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GaloisHLee

MCP SageMath Server

by GaloisHLee
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TypeScript
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Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: sagemath_evaluate executes code, sagemath_health checks system readiness, and sagemath_version retrieves version info. There is no overlap in functionality, making tool selection straightforward for an agent.

    Naming Consistency5/5

    All tool names follow a consistent snake_case pattern with the 'sagemath_' prefix followed by a descriptive action (evaluate, health, version). This uniformity enhances predictability and readability across the tool set.

    Tool Count3/5

    With only 3 tools, the server feels thin for a SageMath domain, which typically involves complex mathematical operations. While the tools cover basic evaluation and system checks, more operations (e.g., for algebra, calculus, or plotting) would be expected for a comprehensive server.

    Completeness2/5

    The tool surface is severely incomplete for a SageMath server. It lacks core mathematical operations like solving equations, symbolic manipulation, or numerical computation, leaving significant gaps that will hinder agents from performing typical SageMath tasks beyond simple code evaluation.

  • Average 3.4/5 across 3 of 3 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

  • 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

  • Behavior2/5

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

    With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool evaluates code 'locally,' which implies execution in a SageMath environment, but doesn't specify security implications, resource usage, error handling, or output format. The presence of a timeout parameter hints at execution limits, but this isn't explained in the description.

    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, efficient sentence with zero waste. It's front-loaded with the core purpose and avoids unnecessary elaboration, making it easy to parse quickly.

    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 tool's complexity (code evaluation with potential side-effects), no annotations, and an output schema (which handles return values), the description is minimally adequate. It states what the tool does but lacks crucial details like safety warnings, execution context, or error behavior, leaving gaps for the agent to navigate.

    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?

    Schema description coverage is 0%, so the schema provides no parameter documentation. The description doesn't mention parameters at all, failing to compensate for the coverage gap. However, with only 2 parameters (code and timeoutMs), the baseline is moderate, as the agent might infer usage from common patterns (code to evaluate and optional timeout).

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the action ('Evaluate') and resource ('SageMath code'), with the qualifier 'locally' providing useful context. However, it doesn't differentiate from sibling tools like sagemath_health or sagemath_version, which likely serve different purposes (health checks and version queries rather than code evaluation).

    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?

    The description provides no guidance on when to use this tool versus alternatives. There's no mention of prerequisites, limitations, or comparison with sibling tools. The agent must infer usage from the tool name and context alone.

    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 provided, the description carries the full burden. It describes the tool as a 'lightweight self-check' which implies it's a read-only, non-destructive operation that tests availability and readiness. However, it doesn't specify what 'readiness' entails, potential error conditions, or performance characteristics like execution time.

    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, efficient sentence that clearly communicates the core functionality without unnecessary words. It's appropriately sized for a simple health check tool and front-loads the essential information.

    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 (zero parameters, has output schema), the description is reasonably complete. The output schema will handle return value documentation, so the description appropriately focuses on purpose. However, it could better address when to use this versus sibling tools for full 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 with 100% schema description coverage. The description appropriately doesn't discuss parameters since none exist, maintaining focus on the tool's purpose. This meets the baseline expectation for parameterless tools.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the tool's purpose: 'Lightweight self-check of SageMath availability and basic readiness.' It specifies the verb ('self-check') and resource ('SageMath'), but doesn't explicitly differentiate from sibling tools like 'sagemath_version' which might provide similar system information.

    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?

    The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'sagemath_evaluate' or 'sagemath_version', nor does it specify scenarios where a health check is appropriate versus other diagnostic operations.

    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 provided, the description carries the full burden. It indicates a read-only operation ('Get') but doesn't disclose behavioral traits such as performance characteristics, error handling, or what specific information is returned. It's minimally adequate 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, efficient sentence with no wasted words. It's front-loaded with the core purpose, making it easy to understand quickly. Every part of the sentence earns its place.

    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 (0 parameters, no annotations, but with an output schema), the description is reasonably complete for its purpose. However, it could benefit from more context about the output format or usage scenarios, especially with sibling tools present.

    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 0 parameters with 100% schema description coverage, so the schema fully documents the input structure. The description adds no parameter details, which is acceptable here, but doesn't compensate for any gaps since there are none. Baseline is 4 for zero parameters.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the action ('Get') and resource ('local SageMath version information'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'sagemath_health' which might also provide version-related information, preventing a perfect score.

    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 like 'sagemath_health' or 'sagemath_evaluate'. The description implies usage for retrieving version info but lacks explicit context, prerequisites, or exclusions.

    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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