--- schema_version: "1" id: abff954b8c02aa446f6e064381723e93c0d5a28da4157c38deab7d7abc2c6bb5 title: Agent Fabric Use Cases collection: mulesoft version: current locale: en-us portal_url: https://docs.salesforce.com/mulesoft/current/en-us/general/agent-fabric-use-cases.md canonical_url: https://docs.mulesoft.com/general/agent-fabric-use-cases source_site: docs.mulesoft.com content_type: documentation content_hash: d43fd115aede2d13638e51cfdb719725bf6e04a3f610135bdde914e0c6891c59 description: MuleSoft Documentation Site latest: true --- --- product: Getting Started --- # Agent Fabric Use Cases > For the full documentation index, see: https://docs.mulesoft.com/llms.txt ## Why Agent Fabric Enterprises don’t struggle to build one agent. They struggle to run many — across Agentforce, Bedrock, custom Mule implementations, and vendor platforms — without losing control of cost, security, and consistency. The usual response is to solve each problem per platform: custom API adapters here, a spend dashboard there, guardrails reimplemented for every team. That work duplicates effort, drifts out of sync, and leaves gaps no one owns. Agent Fabric replaces that per-platform sprawl with one governed layer that every agent, API, model, and provider routes through. Expose APIs as agent tools without touching code, enforce the same policies and budgets everywhere, attribute every token to the team that spent it, and contain a rogue agent before it causes damage — all from a single point of control. The result is faster time-to-agent, predictable spend, and governance that holds as you scale from proof of concept to production. Each use case below maps a specific business problem to the Agent Fabric capabilities that solve it, so you can start where the pain is and build incrementally. Use the quick-reference table to match your immediate goal to the right capability. ## Find Your Use Case
If you want to…​Use caseGo to

Make existing APIs agent-ready without modifying code

Select which API operations to expose as MCP tools, apply read-only filtering, and control agent access to your APIs.

Making Your APIs Agent-Ready

Control token usage and optimize model selection

Monitor token usage across agents and applications, then route queries to cost-effective models based on complexity.

Controlling LLM Costs in Agent Fabric

## Discover and Govern Agents Across Your Organization Use a centralized registry and automated scanners to discover, catalog, and manage agents across your organization. Know what exists and where before you apply governance. For example, a business process outsourcer managing agents across multiple client platforms, or an enterprise security team asked to audit every agent in production, can use Registry and Scanners to get a complete, current picture without manually tracking deployments. For more information, see [Adding Services to Your Portfolio](https://docs.mulesoft.com/general/exp-services-add-to-portfolio). ## Make APIs Agent-Ready with MCP Bridge Transform your existing API instances into agent-ready tools without modifying code. Select which operations to expose, apply read-only filtering where needed, and control agent access to your APIs. For example, an organization with hundreds of existing Mule APIs can make them callable by agents in minutes through configuration alone, without touching the underlying implementations. For more information, see [Making Your APIs Agent-Ready](https://docs.mulesoft.com/general/af-use-case-mcp-bridge). ## Enforce Consistent Policies Across Agent Platforms Consistently enforce business rules, PII policies, and guardrails across all agents regardless of platform. Apply policies one time through a gateway rather than reimplementing them for each platform. For example, a regulated industry deploying agents across Agentforce, Bedrock, and custom Mule implementations can enforce the same data privacy and rate limiting rules everywhere through a single Omni Gateway policy. For more information, see [Applying and Managing Policies](https://docs.mulesoft.com/general/exp-policies-apply-manage). ## Monitor Costs and Optimize Model Selection Monitor token usage across applications and agents, then optimize costs by routing simple queries to cost-effective models while reserving powerful models for complex tasks. For example, a team running hundreds of daily agent interactions can route routine lookups to a smaller, cheaper model and reserve a frontier model only for tasks that require complex reasoning. For more information, see [Controlling LLM Costs in Agent Fabric](https://docs.mulesoft.com/general/af-use-case-cost-management). ## Coordinate Multi-Agent Processes with Brokers Use agent brokers and agent networks to coordinate task delegation across A2A-compliant agents with guided determinism. Define broker routing logic in Agent Script to handle complex business processes, error scenarios, and unhappy paths that require multiple specialized agents working in sequence. For example, an order management process that involves a research agent, a pricing agent, and an approval agent can be wired together in a single agent network with a broker that routes each step to the right specialist. ## Get Started New to Agent Fabric? Start with the [Agent Fabric Overview](https://docs.mulesoft.com/general/agent-fabric-overview) and [Agent Fabric learning map](https://docs.mulesoft.com/general/learning-map-agent-fabric) to understand the fundamentals. After you understand the basics, choose a use case to implement. ## See Also - [Agent Fabric Overview](https://docs.mulesoft.com/general/agent-fabric-overview) - [Learn About Agent Fabric](https://docs.mulesoft.com/general/learning-map-agent-fabric) - [Controlling LLM Costs in Agent Fabric](https://docs.mulesoft.com/general/af-use-case-cost-management) - [Making Your APIs Agent-Ready](https://docs.mulesoft.com/general/af-use-case-mcp-bridge)