"Testing Library" matching MCP servers:

Enables testing and validation of APIs for AI agent compatibility, providing scores, grades, and actionable recommendations.

Integrates Loopy's AI agent loop library with MCP-compatible clients like LM Studio, enabling discovery, analysis, crafting, and execution of bounded agent workflows.

MCP server providing virtual memory for AI context with durable SQLite storage, retrieval, and bounded prompt assembly to manage context windows.

A client library for connecting to and interacting with MCP servers hosted on smcphub.com, allowing users to find, publish, and call tools on MCP servers.

Facilitates browser automation with custom capabilities and agent-based interactions, integrated through the browser-use library.

An MCP server that integrates AI agents with MagicPod, enabling natural language control of MagicPod testing through tools like Cursor and Claude.

Enables access to agent instruction files and prompts for AI development workflows. Provides tools to retrieve and list development rules, security checks, and common prompts from an agents library through MCP protocol.

Enables AI agents to discover, load, and recommend versioned skills from a self-hosted library over MCP, with scoped access and immutable revisions.

A production-ready Python library for building MCP servers with agent orchestration and domain-specific presets for platforms like GitHub, Slack, and Notion.

Self-hosted workspace MCP gateway that registers MCP servers, stores secrets encrypted, mints agent keys, and shares a unified tool library across multiple AI harnesses.

Enables developers to host a minimal MCP endpoint that exposes a read-only Hello World tool and HTML UI resource for testing ChatGPT inline widgets, conversation side panels, and global sidebar apps.

Enables intelligent Kubernetes deployments, automated documentation testing, organizational pattern management, and shared prompt libraries. Provides AI-powered recommendations based on cluster capabilities and automates DevOps workflows through conversational interfaces.

A lightweight server that enables AI agents to interact with the Windows operating system, allowing for file navigation, application control, UI interaction, and QA testing through various tools.

AI-native security testing platform with native MCP support, enabling automated penetration testing, vulnerability discovery, and attack-chain analysis through conversational commands.

A local reimplementation of the AWS Bedrock AgentCore Gateway with a pluggable Lambda backend for developing and testing agent-integrations offline.

A local MCP server that enables Codex and other MCP clients to orchestrate native external coding-agent harnesses through a normalized lifecycle, with guarded execution and deterministic testing.

Enables managing persistent AI workers through MCP tools for versioning, safe testing, deployment, approvals, and run lifecycle with tenant isolation and policy enforcement.

Enables managing a canonical library of agent skills and MCP servers, syncing them across multiple development harnesses, and adding, importing, or configuring them through MCP tools.

Enables host agents to resolve tasks against a local library of reviewed Skills and Experts, then retrieve selected capabilities on demand through MCP tools without loading the full catalog into context.

Starter kit for small businesses: A2A agent card, MCP server card, minimal example MCP server (tools: leistungen, anfrage_anlegen) and validator. Python standard library only, MIT, docs in English and German.