OVS MCP
Server Quality Checklist
Latest release: v1.1.0
- Disambiguation5/5
Each tool targets a distinct concern: connection, product search, cart read, add, and remove. There is no overlap or ambiguity between tools.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern with underscores: connect_ovs, search_products, get_cart, add_to_cart, remove_from_cart. Naming is uniform and predictable.
Tool Count5/5The set of 5 tools is well-scoped for a shopping cart and catalog server. Each tool serves a clear function without unnecessary bloat or missing essentials.
Completeness4/5The surface covers connection, catalog search, and cart CRUD operations (read, add, remove). Minor gaps include lack of an explicit update quantity tool, but add/remove can adjust quantities, so overall coverage is solid.
Average 4.1/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 9 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
This repository is licensed under MIT License.
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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
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds useful behavioral context beyond the annotations: credentials never pass through MCP and a private local URL is returned to present to the user. It does not mention potential side effects or trigger conditions for 'when needed', which is a gap. No contradiction with 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences, front-loaded with the action, and contains no filler. Every sentence adds useful information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With zero parameters and an output schema present, the description covers the essential purpose, the key output behavior, and a security guarantee. It lacks only an explicit trigger condition for when the login URL is returned, but overall it is sufficiently complete for this simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline of 4 applies. The description adds operational context but there are no parameter semantics to clarify.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks the OVS connection and returns a login URL when needed, which distinguishes it from the product/cart siblings. The slight mismatch between the tool name 'connect' and the verb 'check' creates minor ambiguity but does not obscure the core function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The usage context is implied: use when needing to check/establish the OVS connection and obtain a login URL. However, there is no explicit guidance on when not to use it, prerequisites, or comparison with alternative tools.
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, covering safety. The description adds the behavioral context of searching a 'live' catalog, indicating real-time data, which is not explicitly in 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that directly states the tool's purpose without any excess wording. It is front-loaded and easily scannable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple search tool with rich annotations and an output schema, the description adequately covers purpose and scope. However, it lacks parameter semantics and any usage guidance, leaving gaps that could affect correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides zero descriptions for the three parameters (query, page, limit), and the description does not mention any of them. While query is implicitly the search term, page and limit pagination semantics are completely unexplained, failing to compensate for the low schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches the live Official Vegan Shop catalog, specifying a distinct verb and resource. It differentiates from sibling tools like get_cart and add_to_cart, which focus on cart operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The verb 'search' implies usage for product discovery, but there is no explicit guidance on when to use this tool versus alternatives or any conditions. The description does not mention exclusions or prerequisites, leaving usage only implicitly conveyed.
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 indicate destructiveHint=true, and the description adds value by disclosing a confirmation step ('preview, confirm') and quantity semantics ('one or more units'). This goes beyond the structured data without contradicting it, though it does not detail all side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no redundant words. Every element ('Preview, confirm, remove', 'one or more units', 'OVS product ID') contributes meaning, making it both concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has an output schema and annotations, but the description does not clarify the preview/confirm workflow—specifically whether confirmationToken is needed for removal or just for preview. This gap could lead to incorrect invocation, so the description is only partially complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It partially does by mapping 'one or more units' to quantity and 'OVS product ID' to productId, but it fails to explain the confirmationToken's role or when it is required, leaving ambiguity for that parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verbs 'Preview, confirm, and remove' and clearly identifies the resource (OVS product ID) and action (remove from cart). This distinguishes it from sibling tools like add_to_cart and get_cart, making the 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 Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for removing cart items but does not explicitly state when to use this tool versus alternatives, nor does it mention any exclusions. The phrase 'Preview, confirm' hints at a workflow but lacks clear context on when this tool is appropriate.
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 indicate readOnlyHint=false and destructiveHint=true, so the agent knows it is a mutative operation. The description adds value by disclosing a preview-confirm-add workflow, which is not evident from the annotations or schema alone. It does not contradict 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the action ('Preview, confirm, and add') and includes no unnecessary words. It is efficiently structured and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 3 parameters, an output schema, and useful annotations, so the description does not need to explain return values or basic safety. The description covers the core purpose and workflow, though the exact role of confirmationToken could be clearer. It is adequate but not exhaustive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It references 'OVS product ID' (productId), 'one or more units' (quantity), and 'confirm' (confirmationToken), giving contextual meaning to all three parameters. While not highly detailed, it provides essential semantic cues beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (add), the resource (OVS product ID), and the scope (to cart), distinguishing it from sibling tools like remove_from_cart. The verb 'add' is specific and directly aligns with the tool's name and title.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used to add OVS products to a cart, providing clear context. However, it does not explicitly mention when to use this tool over alternatives or when not to use it, though the sibling context makes this reasonably inferable.
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?
Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, but the description adds specific context about what is deliberately omitted (customer and address data). This exceeds the annotation coverage and clarifies the tool's scope, which is valuable for an agent deciding whether this tool meets the needs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, succinct sentence that is front-loaded with the core action ('Read the connected account cart') and immediately clarifies the scope. Every word contributes meaning, with no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with zero parameters, an output schema, and comprehensive annotations, the description is fully sufficient. It clarifies the key behavioral nuance (no customer/address data), and the sibling tool names provide enough context to understand the tool's role in the cart workflow.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the input schema is empty. Per the rubric, a baseline of 4 applies for zero-parameter tools. The description adds no parameter-related meaning, but none is needed since no parameters exist.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Read') and resource ('the connected account cart'), making the purpose unambiguous. It also explicitly excludes customer/address data, which differentiates this read-only cart retrieval from the write operations (add_to_cart, remove_from_cart) and other sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does 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: to read the connected account cart. It doesn't explicitly name alternatives or state when not to use it, but the sibling context and the read-only nature make the use case obvious. No exclusions are mentioned.
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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