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LassiterJ

MCP Server Starter

by LassiterJ
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Hybrid

Server Quality Checklist

58%
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: echo handles text reflection, fetch retrieves specific documents by ID, and search performs document queries with minimal results. There is no overlap in functionality, making tool selection straightforward.

    Naming Consistency5/5

    All tool names follow a consistent, simple verb pattern (echo, fetch, search) without any deviations in style or convention. This uniformity enhances predictability and usability.

    Tool Count3/5

    With only 3 tools, the server feels minimal for a 'starter' purpose, potentially lacking depth for more complex tasks. While not extreme, it borders on being too thin for broader utility.

    Completeness2/5

    The tool set is severely incomplete for a document management domain, missing essential CRUD operations like create, update, or delete. Agents will face dead ends when trying to modify or manage documents.

  • Average 3/5 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 is failing

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  • 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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  "maintainers": [
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  ]
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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?

    No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the basic action ('echo back') but does not disclose any behavioral traits such as side effects, error handling, performance characteristics, or output format. For a tool with no annotation coverage, this is a significant gap in transparency.

    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, front-loading the core functionality. It is appropriately sized for a simple tool, making it easy to parse and understand without unnecessary details.

    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's simplicity, no annotations, and no output schema, the description is incomplete. It lacks information on behavioral aspects, usage context, and output details, which are necessary for the agent to fully understand how to invoke and interpret the tool effectively.

    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 has 100% description coverage, with the parameter 'text' fully documented in the schema. The description adds no additional meaning beyond what the schema provides, as it only repeats the concept of echoing text without elaborating on parameter usage or constraints. Baseline 3 is appropriate when the schema does the heavy lifting.

    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 'Echo back the provided text' clearly states the tool's purpose with a specific verb ('echo back') and resource ('the provided text'), making it easy to understand. However, it does not explicitly differentiate from sibling tools like 'fetch' or 'search', which might have overlapping or distinct functionalities, so it lacks sibling differentiation.

    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 like 'fetch' or 'search'. It does not mention any context, prerequisites, or exclusions for usage, leaving the agent without direction on appropriate scenarios or comparisons with sibling tools.

    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?

    No annotations are provided, so the description carries full burden. It mentions fetching and returning full text but doesn't disclose behavioral traits such as error handling, permissions needed, rate limits, or whether it's idempotent. This leaves significant gaps for a tool with no annotation coverage.

    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 appropriately sized and front-loaded, clearly stating the tool's purpose without unnecessary elaboration.

    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 no annotations, no output schema, and a simple input schema, the description is incomplete. It lacks details on return values, error conditions, and behavioral context, making it inadequate for a tool that performs data retrieval.

    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 100%, so the schema already documents the 'id' parameter. The description adds minimal value by implying the ID is for a 'search result document', but doesn't provide additional syntax or format details beyond what the schema specifies.

    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 ('fetch') and resource ('stub document'), specifying it returns full text. However, it doesn't differentiate from sibling tools like 'search' or 'echo', which could have overlapping functionality.

    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 'search' or 'echo'. The description implies usage for retrieving documents by ID but lacks explicit context or exclusions.

    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 behavioral disclosure. It states the tool searches and returns minimal results, but doesn't cover aspects like whether it's read-only, has rate limits, requires authentication, or how results are paginated/sorted. This leaves significant gaps for a search tool.

    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 front-loads the key action ('search stub documents') and outcome ('return minimal results'), with no wasted words. It's appropriately sized for a simple tool.

    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 simplicity (1 parameter, no output schema, no annotations), the description is adequate but incomplete. It covers the purpose and result format, but lacks behavioral details (e.g., error handling, performance) that would help an agent use it effectively, especially without annotations.

    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 has 100% description coverage, with the 'query' parameter fully documented. The description adds context by specifying it searches 'stub documents', but doesn't provide additional syntax, format, or examples beyond what the schema offers. This meets the baseline for high schema coverage.

    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 searches for 'stub documents' and returns minimal results (id, title, url), providing a specific verb ('search') and resource ('stub documents'). It distinguishes from the 'echo' and 'fetch' siblings by specifying its search functionality, though it doesn't explicitly contrast with them.

    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 like 'echo' or 'fetch'. It mentions returning 'minimal results', which implies a use case for quick searches, but lacks explicit when/when-not instructions or prerequisites.

    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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