agy-mcp

★ 25

agentao

★ 310

agy-mcp vs agentao

Q: Which is better, agy-mcp or agentao?

By GitHub stars, agentao has more community adoption, but the best choice depends on your specific use case.

agy-mcp: Agy-mcp wraps Google's Antigravity CLI into 11 typed MCP tools, making it callable by any MCP client like Claude Code or OpenAI Codex. It also provides optional Skill bundles to teach supporting platforms when and how to invoke these tools, alongside robust safety policies for secure execution.; agentao: Agentao is a governed agent runtime for Python, emphasizing local-first, private-first, and embeddable design. It provides comprehensive control over permissions, protocols, memory, plugins, and multi-session capabilities for AI agents.

TL;DR

agy-mcpMulti-Agent · ★ 25

Getting a second opinion on a bug hypothesis (using `mode="review"`).

Read agy-mcp full review →

agentaoMulti-Agent · ★ 310

Embedding AI agent capabilities into existing Python applications or frameworks.

Read agentao full review →

Side-by-Side Comparison

Field

agy-mcp

agentao

Features

agy-mcp

01Provides Skill bundles for agent platforms to learn invocation context and safety rules.

02Implements a robust safety policy for redaction, write control, and sensitive file access.

03Supports synchronous one-off calls and background long-running tasks with status and result retrieval.

04Offers cross-platform process group termination for running jobs.

agentao

01Robust Governance: Features include tool confirmation, four permission modes (read-only, workspace-write, full-access, plan), and macOS sandbox execution.

02Persistent Memory: SQLite-backed memory with user/project scopes, automatic recall, and Jieba Chinese segmentation for enhanced context.

03Extensible Skills: Automatically discovered from local directories, installable from GitHub, and supports a `/crystallize` workflow for skill creation.

04Flexible Protocols: Implements MCP for tools (stdio, HTTP, SSE) and ACP (JSON-RPC) for full agents, with a comprehensive plugin lifecycle.

05Seamless Embedding: Offers a direct `Agentao(...)` constructor, event streams, active permissions management, and capability injection for integration.

Use Cases

agy-mcp

↳Getting a second opinion on a bug hypothesis (using `mode="review"`).

↳Applying a reviewed diff to the codebase (`mode="execute", allow_write=True`).

↳Performing large-scale refactoring tasks over several hours (`agy_start(..., mode="long")`).

↳Environment and authentication detection without leaking secrets (`agy_doctor`).

agentao

↳Embedding AI agent capabilities into existing Python applications or frameworks.

↳Developing and driving AI agents directly from the terminal using a comprehensive command-line interface.

↳Building custom AI agents with specific governance rules, persistent memory management, and flexible tool integration.

↳Creating and managing a library of reusable AI skills that can be installed and shared across different projects.

Best For

agy-mcp

—

agentao

Hidden Gem

FAQ

What is the difference between agy-mcp and agentao?

Both agy-mcp and agentao are in the Multi-Agent category. agy-mcp has 25 stars, while agentao has 310 stars.

Which is better, agy-mcp or agentao?

The best choice depends on your use case. Choose agy-mcp if Getting a second opinion on a bug hypothesis (using `mode="review"`)., and agentao if Embedding AI agent capabilities into existing Python applications or frameworks..

Is agy-mcp free or open source?

Yes, agy-mcp is open source on GitHub (MIT).

Is agentao free or open source?

Yes, agentao is open source on GitHub (MIT).

Cloud Infrastructure

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Alternatives to agy-mcp →Alternatives to agentao →agy-mcp details →agentao details →

TL;DR

Side-by-Side Comparison

Features

Use Cases

Best For

FAQ

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