"Methods to Test API Endpoints" matching MCP servers:

Test coverage intelligence MCP server for TypeScript and JavaScript projects. Analyzes coverage reports to find untested functions, computes cyclomatic complexity, and suggests test cases locally.

Enables migration of test automation projects from WebDriverIO to Playwright using AST-based transformations. Provides tools for analyzing tests, converting syntax, refactoring to Page Object Model, and generating migration reports.

MCP server that analyzes OpenAPI/Swagger REST API contracts and generates BDD Gherkin feature files and TypeScript Jest regression test scripts.

Enables automatic generation of explicit boilerplate methods (getter/setter/equals/hashCode/toString/constructors) for Java entity classes, replacing Lombok dependencies with visible, reviewable code.

Audits a module against its test suite and reports the cases the tests are structurally unable to see, then proves each gap with a real failing test rather than a warning. Covers Python, TypeScript, JavaScript, Java, Rust and Go.

Enables an editor LLM to run only preconfigured lint, test, and read-only git commands, blocking arbitrary bash execution.

Enables querying Odoo's model registry (fields, inheritance, methods) without a database connection by loading the registry in-memory.

Provides coding agents with visibility into test health through tools for flaky test detection, test quality linting, and LLM evaluation harness, enabling them to triage failures, review test quality, and check prompt changes for regressions.

Provides the real exported API surface and type signatures of any npm package, extracted from its published TypeScript declarations, enabling AI coding agents to use functions accurately and avoid inventing nonexistent APIs.

An MCP server that gives AI coding agents the ability to analyze a Python repository's test health: coverage, flaky tests, and ML-based pull-request risk prediction.

An intelligent MCP toolset for software testers that monitors code changes, analyzes test impact, recommends tests, and assesses risk, supporting multiple AI coding frameworks via dual transport modes.

Provides Python refactoring capabilities via the Rope library, enabling AI agents to perform safe, project-wide code transformations such as renaming symbols, moving modules, and extracting methods.

Enables building MCP servers in TypeScript where tool schemas, descriptions, and validation are automatically generated from class methods, their TypeScript types, and JSDoc comments at compile time.

Validates and tests llguidance grammars (Lark format), providing grammar validation, batch test execution, and syntax documentation.

An MCP server for C++ development that currently provides a server_status diagnostic tool. It validates a workspace directory and is designed to expand into build, test, and debugging capabilities.

High-performance code understanding toolkit that enables batch reading of multiple files with dependency context, structural outline extraction with Java annotation awareness, and precise location of classes/methods across large codebases.

Enables LLMs to systematically develop and validate regex patterns by defining test cases with expected matches, testing patterns against them, and iteratively refining until all requirements are satisfied.

Enables AI agents to lint API artifacts (OpenAPI, AsyncAPI, Arazzo) and manage rulesets conversationally via the Model Context Protocol.

Turn any .NET test-automation solution into a queryable map in one SQLite file — features, steps, API clients, page objects, and their dependencies. Zero config, no AI, no network, 100% deterministic.

MCP server that scans Next.js projects and returns a compact summary of routes, API endpoints, schema, and security issues.