"Créer des systèmes de prompt pour les modèles de langage (LLM)" matching MCP servers:

A standardized MCP server designed for testing integration with the Des MCP Server Testing API. It allows AI agents to interact with testing endpoints using tools implemented via the Model Context Protocol.

A server based on Model Context Protocol that provides predefined prompt templates for tasks like code review and API documentation generation, enabling more efficient workflows in Cursor/Windsurf editors.

Turn any OpenAPI/Swagger/Postman spec into an MCP server — give your LLM live access to any API.

Universal HTTP client tool for LLM agents. Enables Claude and other MCP-compatible agents to perform GET, POST, PUT, DELETE, and other HTTP requests to any URL, including localhost and internal network addresses.

Fault injection and reliability scoring for MCP servers. Scans tool output schemas, injects corrupted payloads, and measures contract enforceability. Model-free, deterministic, no LLM required.

Enables LLM agents to create, read, update, and delete Webhook.site tokens, list and retrieve captured requests, and manage webhook configurations via the Webhook.site API.

An MCP server that provides tools for exploring large OpenAPI schemas without loading entire schemas into LLM context. Perfect for discovering and analyzing endpoints, data models, and API structure efficiently.

A Model Context Protocol server that bridges LLMs (like Claude) with the Fitbit API, allowing the LLM to request and retrieve user health and fitness data through defined tools.

Postman’s remote MCP server connects AI agents, assistants, and chatbots directly to your APIs on Postman. Use natural language to prompt AI to automate work across your Postman collections, environments, workspaces, and more.

A Model Context Protocol server that loads multiple OpenAPI specifications and exposes them to LLM-powered IDE integrations, enabling AI to understand and work with your APIs directly in development tools like Cursor.

Turn any GraphQL API into MCP tools. Zero config, zero code. Auto-introspection, flat InputObject schemas for better LLM accuracy, smart truncation, retry logic with exponential backoff.

A zero-configuration tool that automatically exposes FastAPI endpoints as Model Context Protocol (MCP) tools, allowing LLM systems like Claude to interact with your API without additional coding.

A bridge that enables any LLM to access and interact with documented REST APIs through the Model Context Protocol (MCP).

Turn any OpenAPI specification into a smaller, LLM-friendly MCP server. Enables interaction with REST APIs through MCP tools using profiles to reduce complexity.

Enables AI agents to run deterministic API validation and UI DOM checks, verifying HTTP status codes, JSON schema fields, and page elements with programmatic proof instead of LLM guesswork.

Scan APIs for security vulnerabilities and get OWASP risk scores. Detects auth bypass, BOLA/IDOR, data exposure, prompt injection, and 12+ security categories.

MCP server that exposes Strapi v5 content management, visual layout configuration, schema authoring, media uploads, and GraphQL testing to LLM clients via native Strapi API tokens with security hardening.

Provides integration between Merge API and LLM providers supporting the MCP protocol, allowing natural language interaction with Merge data across HRIS, ATS, and other categories.

Turn any OpenAPI/Swagger spec into MCP tools. Zero config, zero code. Supports Swagger 2.0, OpenAPI 3.x, Bearer/API-key/OAuth2 auth, flat parameter schemas for better LLM accuracy, and smart response truncation.

A modular dynamic API server based on the MCP protocol that provides rich tool capabilities for AI assistants while significantly reducing prompt token consumption.