop_playtest', but does not mention side effects, reversibility, or state changes beyond starting/stopping. The description gives some behavioral context but lacks details on consequences or prerequisites.

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 two sentences, front-loaded with the core purpose. The explicit action list is somewhat redundant with the schema's enum but is concise and gives a quick overview of capabilities without unnecessary elaboration.

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 is a high-level overview but lacks workflow guidance—for example, that start_playtest should precede capture_snapshot or that run_scenario automates the full sequence. With no output schema, return values are not described, leaving some context incomplete, though parameter-level details are well-covered in the schema.

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?

All 9 parameters have descriptions in the input schema (100% coverage), so the description doesn't need to explain individual params. The description only repeats the action enum names, which is already in the schema, adding no extra semantic value beyond what the schema provides.

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 'Runtime observability and playtest feedback' and enumerates concrete actions like query_logs, start_playtest, and capture_snapshot, which gives a specific sense of the tool's scope. It focuses on PIE playtests, distinguishing it somewhat from broader observability tools, though it doesn't explicitly differentiate from siblings.

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 action list implies when to use the tool (e.g., start_playtest for playtesting sessions), but there is no explicit guidance about when to prefer this tool over siblings like 'inspect' or 'manage_performance'. It provides a catalog of actions without preconditions or alternatives.

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

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