mcp-leclerc-drive

Server Quality Checklist

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Latest release: v0.3.0
Disambiguation5/5
Each tool targets a distinct operation: product search, cart mutations (add, remove, update quantity, view), and store selection (find, get, set). No two tools overlap in purpose, and their descriptions make selection unambiguous.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern in snake_case (e.g., search_product, add_to_cart, set_store). The verb clearly indicates the action, and the noun indicates the resource, making the API predictable.
Tool Count5/5
With 8 tools, the set is well-scoped for the Leclerc Drive domain. Each tool covers a necessary step in the shopping workflow without redundancy or bloat, fitting the typical 3-15 tool range.
Completeness5/5
The tool surface covers the full shopping lifecycle: search products, manage cart items (add, remove, update quantity), view cart, and select the store. There are no obvious dead ends—search returns ids for adding, and store selection supports the entire flow.
Average 4/5 across 8 of 8 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 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

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The word 'complètement' discloses that the entire product is removed, but nothing is said about edge cases (product not in cart, cart doesn't exist) or side effects. With no annotations, the description carries the burden but only partially.
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?
A single concise sentence that is action-oriented and contains no unnecessary information.
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?
The tool is simple, but with no annotations or output schema, the description is minimal. It doesn't specify return value or error behavior, leaving some gaps.
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 coverage is 100% and product_id is already described. The description adds no additional meaning about the parameter, so baseline 3 applies.
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 ('Retire') and resource ('panier'), clearly distinguishing it from siblings like add_to_cart and update_quantity.
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 given on when to use this tool versus alternatives. It doesn't mention cases like adjusting quantity with update_quantity when only a partial removal is needed.
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 implies a read-only operation via 'Affiche' (displays), but does not explicitly state that it has no side effects or authentication requirements. It also does not mention behavior for empty carts or error handling.
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 front-loads the purpose. It contains no filler 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?
For a no-parameter, read-only cart viewer, the description adequately explains that it returns the full contents and total. However, it lacks details on response structure, empty cart behavior, or item quantities, which could be useful but are not critical for such a simple tool.
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 input schema has zero parameters, so the description correctly adds no param information. With 0 parameters, the baseline is 4, and the description aligns with the schema's 100% coverage without inventing anything.
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 displays the full cart contents and total, using the specific verb 'Affiche' (displays) with a clear resource. It distinguishes itself from sibling tools like add_to_cart or remove_from_cart by focusing on viewing rather than modifying.
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, such as when checking out or verifying items. It does not mention scenarios, prerequisites, or exclusions, leaving the agent to infer usage from the sibling context.
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?
The description provides context beyond the tool name by explaining that the product ID comes from search_product. However, with no annotations, it doesn't disclose side effects like what happens if the product is already in the cart or whether a cart must exist, leaving the agent partially in the dark about behavioral outcomes.
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 short, front-loaded sentences communicate the purpose and a critical prerequisite with no filler. Perfectly concise.
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 simple two-parameter tool with full schema coverage, the description is nearly complete. It names the action, the key parameter source, and with the sibling list, provides enough context for an agent to select and invoke the tool. The only gap is behavior on conflict, but this is a minor omission given the tool's simplicity.
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 fully describes both parameters (product_id and quantity) with clear descriptions. The tool description merely restates the product_id source, adding no new parameter-specific information. According to the baseline for high schema coverage, this is a 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 clearly states 'Ajoute un produit au panier' (adds a product to the cart), which is a specific verb and resource. It also references 'search_product' to obtain the product ID, distinguishing it from cart-related siblings like remove_from_cart or update_quantity.
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?
It explicitly tells the agent to use the ID returned by search_product, implying a prerequisite search step. However, it doesn't explicitly state when not to use this tool (e.g., for quantity updates vs. adding new items), so it gets a 4 rather than 5.
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 burden of transparency. It discloses sorting and return fields, but doesn't explicitly state this is a read-only search, mention result limits, or cover error cases. More explicit non-destructive language would improve it.
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 concise—two sentences, front-loaded with core purpose, then a structured list of return fields. No redundancy or unnecessary detail.
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 simple search tool with one parameter and no output schema, the description covers the essential behavior: what it does, sorting, and return fields. It also links to set_store. Minor gaps like pagination limits don't significantly impact completeness for this low-complexity tool.
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 only parameter 'query' is fully described in the schema (postal code or city) and the description repeats that. No additional parameter-specific meaning is added beyond the schema, so it stays at the baseline for high schema coverage.
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 searches E.Leclerc drives by postal code or city, sorted by distance. It also lists exact return fields, including the identifier to pass to set_store, distinguishing it from siblings like search_product or cart tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies a workflow by noting the identifier should be passed to set_store, suggesting use before store selection. However, it doesn't explicitly state when to use this tool vs alternatives or provide exclusions, so it stops short of full guidelines.
