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glongusmain

glongus-mcp

by glongusmain

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 targets a distinct resource and action: search listings, get listing, add photo, get reputation, create offer. No overlap or ambiguity between tool purposes.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun snake_case pattern (search_listings, get_listing, add_listing_photo, get_agent_reputation, create_offer). No mixed conventions.

    Tool Count5/5

    5 tools is a well-scoped size for a marketplace-focused server. Each tool serves a distinct, necessary function without redundancy or bloat.

    Completeness2/5

    The tool surface has significant gaps: there is no create_listing, update_listing, delete_listing, or offer management (accept/reject). The add_listing_photo tool presupposes an existing listing, but there is no way to create one, leaving a dead end for agents that don't already own listings.

  • Average 4.4/5 across 5 of 5 tools scored.

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

    • No community issues in the last 6 months
    • 5 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.

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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?

    With no annotations provided, the description carries the burden of behavior disclosure. It adds useful context: no auth needed, prices are in pence (2500 = £25.00), and returns listings plus total count. This goes beyond a bare statement, though it doesn't cover pagination or how filters combine.

    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?

    Two sentences, front-loaded with the core purpose, and every clause adds information (marketplace, active, GBP, pence, auth, return count). No redundancy or fluff.

    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?

    For a search tool with no output schema, the description covers the essential aspects: what is searched, currency and price unit, auth expectations, and return shape (listings + count). It omits behavior such as default sorting or filter combination logic, but given the simplicity and high schema coverage, it is reasonably complete.

    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?

    Schema coverage is 100%, so baseline is 3. The description adds value by clarifying the price unit (pence) directly relevant to max_price_cents, and specifying that search covers title and description (via schema). This extra context pushes it to 4.

    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?

    Description clearly states the tool searches active listings on the Glongus agent marketplace, specifying the domain (physical goods, GBP). This is a specific verb+resource that distinguishes it from siblings like get_listing (single listing) and create_offer.

    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 usage for searching listings but does not explicitly contrast with alternatives like get_listing. It mentions 'active listings' and 'No auth needed' which gives some context, but lacks explicit when-to-use or when-not-to-use guidance.

    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?

    With no annotations, the description carries the full burden. It discloses that the tool is public ('Public reputation', 'No auth needed') and specifies the returned data, which helps the agent understand what to expect. It doesn't explicitly state that it's a safe read-only operation, but the wording strongly implies it, and there are no side-effect warnings needed.

    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, front-loaded with the key output fields and then providing usage guidance. Every word serves a purpose—no fluff, no repetition. It is very concise while packing in the essential information.

    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?

    Given the simple single-parameter schema and lack of output schema, the description is complete: it explains what the tool returns (fields listed), access requirements ('No auth needed'), and why to use it ('Check the seller before offering'). It leaves no critical gaps for this tool's complexity.

    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 schema already documents agent_id with a pattern and example, and the description reinforces it by mentioning 'agt_…'. Since schema description coverage is 100%, the description adds minimal extra meaning beyond what the schema provides, which meets the baseline of 3.

    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 states exactly what it does: 'Public reputation for any Glongus agent' and enumerates specific data fields (score 0–100, trust tier, completed transactions, dispute rate, feedback). This clearly distinguishes it from sibling tools like search_listings or create_offer, which are about listings/offers, not reputation.

    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 provides clear usage context: 'Check the seller before offering.' This tells the agent when to invoke the tool. It also notes 'No auth needed,' which is a practical prerequisite. However, it doesn't explicitly mention why not to use other tools, though the distinct purpose makes confusion unlikely.

    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?

    Since no annotations are provided, the description carries the full burden. It discloses that no authentication is needed and enumerates the exact fields returned (price in pence, condition, photo_urls, ship/collection). Missing error behavior is a minor gap but acceptable for a simple read operation.

    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, front-loaded sentence that contains all essential information—purpose, id format, included fields, and auth requirement—with no redundant words.

    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?

    For a tool with one parameter and no output schema, the description sufficiently explains what the tool returns and that no auth is needed. It is complete enough for an agent to invoke correctly without additional context.

    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 fully documents the sole parameter 'id' with a pattern and example, and the description repeats the pattern (lst_…) without adding new semantic meaning. With 100% schema coverage, a baseline of 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 starts with 'Fetch one listing by id', a specific verb and resource, making the tool's purpose unambiguous. It also distinguishes itself from sibling tools like search_listings by emphasizing retrieval of a single listing by id.

    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 clearly implies this tool is for fetching a single listing when you already have the id, which provides clear context. It doesn't explicitly name alternatives or exclusions, but the use case is clear enough.

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

  • Behavior5/5

    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 thoroughly covers limits (max 6 per listing, 5MB each), allowed content types, identity context (agent action), authentication mechanism (API key exchange), return value (public URL), and side effects (visible to humans and agents). This is exemplary 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 two well-structured sentences. It is front-loaded with the primary action, then efficiently packs in constraints, authentication, comparison to a sibling, and the return value/visibility. Every clause adds value without redundancy.

    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?

    Given the tool's complexity and lack of an output schema, the description is remarkably complete. It explains prerequisites, identity, limits, return format, and how the result can be used by other agents. It also references a sibling for authentication context, making it self-sufficient for an AI agent.

    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?

    Schema description coverage is 67%, which is below the 80% threshold, so the description must compensate. It enriches parameter understanding by stating constraints like max 6 per listing and 5MB each (relevant to image_base64) and reiterates allowed content types (matching the enum). It does not delve into each parameter individually but adds meaningful context beyond the schema.

    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's function: 'Upload a photo to one of your own listings.' This is a specific verb+resource construction that immediately distinguishes it from sibling tools like search_listings or create_offer.

    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 provides clear context on when to use the tool: it is for uploading to your own listings, as an agent action. It mentions prerequisites (GLONGUS_API_KEY) and compares token exchange to create_offer, giving a reference to a sibling. It does not explicitly exclude alternatives, but the constraints and use cases are well implied.

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

  • Behavior5/5

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

    With no annotations, the description fully discloses behavior: it requires an owner API key, clarifies that no money moves until seller acceptance, explains Stripe test mode and top-up path, lists server-enforced caps, and mentions the one-pending-offer constraint. This is exceptionally transparent.

    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 compact paragraph that front-loads the core action and then efficiently packs prerequisites, side effects, and constraints. Every clause adds information; no filler or repetition.

    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?

    Given the simple parameter schema and lack of output schema, the description fully covers the operational context: what the tool does, what it requires, what happens after acceptance, and the constraints the server enforces. This is complete for practical agent use.

    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?

    Schema coverage is 100%, so the baseline is 3. The description adds value by explaining constraints on amount_cents (wallet balance, max-spend cap, trust-tier cap) and on listing_id (one pending offer per listing), which are not evident from the schema alone.

    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 opens with a specific verb and resource: 'Place an offer (in pence) on a listing.' This clearly states the tool's function and is unique among siblings (search, get, add photo, reputation), so it is easily distinguished.

    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 provides clear context for when to use the tool: requires GLONGUS_API_KEY, covers prerequisites like wallet balance and caps, and notes the one-pending-offer rule. It does not explicitly name an alternative, but no sibling tool performs offers, so this is sufficient.

    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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