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Fasping

LiveBrain MCP

by Fasping
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Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool serves a clearly distinct function: health checks server status, live_set_snapshot reads the current Ableton Live set, and generate_bassline creates a bassline. There is no overlap or ambiguity between them.

    Naming Consistency2/5

    Tool names follow mixed conventions: 'health' is a bare noun, 'live_set_snapshot' is a noun phrase, and 'generate_bassline' uses a verb_noun pattern. This inconsistency makes the naming pattern unpredictable.

    Tool Count4/5

    With only 3 tools, the server feels slightly under-scoped but remains reasonable for a focused integration. Each tool contributes a distinct capability without redundancy.

    Completeness4/5

    The server covers the core workflow of reading the Live set and generating a bassline, with health as a utility. Minor gaps exist (e.g., no update/apply function), but the primary purpose is adequately served.

  • Average 3.4/5 across 3 of 3 tools scored. Lowest: 2.8/5.

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

    • No community issues in the last 6 months
    • 29 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.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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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

  • Behavior2/5

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

    The description discloses one important behavioral trait: determinism. However, with no annotations, the description carries the full burden of explaining behavior. It does not mention what the output format is, how style-awareness is determined, or any side effects or prerequisites. This is insufficient for a tool with no additional metadata.

    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 a single, concise sentence with no wasted words. It is front-loaded with the core action and key attributes (deterministic, style-aware). While under-specified in other dimensions, as a structural summary it is efficient and does not ramble.

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

    Completeness2/5

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

    Given the tool has no output schema and minimal annotations, the description should provide more context about return values, expected behavior, and the meaning of 'style-aware.' It is incomplete for a tool with three parameters and no other structured metadata.

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

    Parameters1/5

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

    Schema description coverage is 0%, and the description does not compensate by explaining any of the three parameters (bars, seed, rootMidi). The schema only provides types and defaults, not semantics. Without descriptions, the agent cannot understand what each parameter controls, making this a critical gap.

    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 the tool generates a bassline, with a specific verb ('generate') and resource ('bassline'). It also notes determinism and style-awareness, distinguishing it from the unrelated sibling tools (health, live_set_snapshot).

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

    Usage Guidelines2/5

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

    No guidance is provided on when to use this tool versus alternatives, or under what circumstances it is appropriate. The description only states what it does, not when to use it. Sibling tools are unrelated, so no differentiation is needed, but no usage context is given.

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

  • Behavior2/5

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

    With no annotations provided, the description carries the full burden of disclosing behavior. It only states that the tool checks health, without detailing what that entails (e.g., connectivity, latency, component status), whether it is read-only, or what the response looks like. The description is too sparse to provide meaningful behavioral insight.

    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 a single, short sentence that immediately conveys the tool's purpose. There is no fluff or redundant information; every word contributes to clarity and it is front-loaded.

    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?

    Given the low complexity (0 parameters, no output schema), the description might be minimally adequate for a health check, but it lacks any explanation of return values, success/failure semantics, or what 'health' means. For a tool with no annotations or output schema, the description should offer just a bit more context, so a score of 3 reflects a bare-minimum completeness.

    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?

    The tool has zero parameters and the schema is trivially fully covered. Per the rubric, a baseline of 4 is appropriate for 0-parameter tools, and the description adds no unnecessary parameter information.

    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 a specific verb 'Check' and clearly names the resource 'LiveBrain MCP health', making the tool's purpose unmistakable. It naturally distinguishes itself from the sibling tools (live_set_snapshot and generate_bassline), which are unrelated to health checks.

    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 description implies the tool is for verifying system health but does not provide explicit guidance on when to use it versus alternatives, nor does it mention any prerequisites or exclusions. The usage context is apparent from the tool's name and description, but no explicit when/when-not is given.

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

  • Behavior3/5

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

    With no annotations, the description carries the full burden of behavioral disclosure. It explicitly says 'Read', which implies non-mutating behavior, but it does not describe return format, performance characteristics, or any side effects. It is minimally transparent but lacks depth.

    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 a single concise sentence that effectively states the tool's purpose. There is no fluff or redundant information, making it highly efficient.

    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 simplicity (no parameters, no output schema, no annotations), the description adequately covers its behavior. It could specify what the returned snapshot contains, but the name and description together imply a full representation of the Live Set, which is likely sufficient.

    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?

    The tool has zero parameters, and the baseline for 0-parameter tools is 4. No parameter description is needed, and the schema shows an empty object, so there is nothing more to add.

    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 a specific verb ('Read') and a clear resource ('the current Ableton Live Set'). It distinguishes itself from sibling tools like 'generate_bassline' and 'health' by indicating a read-only snapshot operation.

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

    Usage Guidelines2/5

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

    No guidance is provided on when to use this tool versus alternatives. There is no mention of context, prerequisites, or exclusions. The description only states what it does, not when to choose it.

    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 there are no obvious security issues.
  • Evaluate tool definition quality.

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