Get to Know the Enhanced MuleSoft Experience
Learning Objectives
After completing this unit, you’ll be able to:
- Explain how MuleSoft’s enhanced experience simplifies the management and governance of APIs, agents, MCP servers, and LLMs in a single experience.
- Identify how to scan for agents, protect an agent, and see metrics for that agent.
- Connect external cloud platforms and AI providers to unify your ecosystem.
Simplify AI and API Management with MuleSoft
Meet Linda. She’s an admin at Cloud Kicks, a company famous for its stylish sneakers. But behind those high-tops is a high-tech operation. Linda’s team has built AI agents to automate customer service and detect fraud. These agents run on platforms like Salesforce Agentforce, and they connect to enterprise systems through Model Context Protocol (MCP) servers.
As Cloud Kicks embraces agents, Linda faces a new challenge. She needs a way to check the health of the Sneaker Concierge agent to make sure that it’s operating as expected. She also needs to monitor performance across different agents, apply governance policies, and control costs.
MuleSoft’s enhanced experience solves this problem. Built into the MuleSoft Platform Linda’s team already uses, the enhanced experience provides one place to discover, monitor, and secure both traditional APIs and AI services.
Get to Know the Enhanced Experience
When Linda accesses MuleSoft’s enhanced experience, she sees a navigation menu for quickly managing her entire AI portfolio. Let’s look at the five main areas where she spends her time.
Home: The Mission Control
The Home page gives Linda an instant snapshot of the Cloud Kicks portfolio. She can see a high-level view of discovered, manually added, and governed services. She also has quick access to her scanners, which automatically find and catalog AI services from her connected providers so she doesn’t have to add them manually.
Portfolio: The Catalog of Services
The Portfolio is where Cloud Kicks’s technical services live. Here, Linda can see her agents, large language models (LLMs), Model Context Protocol (MCP) servers, and APIs in one searchable list.
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Agents: The doers, like the Cloud Kicks sneaker concierge agent that helps people find the right shoe size.
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LLM proxies: A unified access layer for multiple LLM providers. The LLM proxy helps to route requests to the right models, like GPT-5 or Claude Opus, based on the task.
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MCP servers: The AI connectivity layer that lets the agents communicate directly to the Cloud Kicks inventory database.
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APIs: The classic connectivity layer that powers the website and mobile app.
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Gateways: Secure routing infrastructure that manages traffic to your services.
Governance: Security and Efficiency
In the Governance section, Linda makes sure every service meets Cloud Kicks’s standards. She checks to see how well services comply with governance rules and policy coverage and identifies which areas require further oversight. To stay within budget, she tracks how many tokens her MCP servers and LLM proxies consume, then applies out-of-the-box optimization policies to limit and manage that consumption before it drives up costs. This helps her identify and control MCP servers and LLM proxies before they inflate expenses, ensuring the company’s AI spend remains cost-effective.
Observability: Performance Data
When Linda needs to dig into the details, she heads to Observability. This is where the performance data lives. She can look at uptime reports, error rates, and latency. If a customer reports that the sneaker concierge is slow, Linda uses these dashboards to find exactly where the bottleneck is. She can even set up custom alerts so that she gets notified in Slack or via email the moment something isn’t working as expected.
Platform: Scanner Management
The Platform section is where Linda configures and manages her scanners. When Cloud Kicks links its external cloud accounts to the enhanced experience, this is where the configuration lives. Linda uses this space to check active scanners and see which platforms are ready to connect. She can also review scan histories, check background job statuses, and troubleshoot any issues to keep data flowing smoothly. It’s her ultimate toolkit for managing the Cloud Kicks multi-vendor ecosystem.
Track System Health with Scanner Details
To maintain a reliable ecosystem, Linda keeps a close eye on her scanner metrics. On the Providers page, she can select any active scanner to view its detailed overview. This page shows the total count of discovered services and the exact timestamp of the last successful scan. She can also see whether a scan was triggered automatically on a schedule or run on demand. This visibility helps Linda ensure that Cloud Kicks always has an accurate, real-time inventory of its active tools.
Troubleshoot and Monitor Background Jobs
Linda loves that automated scanners do the heavy lifting, but she still verifies the background operations. If a new AI service isn’t appearing in her portfolio right away, she heads to the Providers page to check the scanner’s history for error messages. Linda can review previous scan attempts, verify the timestamp when a problem started, and check that the scanner is assigned to the correct platform connection. This quick troubleshooting process keeps Cloud Kicks’s data flowing safely without interrupting the team's development workflow.
Wrap It Up
With the Enhanced MuleSoft Experience, Linda transforms how Cloud Kicks manages its connected assets. She monitors scanner health and troubleshoots background operations on the Providers page. These capabilities give her team clear visibility into active AI agents and APIs. Now it’s your turn to bring unified management to your own integration landscape.