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 discloses return fields (label, price, price per kilo/liter, Nutri-Score, availability, and id) and references the configured store, which implies a dependency on store configuration. However, it does not mention error behavior, pagination, or any rate limits, so it is only partially 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 single, concise sentence that front-loads the main action and lists key return fields without unnecessary detail. It does not repeat what the schema already provides.
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 simple search tool with one parameter and no output schema, the description is fairly complete. It lists the return fields and mentions the store context, which is sufficient for an agent to understand the tool's role and basic behavior. It lacks minor details like sorting or limits, but those are not critical for a simple search.
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 describes the 'query' parameter with an example, achieving 100% coverage. The description does not add meaning beyond the schema, so the baseline score 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 clearly states the tool's function: searching for products in the Leclerc Drive catalog of the configured store. It specifies the resource ('produits dans le catalogue Leclerc Drive') and verb ('Recherche'), and distinguishes itself from sibling tools by focusing on search rather than cart operations or store management.
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 implies usage context by noting the search returns an 'id à utiliser pour add_to_cart', guiding when to use this tool (before adding items). It does not explicitly state alternatives or exclusions, but the sibling tools and the described return fields make the use case clear.
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?
No annotations are provided, so the description carries the burden. It discloses the key constraint that the product must already be in the cart, which is a behavioral trait. However, it does not mention that setting quantity to 0 removes the item (though the schema does), nor does it describe error behavior for a missing product ID. This is a clear gap.
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 in French. It front-loads the action and avoids unnecessary wording, making it easy to scan and understand.
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?
With only 2 parameters, both fully described in the schema, and no output schema, the description provides the essential purpose and a key constraint. It is adequate for an agent to invoke the tool correctly, though it could mention return values or failure modes. For a simple cart operation, a 4 is justified.
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 provides descriptions for both required parameters (quantity and product_id) with 100% coverage. The description adds no extra parameter information beyond the schema, so the baseline score 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 clearly states the action ('Modifie' = modifies) and the resource ('la quantité d'un produit déjà présent dans le panier' = the quantity of a product already in the cart). It explicitly distinguishes this tool from siblings like add_to_cart and remove_from_cart by noting the product must already be in the cart.
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 implies the tool is for updating an existing cart item's quantity, which gives clear usage context relative to add/remove siblings. However, it does not explicitly name alternative tools or state when not to use it, so it stops short of full guidance.
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?
No annotations are provided, so the description must carry the behavioral disclosure burden. It correctly indicates a read operation and mentions output fields, but it does not describe what happens if no store is selected, authentication needs, or error behavior. These gaps are meaningful but not critical for such a simple getter.
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 front-loads the action and output. Every word contributes to understanding.
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 simple getter with no parameters, the description is nearly complete: it states the resource, scope, and output fields. It omits edge cases like 'no store selected' and does not explicitly declare read-only behavior, but sibling tool context and the nature of the tool make this acceptable.
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 complete. The description adds no parameter-specific information, but none is needed. The baseline of 4 for zero-parameter tools applies.
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 'Affiche' and clearly identifies the resource ('le magasin actuellement sélectionné') and expected output ('id, host'). This distinguishes it from sibling tools like find_stores (searching stores) and set_store (changing the selected store).
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?
'actuellement sélectionné' provides clear context that this tool retrieves the current store selection, implicitly distinguishing it from find_stores and set_store. However, it does not explicitly state alternatives or when not to use it.
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 provided, the description carries the burden of disclosing side effects. It explicitly states that the selection is remembered for future sessions ('le mémorise pour les prochaines sessions'), which is a key behavioral trait beyond the schema. It does not mention other details like error handling, but the essential persistence behavior is disclosed.
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, well-structured sentence that front-loads the core purpose and then adds the key usage hint and persistence detail. Every part is informative with no redundant filler.
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 simple state-setting tool with no output schema, the description is complete enough: it identifies the action, the target resource, the persistence side effect, and the correct parameter source. The optional host parameter is covered by the schema, so no additional description is required.
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 parameters store_id and host are already well-documented in the schema. The description adds the meaningful relationship that store_id comes from find_stores, but otherwise does not add significant new semantic value beyond what the schema provides.
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: 'Sélectionne le magasin actif' (selects the active store). It also distinguishes it from the sibling get_store by emphasizing the state-changing and persistent nature of the operation, and references find_stores as the source for the 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 gives explicit usage guidance by stating to use the ID returned by find_stores, which is a clear prerequisite and points to the correct sibling workflow. It does not explicitly describe when not to use the tool or compare with alternatives, but the context is clear.
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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