"Reading terminal outputs from a Next.js dev server while developing in Cursor" matching MCP servers:

Enables users to expose arbitrary HTTP APIs as configurable MCP tools by defining tool specifications in a JSON configuration file.

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

A utility tool that analyzes Next.js application routes and provides detailed information about API paths, HTTP methods, parameters, status codes, and request/response schemas.

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.

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

Integrates XAPIHub API services with the Cursor IDE to enable user authentication, real-time data fetching, and connection diagnostics. It allows developers to interact with their XAPIHub organization and manage user details directly through natural language commands.

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

Goodday‑MCP is a lightweight Model Context Protocol (MCP) server designed to seamlessly integrate with the Goodday project management platform via its API v2. It enables querying of projects, tasks, and users—without altering any data—making it ideal for secure context-aware applications

A Node In Layers package that simplifies creation of MCP (Model-Control-Protocol) servers with tools for defining models, adding CRUD operations, and interacting with clients.

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.

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

Provides AI assistants with access to OpenAPI specifications, enabling API discovery, schema retrieval, and direct API execution with support for OAuth 2.0 and other authentication methods.

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).

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.

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 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.

Enables Claude to create local, persistent mock REST APIs on demand from plain-language descriptions, with data written to disk so it survives restarts.

Enables LLMs to make HTTP requests with OAuth2, session cookies, retry logic, and cURL command generation, while providing security features like SSRF protection and TLS enforcement.

Enables agents to interact with the Logflare API by writing JavaScript functions that run in a Vercel Sandbox, using three tools: search, execute_read, and execute_write.

Run the requests in a Postman collection folder and get structured, assertion-level results back straight from your AI assistant.