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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 DescriptionsA

Average 4/5 across 2 of 2 tools scored.

Server CoherenceA
Disambiguation5/5

The two tools have completely distinct purposes: one calculates delivery costs, the other retrieves dimensions. No overlap.

Naming Consistency5/5

Both use a consistent verb_noun camelCase pattern (calculate... and get...), which is clear and predictable.

Tool Count3/5

Two tools is minimal but acceptable for a narrowly focused server on container delivery and dimensions. It feels somewhat thin but not unreasonable.

Completeness3/5

The tools cover the core functions implied by the server name (cost calculation and dimension lookup), but lack additional operations like listing depots or placing orders, leaving minor gaps.

Available Tools

2 tools
calculateContainerDeliveryCostAInspect

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
quantityYesNombre de conteneurs à livrer
container_typeYesType de conteneur : 20ft, 40ft ou 40ft_hc (High Cube)
delivery_addressYesAdresse complète ou ville de livraison en France
Behavior3/5

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

Discloses automatic depot selection and return of HT/TTC prices. No annotations provided, so description partially covers behavioral traits. Lacks details on potential side effects, authorization needs, or completeness of price calculation.

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 efficiently convey purpose and key behavior. No redundant information.

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?

Given no output schema, description hints at return fields (HT/TTC). Parameters are simple and well-documented. Could specify address format or currency, but overall adequate for a straightforward cost calculation 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?

Schema description covers all 3 parameters (100%). Description reiterates them in context but adds no extra semantic value beyond the schema definitions. Baseline score of 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?

Clear verb 'calcule le coût de livraison' with specific resource 'conteneurs maritimes vers une adresse en France'. Distinct from sibling 'getContainerDimensions' which focuses on dimensions.

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 on when to use this tool versus alternatives. Does not specify prerequisites (e.g., address format) or when not to use it. Only describes the core function.

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
sizeNoTaille du container en pieds. Omis = toutes les tailles.
typeNoType de container. Omis = tous les types.
quantityNoNombre de containers accolés (2, 3 ou 4) pour obtenir la surface combinée. Nécessite size=20ft ou size=40ft.
min_volume_m3NoVolume intérieur minimum en m³ (ex: 30 pour trouver un container d'au moins 30m³)
min_surface_m2NoSurface intérieure minimum en m² (ex: 13 pour trouver un container d'au moins 13m²)
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It clearly indicates the tool returns data (retourne) and mentions constraints like quantity needing size 20ft or 40ft. It does not discuss authentication or rate limits, but the read-only nature is implied.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and covers the main functionality in a few sentences. It is well-structured, but could be slightly more organized by separating filter options from output details.

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?

Given no output schema, the description adequately describes the return values (dimensions, volumes, surfaces, weights) and parameters. It could be more explicit about the output format (e.g., list of containers) but is generally 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%, but the description adds context such as using quantity for combined surfaces and requiring specific sizes. It also explains the purpose of volume and surface filters with examples.

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 it returns dimensions, volumes, surfaces, and weights of containers, with filtering by type, size, volume, and surface. It also mentions combined surfaces for multiple containers. This clearly distinguishes it from the sibling tool for delivery cost.

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 explains filtering options and the quantity parameter's requirement for specific sizes. However, it does not explicitly state when to use this tool versus the sibling tool, though the sibling's purpose is distinctly different.

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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