fivem-mcp-server

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Capture the game window

screenshot

Capture the FiveM game window as a downscaled PNG for AI vision checks, with optional crop and maxSide to limit transcript cost.

Instructions

PNG of the FiveM window (PrintWindow with PW_RENDERFULLCONTENT; falls back to a screen BitBlt of the window rect when the swapchain returns black, which means whatever covers the window is also captured — the game is focused first). Downscaled so vision models can read it cheaply. COST WARNING: every screenshot stays in the transcript and is re-sent on every later turn - many shots multiply session latency. Prefer text probes (read_console, wait_for_console, bridge ops); when pixels are the evidence, keep maxSide small (640 suffices for layout checks) and crop to the panel of interest.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "screenshot"
  }
}

Input Schema

Name	Required	Description	Default
`crop`	No	Window-pixel rect, as an object or JSON string, e.g. {"x":300,"y":200,"width":400,"height":300}
`maxSide`	No	Downscale longest side (default 900)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.6.0Oct 17, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Goes well beyond annotations: it discloses the capture mechanism (PrintWindow with PW_RENDERFULLCONTENT), the black-swapchain fallback to BitBlt (and that occluding windows are then captured), and — critically — that the game is focused first, which explains the readOnlyHint=false annotation. The transcript-cost warning (shots are re-sent every later turn, multiplying latency) is a behavioral trait no structured field conveys.

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?

Every sentence earns its place — mechanism, fallback, cost, alternatives, and parameter advice are all non-redundant. It is dense with parentheticals and the cost warning arguably belongs before the mechanism detail, but there is no filler or repetition.

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?

With no output schema, the description still specifies the return format (PNG), the resize behavior, and the failure/fallback path, plus cost and alternative-tool context. Nothing an agent needs to invoke this correctly — or to decide against it — is missing.

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

Parameters4/5

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

Schema coverage is 100%, so baseline is 3; the description adds operational meaning by tying maxSide to cost ('keep maxSide small (640 suffices for layout checks)') and by advising crop to the panel of interest, which the schema's bare types don't imply. It doesn't restate ranges or defaults, but the added usage-level semantics lift it above baseline.

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?

States a specific verb+resource (capture PNG of the FiveM window) and immediately names the mechanism and scope, distinguishing it from text-oriented siblings like read_console and wait_for_console. An agent can tell what this returns and how it differs from the surrounding tools without opening the schema.

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?

Explicitly says to prefer text probes (read_console, wait_for_console, bridge ops) and names the condition that justifies this tool: 'when pixels are the evidence'. It further routes usage with 'keep maxSide small (640 suffices for layout checks) and crop to the panel of interest', which is actionable when-to-use guidance.

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