"A server offering MCP prompts as primitives for task execution" matching MCP servers:

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Verifies AI agent completion claims by checking that claimed output files exist and are fresh, acting as a lightweight physical telemetry gate.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

MCP server that verifies restaurant booking outcomes by reconciling API claims against independent re-reads, with a recovery dial for stakes-based retry policies.

Enables Claude to independently check an AI agent's work in a local git repository by recording a baseline, running only the checks relevant to the changed files, and cross-checking what the agent claimed. Returns a compact, evidence-labelled report with a verdict and a ready-to-paste next prompt, so unverified success claims can't slip through.

Enables LLMs to inspect and test other MCP servers by listing and calling their tools, reading resources, and getting prompts. Supports stdio, SSE, and HTTP transports for both local and remote MCP server inspection.

Enables researchers to present 12 mock file, memory, schedule, and database tools over stdio and collect LLM pre-execution judgments (EXECUTE/CONFIRM/REFUSE) without executing real operations.

Provides prompt templates and tools for mobile QA automation, including converting manual tests to Appium scripts, analyzing failures, and standardizing bug reports.

MCP-first A/B testing server that enables agents to manage experiments (create, update traffic splits, read results, apply winning variants) from tools like Claude Code, with self-hosted Cloudflare backend.

Zero-sidecar MCP server embedded directly in the Godot 4 editor as a GDScript EditorPlugin — no Node or Python sidecar. Reflection-driven tools over any engine class, validate-before-write GDScript, scene/script/resource authoring, and a runtime play-test loop (play, screenshot, input, assert).

A multi-task MCP server for AI code optimization and testing that integrates with VSCode/Cursor, CLI tools, and autonomous agents. It provides tools for running tests, generating code improvements, and managing objectives across different environments.

Enables users to query, create, update, and manage Digital.ai Agility assets through MCP tools, with secure Windows Credential Manager authentication and configurable write operations.

Generates a pytest suite from acceptance criteria that are withheld from the coding agent, so the tests can disagree with the code. Four tools, and qikly_run never returns the criteria, which a test in the suite enforces.

Enables Claude to build and preview mobile apps on multiple iOS and Android devices simultaneously, with live streaming and touch control, all via MCP.

MCP server that brings Trustabl static reliability scanning into Cursor, letting agents inventory agents/tools, flag risky patterns, score production readiness, and write SARIF reports.

A reference MCP server that enforces identity-aware tool access using role-based permissions (Reader, Analyst, Auditor) and supports multiple identity routes like Entra RBAC, Copilot Studio, and Okta XAA. It provides read-only access to test evidence with explicit denial paths for unauthorized tools.

Zero-dependency MCP server and CLI that proxies, inspects, and analyzes JSON-RPC message streams between MCP clients and servers.

Enables checking npm packages for known security vulnerabilities using the OSV API before installation. Supports both single package checks and bulk vulnerability scanning for multiple packages at once.

A simple server implementing the Model Context Protocol (MCP) that echoes messages back, designed for testing MCP clients.

Bridges AI models with WinDbg to analyze Windows crash dumps and perform remote debugging through natural language queries, enabling execution of debugger commands and automated crash analysis.