"Checking Supabase migrations in GitHub Actions" matching MCP servers:

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

Enables natural-language testing of MCP servers—covering tools, resources, prompts, contracts, and transports—without writing test code, with deterministic validation and CI integration.

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.

Lets AI assistants safely explore a Matrix42 instance by discovering web services and the data model, running validated ASQL queries, searching the service desk, and previewing ticket actions — read-only by default and without exposing credentials.

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.

MCP server for reading, writing, and organizing API documentation in Apidog.

Point Claude at any API. JitAPI figures out which endpoints to call and in what order — automatically. Register any OpenAPI spec, search endpoints in plain English, and orchestrate multi-step workflows across multiple APIs. No API keys required — works out of the box with local embeddings.

Turn any REST API into a hosted MCP server. 18 free public servers (GitHub, Stripe, Slack, OpenAI, Notion, and more) — no setup required, bring your own API key.

Enables LLMs to dereference and query OpenAPI/Swagger specifications, search endpoints and schemas, validate payloads, extract security schemes, and generate production-ready integration code in multiple languages.

Enables AI agents to create, run, and save API requests and collections as local Gud API files, which are git-committable and viewable in VS Code-compatible editors.

Enables AI coding assistants to discover, inspect, and run API requests in Bruno collections locally, keeping all data private.

Enables direct integration with YApi API documentation platform in MCP-compatible editors like Cursor, allowing users to query API details, list interfaces, and search endpoints by simply pasting YApi URLs.

A Model Context Protocol server that creates tools from API configurations defined in YAML files, allowing easy integration of external APIs into an MCP ecosystem without coding.

Monitors API endpoint health by checking availability, measuring response times, and providing detailed status reports with error handling and timeout protection for the localhost:8080/api/ticket endpoint.

An MCP server for checking OWASP Top 10 vulnerabilities during API development testing. It analyzes API information and returns security assessment results to help developers identify potential security issues.

Enables AI tools to create and manage API requests and collections in Thunder Client, with automated collection and folder creation.

Enables AI agents to create, manage, and execute API collections, requests, and environments in Insomnia-compatible formats. It supports direct synchronization with the local Insomnia app database and importing from OpenAPI, Postman, and cURL.

Enables validation of OpenAPI 2.0 and 3.0 specifications in JSON or YAML format using APIMatic's comprehensive API validation service through the Model Context Protocol.

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.

Generates API documentation in Confluence from Swagger/OpenAPI specs or NestJS controller files, including automatic Postman collection generation.