Past battle · 2024-03-15 UTC
AI Agent Development Frameworks Showdown — March 15, 2024
From the AI Agent Development Frameworks category. 10 marks placed across 3 fighters. Agent Network Protocol took the crown.
Final standings
The line-up
The fighters
Profiles of every tool that competed in this battle, ranked by their final score.
Agent Network Protocol
An open-source protocol enabling secure, decentralized communication among AI agents.
The Agent Network Protocol (ANP) is an open-source protocol enabling secure, decentralized communication among AI agents. It is a layered protocol stack that reuses the open Internet foundation and is designed for open, cross-domain agent networks. The protocol has three layers: the bottom layer reuses HTTP, CA, DNS, CDN, Search, TLS, and the existing web operating model; the middle layer provides decentralized identity (DID:WBA), handles, authentication, key material, secure messaging, and cross-domain communication foundations; the top layer includes Agent Description, Agent Discovery, and domain-specific protocols for payment, authorization, authentication, commerce, and other agent workflows. ANP allows agents to publish capabilities, find interoperable services, and enable direct chat, groups, encryption, attachments, and federation semantics. The protocol is organized in modular sections such as identity and communication, description and discovery, messaging profiles, and domain protocols. It features DID:WBA identity, WNS handles, authentication, key distribution, and secure messaging. This allows for a verifiable agent identity and readable handles, and enables cross-domain trust roots. ANP can be adopted by implementations as a foundation for their application-specific needs and allows for the addition of messaging, discovery, and payment capabilities as needed. The goal of ANP is to create a decentralized infrastructure for AI agents. The protocol allows for new specifications and updates, with recent additions including new WBA Name Space, end-to-end instant messaging, and an agent payment protocol. It follows a three-layer architecture with the open Internet infrastructure at the base, identity and communication infrastructure above it, and application protocols at the top. ANP's modular design allows for adoption and extension by multiple parties and enables open, cross-domain agent networks.
Criteria breakdown
- DID:WBA identity
- WNS handles
- Authentication
- Key distribution
- Secure messaging
- Direct messaging
MCP‑Use
Open‑source platform to connect LLMs with MCP servers and build custom AI agents with tool access.
mcp-use is an open-source platform that facilitates the connection of Large Language Models (LLMs) with MCP servers and enables the development of custom AI agents that can interact with these LLMs. The platform provides a full-stack MCP framework (mcp-use SDK) to build ChatGPT Apps, Claude Connectors, and MCP Servers. With mcp-use, developers can leverage a single codebase to deploy their applications on various surfaces where users and agents already work, including ChatGPT, Claude, and Gemini. The platform offers a range of tools and features, such as the ability to scaffold MCP applications in one command, automatic deployment to Manufact Cloud, and built-in analytics and observability. Developers can use the mcp-use SDK to build and deploy MCP servers and applications without requiring additional tools. The platform also provides a Visual Inspector and Sandbox testing capabilities, allowing developers to test their applications without the need for a live LLM. mcp-use aims to simplify the development and deployment of MCP-based applications, making it an attractive option for developers looking to build and deploy custom AI agents and applications.
Criteria breakdown
- MCP server management
- LLM connection and integration
- Custom AI agent development
- Automated deployment and scalability
- Visual Inspector and Sandbox testing
- Built-in analytics and observability
Cerebrum: AIOS SDK
An SDK for developing and deploying LLM-based AI agents within the AIOS framework.
Cerebrum is an SDK for developing and deploying LLM-based AI agents within the AIOS (AI Agent Operating System) framework. AIOS addresses challenges such as scheduling, context switching, memory management, and tool management for LLM-based agents. The Cerebrum SDK allows developers to build and run agent applications by interacting with the AIOS kernel. It supports both Web UI and Terminal UI. The SDK includes features for listing available LLMs, agents, and tools, as well as downloading, uploading, and running agents and tools. Cerebrum is designed for agent users and developers, enabling them to create and deploy AI agent applications.
Criteria breakdown
- Agent development and deployment
- LLM-based AI agent management
- Support for Web UI and Terminal UI
- Agent and tool management
- Listing available LLMs, agents, and tools
- Downloading and uploading agents and tools