ScratchRun MCP Server
Server Quality Checklist
Latest release: v0.1.1
- Disambiguation5/5
Only one tool exists, so there is no possibility of confusion between tools. The tool's purpose is clearly described as sandboxed code execution, making it unambiguous.
Naming Consistency5/5The single tool name 'scratchrun_exec' follows a clear snake_case pattern with a descriptive prefix and verb. Consistency is trivially maintained when there is only one tool.
Tool Count5/5The server is focused entirely on one function: executing code in an ephemeral sandbox. One tool is exactly the right size for this narrow, well-defined purpose, and the parameter space covers execution, environment variables, and file output.
Completeness5/5For the server's stated purpose (sandboxed code execution), the tool fully covers the lifecycle: execute code, pass environment variables, and retrieve output files. No obvious missing operations exist within the domain.
Average 4.7/5 across 1 of 1 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 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
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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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
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden and excels: it discloses hard-purge/no persistence, full internet egress with RFC 1918/cloud metadata blocks, and how to retrieve artifacts. This is rich behavioral context beyond basic function.
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 compact and front-loaded with the primary purpose. Every sentence adds value—covering security, persistence, file capture, and secrets—without redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema or annotations, the description provides comprehensive context: execution environment, security boundaries, state persistence, artifact retrieval, and secrets handling. It addresses the tool's complexity and likely pitfalls.
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?
Schema coverage is 100%, providing baseline 3. The description adds extra meaning by explaining the purpose of return_files (base64-encoded artifacts) and recommending env for secrets, reinforcing and supplementing schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool executes code in an ephemeral, MicroVM-isolated sandbox, using a specific verb and resource. It conveys the core function and distinctive characteristics (isolation, ephemerality) without ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides practical usage guidance such as using return_files to capture output artifacts and passing secrets via env instead of code strings. It implies appropriate contexts (e.g., untrusted code, one-off executions) though it doesn't explicitly contrast with alternatives, as none are listed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
GitHub Badge
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- Confirm that the MCP server is working as expected.
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- Evaluate tool definition quality.
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