"Oracle Fusion Cloud API Documentation and Resources" matching MCP servers:

Enables running and grading AI agent evaluations, and applying runtime guardrails that check or block unsafe tool calls through dedicated guardrail tools.

An MCP Server that provides access to Google's Cloud Tool Results API, enabling applications to programmatically interact with test results from Firebase Test Lab and mobile app testing through natural language.

Enables AI coding agents to verify code patches locally with sub-50ms neuro-symbolic analysis, detecting structural issues like dependency cycles and interface drift without consuming output tokens.

Enables read-only querying, evaluation, challenge, and judging of an Oracle project's rules and evidence without modifying the filesystem, plus task tracking for agents.

Enables LLMs to interact directly with generated REST services by discovering and invoking CRUD tools and reading exposed resources for list and get-by-id data.

An MCP server that connects AI assistants to Xray Cloud for Jira test management, enabling natural language interaction with tests, test plans, executions, and CI result imports.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Turns an OpenAPI spec into a ready-to-run test harness with local LLM agents: WireMock stubs, contract tests, robustness probes, and chaos scenarios you can switch on and off in a running WireMock.

Enables automated access to LoadRunner Cloud APIs for retrieving performance test data, managing projects, and collecting test results. Supports integration with AI clients for building performance engineering workflows and dashboards.

Enables access to Xray Cloud test management on Jira Cloud through its REST v2 and GraphQL APIs, with configurable read/write toolsets, single-tool selection, and read-only or per-request credential modes.

Provides a hand-written MCP server integrated with a LangGraph agent to benchmark multiple agent topologies and measure their failure rates.

Enables AI assistants to interact with Zephyr Scale Cloud for test management, including test cases, cycles, plans, folders, priorities, and statuses via the MCP protocol.

Enables natural-language chat-driven API testing, letting users upload API specs, run deterministic pytest checks against live targets, inspect results, create defects, and view failure trends.

Starter scaffold for a workshop to build an MCP API testing server, intended to be extended through incremental steps.

A paid remote MCP server for OpenAI Codex harness, offering structured JSON tools for coding task planning, safe command suggestions, test verdict recording, and run history.

An MCP server that makes backend API requests and packages request+response pairs as evidence to prove an endpoint works.

Enables AI agents to call real API endpoints and verify responses against OpenAPI specs, supporting contract testing, auth presets, spec diffing, and health checks.

Enables creating mock API endpoints and responses, including mock collections and status checks.

Enables AI agents to drive API testing from YAML definitions, executing and chaining requests without hand-written curl, while keeping credentials out of the conversation and responses token-cheap, plus a VANDER-based QA review of endpoints.

API Tester AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

Enables regex testing, replacement, splitting, validation, explanation, escaping, common patterns, and benchmarking through an MCP server.

Enables testing and interacting with REST API endpoints through MCP clients such as Claude and Cline, supporting multiple HTTP methods, authentication, custom headers, and configurable response limits.

Enables testing and interacting with any REST API endpoints directly from MCP clients such as Claude and Cline, supporting GET, POST, PUT, DELETE, and PATCH requests with detailed status, header, and body responses. It handles Basic, Bearer, and API Key authentication, custom headers, configurable SSL verification, and response size limits.

Enables testing and interacting with any REST API endpoints directly from development environments through MCP clients, including support for multiple HTTP methods, authentication methods, custom headers, SSL verification control, and response size limiting.

Enables testing and interaction with REST API endpoints from MCP clients such as Claude and Cline, supporting multiple HTTP methods, authentication, custom headers, SSL verification control, and response-size limiting.

Analyzes API requirements and source code, evaluates existing Postman test coverage, and generates or updates test automation with an optional draft pull request on GitHub.

Enables users to test and interact with any REST API endpoints directly from their development environment through MCP clients such as Claude and Cline. Supports GET, POST, PUT, DELETE, and PATCH requests with configurable authentication, custom headers, SSL verification, and response size limits.

Enables testing and interacting with REST API endpoints from Claude, Cline, and other MCP clients, supporting GET, POST, PUT, DELETE, and PATCH requests with authentication, custom headers, SSL control, and response size limits.

基于fastmcp-ts开发的接口测试mcp工具，ai可以通过调用该工具对接口进行测试。

Enables testing and interacting with REST API endpoints through MCP clients such as Claude and Cline, with support for common HTTP methods, authentication, custom headers, SSL verification settings, and response size limits.