AgentGuard is an MCP server from RLabs for AI code generation quality assurance. It is described as giving Claude, GPT, or Cursor a five-step process to generate production-ready code, and it uses archetypes, or architecture templates, to help keep project structure consistent and quality-focused.
Its documented workflow exposes five capabilities: skeleton for project structure and scaffolding, contracts for type-safe interfaces and schemas, logic for implementation with validation, validate for structural and security checks, and digest for a quality report with trace summary. The page also describes a real example around generating a task management REST API and contrasts outcomes such as inconsistent file structure, partial or missing typing, low test coverage, disorganized imports, and long manual refactoring with the validated, standardized results associated with AgentGuard. It states that the tool provides code verification, protection against hallucinations, granular verification mechanisms, and validation decisions that are explainable and traceable.
AgentGuard is delivered as an MCP server and can be installed with pip as rlabs-agentguard. The page shows a Claude desktop configuration snippet using agentguard-mcp and an archetype argument, and it notes that no API keys or extra configuration are required. It also references a marketplace with 61+ archetypes, 8 built-in archetypes, and 19 MCP tools. Pricing cues on the page include a Get Started Free prompt and monthly installs listed as 878+, while licensing is shown as MIT License. The page title and surrounding copy identify the product as AI quality assurance by RLabs.
AgentGuard is a LLM eval & observability project. It focuses on ensuring the quality and consistency of AI-generated code through automated validation and structural checks. It is built as an open-source project for AI developers and QA engineers. AgentGuard is open source under the MIT license. AgentGuard is available on the command line and API.
Behind AgentGuard is RLabs, based in Chile, and it first shipped in 2026. The project is developed in the open on GitHub with 11 stars and 40 commits in the last 90 days. Key capabilities include MCP server, code validation, and archetype templates. It exposes integrations via an MCP server.
Summary written by a language model from the project’s public pages.
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