QEMU Screenshot MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool has a clear and distinct purpose of capturing screenshots from QEMU instances.
Naming Consistency5/5With only one tool, naming consistency is inherently perfect. The tool name 'capture_screenshot' follows a clear verb_noun pattern and sets a consistent standard, though there are no other tools to compare it against.
Tool Count2/5A single tool is too few for most server purposes, as it severely limits functionality and scope. While it may be appropriate for a minimal utility, it feels thin and incomplete for a server named 'QEMU Screenshot MCP Server', which suggests broader screenshot-related capabilities.
Completeness2/5The tool surface is severely incomplete for a screenshot server. It only captures screenshots from the first running QEMU instance, with no tools for listing instances, selecting specific ones, managing captures, or handling errors, leading to significant gaps that will cause agent failures.
Average 3.6/5 across 1 of 1 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses behavioral traits: the prioritization of QMP over X11 and the fallback mechanism. However, it doesn't cover important aspects like error handling (e.g., what happens if no QEMU instance is running), output format, or side effects. This leaves gaps in understanding the tool's behavior beyond the basic operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is highly concise and well-structured: two sentences that efficiently convey the purpose and behavioral context. Every sentence adds value without redundancy, making it easy to parse and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (involves QEMU and multiple capture methods), lack of annotations, and no output schema, the description is incomplete. It explains the capture process but omits details like what the output is (e.g., image format, storage location), error conditions, or dependencies. This leaves the agent with insufficient information for reliable use in varied scenarios.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameters need documentation. The description doesn't add parameter semantics, which is acceptable here. A baseline of 4 is appropriate since the schema fully covers the lack of parameters, and the description doesn't need to compensate for any gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Captures a screenshot of the first running QEMU instance.' It specifies the action (captures) and target resource (screenshot of QEMU instance), though it doesn't need to distinguish from siblings since none exist. However, it could be more specific about what 'first running QEMU instance' means in ambiguous scenarios.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides implied usage context: 'Prioritizes QMP (window-independent), falls back to X11 (if available).' This suggests when certain methods are preferred, but it doesn't explicitly state when to use this tool versus alternatives (e.g., other screenshot tools) or any prerequisites. Since there are no sibling tools, the lack of explicit alternatives is less critical, but guidance on conditions for successful invocation is limited.
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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