"Île-de-France Mobilités" matching MCP servers:

Optimizes REST API calls for AI agents by returning compact schemas instead of full responses, allowing agents to fetch only needed fields via jq masks, reducing token consumption by up to 50x.

MCP server that exposes RESTForge capabilities to AI agents, enabling them to set up, configure, generate code, and manage RESTForge projects through natural language.

MCP server for lolzteam/lzt.market ecosystem providing 29 tools for raw API requests, flow scenario management, event subscriptions, and API introspection.

A server that interfaces with the Hedera Testnet Mirror Node API, converting its OpenAPI-defined endpoints into MCP-compatible tools that can be accessed over Server-Sent Events (SSE).

DreamFactory MCP Server enables AI assistants like Claude to directly query your databases through DreamFactory's auto-generated REST APIs. This Node.js server implements the Model Context Protocol (MCP), allowing natural language database interactions while maintaining enterprise-grade security.

Enables AI assistants to interact with Dev Proxy for creating configurations, finding documentation, and discovering best practices via the MCP standard.

Provides a tool to inspect and execute actions on a scaffolding API through Siren hypermedia links, enabling management of scaffolding resources without endpoint knowledge.

Dynamically creates MCP servers from web API configurations, enabling AI assistants to interact with any REST API, GraphQL endpoint, or web service.

Enables AI assistants to interact with Magic-API development environment, supporting script syntax query, API management, debugging, and knowledge search for efficient development.

Enables AI assistants to interact with the Post For Me API, allowing them to explore endpoints, make test requests, and use documentation to help integrate this SDK into your application.

Enables MCP clients to check whether third-party API responses have drifted, inspect expected schemas, review change history, list monitored endpoints, and trigger checks before agents trust an API.

Enables AI agents to develop SAP Cloud Integration content by editing iFlows, Groovy scripts, and XSLT locally, validating and checking them, then pushing, deploying, and testing on development tenants. It supports package and artifact inspection, model-level diffs, script and XSLT runs, and tenant message testing with safety controls.

MCP server for REST API reverse engineering from HTTP traffic captures, wrapping mitmproxy for live capture and mitmproxy2swagger for spec derivation.

Enables developers to access kintone API specifications, field type documentation, and development best practices through natural language queries. Supports API request validation and provides comprehensive development guidance for kintone customizations.

Gives AI coding agents dereferenced OpenAPI facts about the backend being implemented, and verifies that implementation against a local server via ping probes, single requests, contract tests, and ordered multi-step scenarios with extraction and assertions. It also spins up loopback mocks for missing dependencies and derives a relational data model from the spec, reconciling it with optional live database evidence and emitting additive SQL that is never executed.

Enables interaction with e-commerce storefronts through a standardized API. Provides access to product catalogs, inventory management, and customer operations for online retail platforms.

Enables Gemini AI to interact with a FastAPI application through MCP tools for user management, task management, and dice rolling functionality. Provides natural language access to REST API endpoints including CRUD operations, health checks, and application statistics.

A demonstration server that automatically generates Model Context Protocol (MCP) servers from OpenAPI specifications, providing seamless integration with FastAPI and supporting various transmission methods like STDIO, HTTP, and SSE.

A Model Context Protocol service registry and connector framework that enables seamless integration with multiple services and models through a standardized API interface. Provides an extensible architecture for custom service adapters, API integrations, and model registries.

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.

API documentation drifts away from the running service, so consumers integrate against a contract nobody keeps. Routebase keeps API design, testing, mocking and documentation on one living source of truth, and this MCP server lets AI agents work in that workspace under the permissions of the connected account.