"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.

Enables active, authorized security testing of remote MCP servers' OAuth authorization flows, reporting results as JSON, SARIF, and Markdown. It runs checks for refresh token rotation, redirect URI strictness, PKCE enforcement, token audience, throttling, and consent CSRF.

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.

Enables agents to probe one or more paid HTTP endpoints and verify they actually return a usable 402 payment challenge — checking status, Base64/JSON envelope validity, required payment fields, MPP dual-stack discoverability, and whether gated content leaks for free. Results come back with A–F grades and plain-English findings, backed by batch scanning and live catalog health stats, without ever sending a payment.

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

Lets AI coding agents list captured webhooks, explain why a signature failed, replay events to localhost and generate handler code. Works with Stripe, GitHub, Shopify, Slack and Twilio.

Provides Plaid developers with sandbox integration tools for creating test items, reading financial data, simulating webhooks and login failures, plus docs-quality tools for API search and OpenAPI-vs-Postman-vs-docs drift checking.

Runs, tests and edits the saved HTTP requests in a Kurlo API workspace (Git-backed YAML): list collections and environments, send requests with their auth and pm.* tests, write new requests and tests, and diagnose the last failure. Secret values are sent to the API but masked in every tool result, and protected environments are refused.

A small native HTTP client whose MCP server (plunger mcp) lets an AI agent send requests safely: undefined variables are refused, secrets are filled in by name and masked in results, and every request is recorded in a history you can see in the window. MIT licensed, for Windows, with a Linux build of the CLI and MCP server.

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.

A local stdio server that lets coding agents build and verify a merchant payment integration against a sandbox, creating and cancelling invoices, simulating payment outcomes, checking invoice status, and validating webhook signatures. It also serves embedded docs as resources and refuses live or payout keys, keeping all work out of production paths.

Enables agents to verify real-world assertions like content being posted or PRs merged by fetching live evidence from URLs and GitHub, returning a verified boolean plus raw evidence.

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 detection of breaking API changes across OpenAPI, Swagger, GraphQL, gRPC, AsyncAPI, and SOAP contracts, identifying affected consumers, checking deployed drift and live conformance, and generating contract tests.

Enables developers to integrate Kount Payments Fraud v2 from a coding assistant by inspecting API contracts, generating and validating synthetic requests, authenticating against Sandbox, troubleshooting errors, and checking integration readiness.

Enables generating complete multi-step API workflows, converting scenario outlines to HTTP steps, and checking server status through MCP tools.

Enables AI agents to read realistic, coherent data—repos, pull requests, issues, commits, users—through API-compatible, read-only replicas of 21 developer platforms including GitHub, Jira, Linear, Slack, Sentry and Salesforce, all preloaded with one simulated company so integrations can be built and tested with no accounts, credentials, rate-limit worry, or cleanup.

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.

Enables measuring, comparing, and health-checking endpoint response times through natural language, using tools to probe URL latency and compare two URLs.

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.

Enables autonomous agents and CI pipelines to execute declarative multi-step REST API workflows in a single tool call, with in-memory variable chaining, assertions, and built-in SSRF protection.

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.

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 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 provides tools for fetching and posting HTTP data, with built-in prompts for URL summarization and API analysis.

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.

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.

Aggregates multiple third-party APIs into unified MCP tools, providing out-of-the-box access to 10 popular services including OpenWeather, Google Maps, GitHub, Notion, Spotify, and more. Enables users to interact with weather data, search places, manage repositories, create content, and access various web services through a single MCP server.

An MCP (Model-Controller-Processor) server for accessing League of Legends client data. This server provides a collection of tools that communicate with the League of Legends Live Client Data API to retrieve in-game data.

Bridges with an installed API monitoring application to enable launching and status checks, live background capture, process attach, filter-tree inspection, GUI actions, and opening, validating, decoding, searching, inspecting, exporting, and comparing saved captures and related metadata.

MCP server that fetches API responses and generates ready-to-use model/POJO classes in your configured language, with built-in login/refresh token handling.

Monitor the real-time status of 200+ popular APIs and services. Check if services like GitHub, Stripe, AWS, and Slack are experiencing outages or degraded performance directly from your AI assistant.