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Building Agent Networks for Agent Fabric

Agent Fabric manages and coordinates the execution of agents across your enterprise, regardless of where they’re deployed. Agent Fabric solves the problem of integrating and automating complex processes that involve multiple agents and tools.

Complex tasks often require a series of steps, with each step handled by a different agent or tool. Managing this process manually is difficult and error-prone. Agent networks (networks of agents in a domain) act as central hubs for defining, validating, and executing these multi-step processes.

Define your agent network in a simple, human-readable YAML file in Anypoint Code Builder. This approach abstracts away the underlying technical complexities so you focus on the business constraints and context of your process without needing to understand the inner workings of the orchestration engine.

Don’t worry, we give you a head start by providing you with a YAML template in your agent network project. MuleSoft Dev Agent can help you configure it for your business environment, publish agent network assets to Anypoint Exchange, and deploy your agent network instance.

For more information about Agent Fabric, see Agent Fabric Overview.

Agent Network Components

Agent networks support brokers, A2A-compliant agents, and Model Context Protocol (MCP) servers.

Agent network

A collection of agents, brokers, LLMs, and MCP servers that are connected to each other.

Broker

An intelligent routing service that coordinates task delegation across specialized A2A-compliant agents in your enterprise. A broker is defined by the agents and MCP servers it can leverage to accomplish tasks. Brokers originate from MuleSoft and are referenced in the agent network YAML.

After you publish your agent network, brokers appear as specialized agents in Anypoint Exchange and can be reused by other brokers.

Agent

An autonomous software component that uses goals, context, and available tools, often via a large language model (LLM), to decide and execute actions on behalf of a user or system.

Agents can be defined either locally in the agent network or externally in a different agent network or elsewhere in your company. Your agent network can use both locally defined and externally defined agents to complete tasks.

Agent assets must be A2A-compliant.

MCP server

A service that implements the Model Context Protocol (MCP) to expose tools and data to AI clients, enabling LLMs to invoke external capabilities through a standard interface.

MCP servers can be defined either locally in the agent network or externally in a different agent network or elsewhere in your company. Your agent network can use both locally defined and externally defined MCP servers to complete tasks.

Anypoint Code Builder canvas showing brokers, agents, and MCP servers
1 The Brokers component groups brokers defined locally in your agent network YAML. It can include assets defined locally within the project and assets previously published to Anypoint Exchange, either by your organization or third parties.

Brokers can reference other brokers defined within the project.

Agent network projects don’t require brokers. They can contain only agents and MCP servers defined within the agent network project.

2 The Agents component groups agents defined locally in your agent network YAML.

These agents will be published to Exchange.

3 The MCP Servers component groups MCP servers defined locally in your agent network YAML.

These servers will be published to Exchange.

4 An asset that has been defined within this agent network project.

The asset might also be published to Exchange.

Considerations

Agent networks have these considerations.

  • An agent network project supports only one domain (one YAML file per project). For multiple domains, create a separate project for each.

  • These authentication types are supported.

    • Basic

    • Client Credentials

    • Anypoint Client Credentials

  • A2A specification 0.3.0 is supported. Brokers use the A2A protocol to accept requests to reach other agents.

  • These A2A features aren’t available.

    • Task History

    • Push Notifications Config

    • Streaming

  • Text-based prompts and responses are supported. Image and binary message/artifact types aren’t supported.

  • All LLM models in your agent network project must support structured responses in JSON format. For example, a gpt4.1 model is supported; a gpt4 model isn’t.

  • These LLMs are supported.

    • Azure OpenAI

    • OpenAI Direct API

  • When you add governance policies to your agent network project YAML file, those policies persist between deployments. However, if you add governance policies at run-time, those policies don’t persist. The next time you deploy your agent network, the governance policies used are the ones in the agent-network.yaml file.

  • These deployment targets are supported.

    • CloudHub 2.0

    • Runtime Fabric (limited availability)