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dylantirandaz

Tailscale Compute MCP

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.1.0-beta.1

  • Disambiguation5/5

    compute_status and compute_run are clearly distinct: one inspects the remote node's configuration and health, while the other executes a command. There is no overlap or ambiguity between the two tools.

    Naming Consistency5/5

    Both tools follow the same compute_ prefix with a concise action suffix (status, run), creating a consistent and predictable naming pattern.

    Tool Count4/5

    With only two tools, the server is under the typical 3-15 range, but the scope is intentionally narrow—checking status and running commands on a configured remote node. Each tool is essential and earns its place.

    Completeness5/5

    The server covers the core workflow: verify connectivity/state with compute_status and perform remote work with compute_run, which includes automatic project syncing. No obvious gaps exist for its stated purpose.

  • Average 4.3/5 across 2 of 2 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 7 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing
  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

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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

  • Behavior4/5

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

    The description adds important behavioral context beyond annotations: commands run non-interactively, the tool syncs the local project, and 'the command has the full permissions of the remote SSH user.' These details complement the destructiveHint and readOnlyHint annotations without contradiction.

    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?

    Four concise sentences each carry unique information: purpose, use cases, a warning to keep edits local, and the permission warning. There is no redundant or filler content.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness4/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the tool's complexity (8 params, output schema, annotations), the description covers the core workflow (sync and run), the intended use cases, and the security implications. It does not need to restate schema details, making it complete enough for an agent to decide when and how to invoke it.

    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?

    The input schema already provides 100% parameter coverage with detailed descriptions, so the description adds minimal parameter-level value. The note about running 'non-interactive' commands is useful context but the schema already explains shell syntax for program/arguments.

    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 uses specific verbs 'Sync' and 'run' with the resource 'Tailscale compute node', clearly distinguishing it from the sibling tool compute_status. It also enumerates use cases (builds, tests, benchmarks) that make the tool's purpose unambiguous.

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

    Usage Guidelines4/5

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

    The description explicitly states 'Use it for builds, tests, benchmarks, and other costly work', giving the agent clear when-to-use guidance. While it does not mention when not to use it, the sibling tool compute_status is obviously for status checks, so the context is sufficient.

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

  • Behavior4/5

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

    Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds specific behavioral context by detailing the types of information reported and positioning it as a pre-flight check, which is useful beyond the annotations.

    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 two sentences with front-loaded purpose and no unnecessary words. Every phrase adds value, including the usage guidance.

    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 a single optional parameter, full annotations, and an output schema, the description provides sufficient context to invoke the tool correctly and understand when it is needed. The explicit usage scenarios complete the picture.

    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?

    The input schema provides 100% coverage with a clear description for the single parameter, including when to omit it. The description itself adds no parameter-specific meaning, so the baseline 3 is appropriate.

    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 'Check the configured Tailscale compute node and report its operating system, hardware, remote shell, and accelerator inventory.' This is a specific verb+resource+output list that distinguishes it from the sibling compute_run by indicating a status check before running.

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

    Usage Guidelines4/5

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

    The description explicitly says 'Use this before the first remote run or after a connection failure,' providing clear timing guidance. It does not explicitly state when not to use it or name alternatives beyond the sibling context, but the usage context is strong.

    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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  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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