"Assistance with reviewing and merging code changes in a merge request" matching MCP servers:

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.

A TypeScript-based MCP server that enables AI assistants to execute HTTP requests with full control over methods, headers, and body content. It facilitates seamless interaction with web APIs and endpoints through a versatile tool that handles automatic JSON formatting and response truncation.

Enables automatic HTTP requests (GET, POST, PUT, DELETE, etc.) with JSON validation and proxy support. Supports custom headers, request bodies, and environment variable configuration for seamless API integration.

Implements a secure MCP server with API Key and JWT authentication, providing tools like echo, login, secure_action, and admin_action. Includes MCP Inspector integration for testing and debugging.

Middleware that converts a serverless handler with OpenAPI spec into an MCP endpoint following stateless MCP principles.

Enables automated semantic analysis of Git pull request diffs to detect breaking REST/GraphQL API schema changes, integrating with MCP-compatible clients for AI-driven code review.

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.

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.

A comprehensive HTTP client MCP server for security testing, API testing, and web automation that provides full-featured HTTP tools with detailed logging capabilities.

Enables LLMs to interact directly with generated REST APIs by exposing CRUD actions as MCP tools and read-only data as MCP resources.

This server facilitates scalable discovery and execution of OpenAPI endpoints using semantic search and high-performance processing, overcoming limitations of large spec handling for streamlined API interactions.

Enables LLMs to discover and use generated REST API services as Model Context Protocol tools and resources, supporting CRUD actions and read-only data access without custom glue code.

A Bun-based MCP server providing a persistent HTTP request toolset for testing and inspecting JSON APIs. It supports session-aware operations, including cookie persistence, automatic bearer token reuse, and configurable base URLs.

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

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 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.

An open standard server implementation that enables AI assistants to directly access APIs and services through Model Context Protocol, built using Cloudflare Workers for scalability.

Enables precise measurement of live HTTP and WebSocket services while maintaining an append-only, evidence-based ledger of claims that agents can query with explicit timestamps, staleness indicators, and instructions for re-verification.

Enables reading and searching API documentation from YApi instances, allowing AI models to access interface definitions, project API lists, and search through API endpoints using YApi URLs or project IDs.

Enables LLMs to make HTTP requests using structured cURL commands with support for multiple authentication methods, custom headers, and comprehensive request/response control.