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awssam

mcp-swagger

by awssam

executeEndpoint

Executes API endpoints and returns actual responses, automatically using Swagger-defined headers. Ideal for testing and fetching real-time data.

Instructions

Exécute un endpoint API et retourne la réponse réelle. Utilise automatiquement les headers requis définis dans le Swagger. Parfait pour tester les endpoints et récupérer des données en temps réel.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyNoCorps de la requête pour POST/PUT/PATCH
pathYesLe chemin de l'endpoint (ex: /users/{id})
methodYesLa méthode HTTP
baseUrlNoURL de base du serveur (optionnel, utilise celle du Swagger par défaut)
headersNoHeaders personnalisés (ex: {"Authorization": "Bearer token"})
pathParamsNoParamètres de chemin (ex: {"id": "123"})
queryParamsNoParamètres de requête (ex: {"page": 1, "perPage": 10})
Behavior2/5

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

No annotations are provided, so the description carries full burden. It discloses that the tool returns the real response and automatically uses Swagger-defined headers, which is useful. However, it does not mention potential side effects (e.g., executing POST/PUT/DELETE mutates backend data), error behavior, authentication requirements, or rate limits. For an execution tool, this is a significant transparency 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?

Two sentences, front-loaded with the core action, no redundancy. Every word is information-dense and fits the purpose of an execution tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, but the tool is an execution tool with moderate complexity. The description lacks essential context about side effects, error scenarios, and security implications of calling endpoints. While the parameter list is well documented, the description fails to warn that mutating methods will actually change data. This is incomplete for a tool that directly invokes arbitrary API endpoints.

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?

Input schema covers 100% of parameter descriptions, so baseline is 3. The description adds context about automatic header handling and real response but does not elaborate on parameter syntax beyond what the schema already provides. Thus it adds marginal value.

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 'Exécute un endpoint API et retourne la réponse réelle' (executes an API endpoint and returns the actual response), which is a specific verb+resource. It distinguishes from sibling tools like listEndpoints and getEndpointDetails by emphasizing real-time execution rather than introspection of API definitions.

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 notes it is 'Parfait pour tester les endpoints et récupérer des données en temps réel' (perfect for testing endpoints and retrieving real-time data), implying use cases. It does not explicitly name alternatives or exclusions, but the contrast with sibling tools that inspect/retrieve definitions is implicit. This is clear context but lacks explicit '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.

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