Adopte un Conteneur - Container Delivery & Dimensions
Server Details
Delivery cost calculator and container dimensions for France. Real HT/TTC prices.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- adopteunconteneur/mcp-container-delivery
- GitHub Stars
- 0
- Server Listing
- Adopte un Conteneur — Container Delivery Calculator
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Tool Definition Quality
Average 3.9/5 across 2 of 2 tools scored.
The two tools have entirely distinct purposes: one calculates delivery costs, the other retrieves container dimensions. There is no overlap or confusion possible.
Both tool names use consistent camelCase and follow a verb+noun pattern ('calculateContainerDeliveryCost' and 'getContainerDimensions'), making the naming predictable and clear.
With only 2 tools, the server feels thin for a domain that could encompass more operations like listing container types or depot locations, but it may be appropriately scoped for a focused info service.
The tools cover cost calculation and dimensions, which are core to the domain, but lack operations for ordering, managing, or updating container data, leaving notable gaps.
Available Tools
2 toolscalculateContainerDeliveryCostAInspect
Calcule le coût de livraison d'un ou plusieurs conteneurs maritimes vers une adresse en France. Sélectionne automatiquement le dépôt le plus économique et retourne le prix réel HT et TTC.
| Name | Required | Description | Default |
|---|---|---|---|
| quantity | Yes | Nombre de conteneurs à livrer | |
| container_type | Yes | Type de conteneur : 20ft, 40ft ou 40ft_hc (High Cube) | |
| delivery_address | Yes | Adresse complète ou ville de livraison en France |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must disclose behavioral traits. It notes automatic depot selection and the output fields (HT and TTC prices), which adds value. However, it omits details about error handling, address validation, or any rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two clean sentences with no extraneous words. It efficiently conveys the core purpose and key features, making it easy for an agent to quickly understand the tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has three required parameters and no output schema, the description adequately covers the return values (HT and TTC prices) and the automatic depot selection. It is complete for the tool's complexity, though it could mention potential error scenarios.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for all three parameters, so each parameter's meaning is already clear in the schema. The description does not add further semantics beyond the schema, meeting the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates delivery cost for maritime containers to a French address, automatically selects the cheapest depot, and returns pre-tax and inclusive-tax prices. This accurately identifies the tool's function and distinguishes it from the sibling tool getContainerDimensions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for cost estimation but does not explicitly state when to use versus alternatives, or when not to use. It provides context (delivery to France) but lacks guidance on exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
getContainerDimensionsAInspect
Retourne les dimensions intérieures et extérieures, volumes, surfaces et poids des containers. Permet de filtrer par type (stockage, dry, high_cube, reefer), taille (6ft à 45ft), volume minimum ou surface minimum. Inclut les surfaces combinées pour plusieurs containers accolés.
| Name | Required | Description | Default |
|---|---|---|---|
| size | No | Taille du container en pieds. Omis = toutes les tailles. | |
| type | No | Type de container. Omis = tous les types. | |
| quantity | No | Nombre de containers accolés (2, 3 ou 4) pour obtenir la surface combinée. Nécessite size=20ft ou size=40ft. | |
| min_volume_m3 | No | Volume intérieur minimum en m³ (ex: 30 pour trouver un container d'au moins 30m³) | |
| min_surface_m2 | No | Surface intérieure minimum en m² (ex: 13 pour trouver un container d'au moins 13m²) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description clearly indicates a read-only query returning data based on filters. It does not mention side effects or authorization needs, which is acceptable for a straightforward retrieval tool. The behavior is transparent enough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph of two sentences, front-loading the main purpose. It is concise without unnecessary words, though slightly more structure could improve readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the filtering options and returned data types but does not specify the exact structure of the output (e.g., whether fields are nested). For a tool with no output schema, more detail would enhance completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides 100% coverage of parameter descriptions, and the tool description adds extra context (e.g., combined surfaces for multiple containers). This complements the schema effectively.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns interior/exterior dimensions, volumes, surfaces, and weights of containers, with filtering capabilities. It distinguishes itself from the sibling tool calculateContainerDeliveryCost by focusing on dimensions rather than costs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description lists filtering criteria (type, size, volume, surface) and mentions combined surfaces for multiple containers, but does not explicitly state when to use this tool versus the sibling or provide exclusion conditions. Usage is implied but not explicit.
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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