> For the complete documentation index, see [llms.txt](https://jranjan.destinjidee.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://jranjan.destinjidee.com/blogs/ai/llms-meet-api-catalogs-a-practical-path-to-intelligent-integration.md).

# LLMs Meet API Catalogs: A Practical Path to Intelligent Integration

The core idea was brewing in my mind, but it was brought to life during a recent APIDAYS workshop. The session was led by a banking AI team, which integrated its API catalog with its LLMs. The idea was to use this approach in the absence of an enterprise [MCP catalog](https://docs.docker.com/ai/mcp-catalog-and-toolkit/catalog/), which was recently released.

Large enterprises often maintain an **API catalog**—a centralised registry of their REST, SOAP, and event-driven interfaces. Traditionally, these catalogs have been used for governance, discovery, and compliance.

But with the rise of **Large Language Models (LLMs)**, a new integration pattern is emerging: rather than relying on a third-party MCP-style catalog, firms are **directly linking LLMs to their existing API catalogs**. This unlocks the ability for developers, analysts, or even business users to query, explore, and auto-generate integration flows in natural language.

### **Why This Matters**

* **Firms already have API catalogs** (Apigee, Kong, MuleSoft Anypoint, or custom)
* **LLMs can parse OpenAPI specs**, understand endpoints, parameters and response schemas
* **Integration scenarios accelerate**: instead of manually browsing, users can ask:\
  \&#xNAN;*“How do I fetch open invoices for a given customer?”* and get back the correct API and sample code

### **Integration Approach**

1. **Extracting APIs from the Catalog**
   * Use Exchange APIs (e.g., MuleSoft Anypoint Exchange REST API) to pull OpenAPI specs
2. **Normalizing API Specs**
   * Convert to a standard JSON schema (endpoint, verb, input, output, auth)
3. **Registering with an LLM**
   * Store in a vector DB or structured index
   * Feed to an LLM so it can answer API-related queries in natural language
4. **Generating Code**
   * LLM returns pseudocode, SDK snippets, or workflow definitions

### Usage

1. **Developer Co-pilot**:\
   Ask: *“How do I retrieve customer order history?”* → LLM returns the right API and a **Java snippet**
2. **Business Analyst Querying**:\
   Ask in plain English → Get the API name, description, and usage instructions
3. **Workflow Generation**:\
   LLM suggests orchestration across multiple APIs (CRM + Payments + Notifications)

### Example

The gist shows a sample registry code for an org's MuleSoft exchange APIs.

{% embed url="<https://gist.github.com/Jitu-Ranjan/e2f0b05f91ac0cf74d414624e380e0df>" %}

### **Comparison: LLM + API Catalog vs MCP Catalog**

| Aspect            | MCP Catalog                                         | LLM + API Catalog                                 |
| ----------------- | --------------------------------------------------- | ------------------------------------------------- |
| **Setup & Infra** | Requires separate MCP servers, new infra            | Reuses existing API catalog infrastructure        |
| **Dependencies**  | Third-party protocol, new runtime components        | In-house development, minimal new stack           |
| **Security**      | Additional surface (tool poisoning, remote servers) | Security model already governed in catalog        |
| **Flexibility**   | Rich primitives (resources, prompts, tools)         | Focused on APIs, pragmatic for enterprises        |
| **Time to Value** | Longer — requires MCP integration and governance    | Faster — immediate head start with current assets |
| **Control**       | Vendor-ecosystem driven                             | Fully enterprise-owned and customizable           |

### **Verdict**

| Criteria           | Best Option                               |
| ------------------ | ----------------------------------------- |
| Cost & Ownership   | LLM + API Catalog                         |
| Security & Control | LLM + API Catalog                         |
| AI Readiness       | Both viable, but MCP richer in primitives |
| Time-to-Value      | LLM + API Catalog                         |

### **Final Thoughts**

If your organisation already maintains an API catalog, integrating it with an LLM offers a **cost-effective, secure, and fast-start approach**. MCP may bring richer primitives in the long term, but for most firms, **leveraging existing assets delivers quicker ROI and avoids unnecessary dependencies**.


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