Connect Oracle Fusion Cloud EPM to ChatGPT: Audit Users and Roles

If you need to connect Oracle Fusion Cloud EPM to ChatGPT to audit users, review roles, or automate access governance, you need a Model Context Protocol (MCP) server. This server acts as the translation layer between ChatGPT's JSON-RPC tool calls and Oracle EPM's REST APIs. You can either build and maintain this infrastructure yourself, or use a managed integration platform like Truto to dynamically generate a secure, authenticated MCP server URL. If your team uses Claude, check out our guide on connecting Oracle Fusion Cloud EPM to Claude or explore our broader architectural overview on connecting Oracle Fusion Cloud EPM to AI Agents.

Giving a Large Language Model (LLM) read and write access to a sprawling financial ecosystem like Oracle Fusion Cloud EPM is a high-stakes engineering challenge. You have to handle fragmented identity models, map complex JSON schemas to MCP tool definitions, and deal with Oracle's extremely specific API behaviors. Every time Oracle updates an endpoint or shifts access control paradigms, you have to update your server code, redeploy, and test the integration.

This guide breaks down exactly how to use Truto to generate a secure, managed MCP server for Oracle Fusion Cloud EPM, connect it natively to ChatGPT, and execute complex audit workflows using natural language.

The Engineering Reality of the Oracle Fusion Cloud EPM API

A custom MCP server is a self-hosted integration layer. While Anthropic's open MCP standard provides a predictable way for models to discover tools, the reality of implementing it against Oracle's APIs is painful. You aren't just integrating a generic REST service - you are integrating an enterprise resource engine with legacy architectural roots.

If you decide to build a custom MCP server for Oracle EPM, you own the entire API lifecycle. Here are the specific integration challenges that break standard CRUD assumptions when working with Oracle Fusion Cloud EPM:

The Identity Domain vs Native Roles Chasm Oracle EPM access control is split. A user's base identity exists in Oracle Cloud Infrastructure (OCI) Identity and Access Management (IAM), but their actual application access is governed by local EPM predefined roles and group memberships. If an LLM wants to perform a complete User Access Review (UAR), it cannot call a single /users endpoint and get everything. It must retrieve the user roster, query the local groups, and extract the application-level predefined roles. If your MCP server doesn't provide discrete tools for each of these identity layers, the LLM will fail to build a complete access matrix.

Heavy Pagination and Asynchronous Jobs Fetching identity data across thousands of enterprise users is not a synchronous operation in Oracle EPM. The API relies heavily on strict pagination offsets. For bulk operations, Oracle often forces you into asynchronous job execution, returning a job ID that must be polled. If your AI agent requests a massive role audit, your MCP server must explicitly instruct the LLM to pass pagination cursors back unchanged to fetch the next set of records, or handle the async polling state in the proxy layer.

Strict Rate Limits and Normalization Oracle EPM enforces aggressive rate limits to protect instances from reporting degradation. A common mistake when building custom MCP servers is attempting to have the server automatically absorb or retry these rejections. Truto takes a strict, predictable approach: Truto does not retry, throttle, or apply backoff on rate limit errors. When the upstream Oracle API returns an HTTP 429 Too Many Requests, Truto passes that error directly to the caller. Truto normalizes the upstream rate limit information into standardized headers (ratelimit-limit, ratelimit-remaining, ratelimit-reset) per the IETF specification. The caller - in this case, the LLM framework or custom agent - is entirely responsible for evaluating these headers and executing the retry or backoff logic.

The Managed MCP Approach

Instead of forcing your engineering team to build, host, and maintain a custom Node.js or Python server to translate JSON-RPC to Oracle EPM REST calls, Truto handles the translation layer dynamically.

Truto derives MCP tools directly from the Oracle Fusion Cloud EPM integration's resource definitions and human-readable documentation records. A tool only appears in the MCP server if it has a corresponding documentation entry. This documentation acts as a quality gate, ensuring the LLM only sees well-described endpoints with strictly defined JSON schemas.

Each MCP server is scoped to a single integrated account (a specific tenant's connected Oracle EPM instance). The server URL contains a cryptographic token that encodes the account, the allowed tools, and the expiration time. The URL alone is enough to authenticate and serve tools, requiring zero boilerplate code.

Step 1: Creating the Oracle EPM MCP Server

There are two ways to generate an MCP server for your connected Oracle Fusion Cloud EPM instance. You can do this visually through the UI or programmatically via the Truto REST API.

Method A: Via the Truto UI

If you are an IT admin or support engineer setting up access for an internal AI tool, the UI is the fastest path.

1. Log into your Truto dashboard and navigate to the integrated account page for the specific Oracle EPM connection.
2. Click the MCP Servers tab.
3. Click Create MCP Server.
4. Configure the server parameters. You can set a human-readable name, restrict allowed methods (e.g., check "Read-only" to prevent the LLM from altering users), and set an optional expiration date for temporary audit access.
5. Click Create and copy the generated MCP server URL (e.g., https://api.truto.one/mcp/a1b2c3d4...). Keep this secure.

Method B: Via the Truto REST API

For DevOps teams automating the deployment of AI infrastructure, you can generate MCP servers programmatically.

The API validates that the integration has tools available, generates a secure token, stores the hash in the edge distributed caching layer, and returns a ready-to-use URL.

// POST /integrated-account/:id/mcp
 
const response = await fetch('https://api.truto.one/integrated-account/YOUR_ACCOUNT_ID/mcp', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer YOUR_TRUTO_API_TOKEN',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    name: "Oracle EPM SOX Audit Server",
    config: {
      methods: ["read"], // Restrict the LLM to GET and LIST operations
      tags: ["identity", "audit"] // Only expose endpoints related to identity
    },
    expires_at: "2026-12-31T23:59:59Z" // Automatically revoke the URL for compliance
  })
});
 
const mcpServerData = await response.json();
console.log(mcpServerData.url); 
// Outputs: https://api.truto.one/mcp/a1b2c3d4...

This API-first approach allows you to spin up ephemeral MCP servers dynamically whenever a compliance officer requests a new ChatGPT audit session.

Step 2: Connecting the MCP Server to ChatGPT

Once you have the Truto MCP URL, you need to register it with your LLM framework so the model can discover the available Oracle EPM tools.

Method A: Via the ChatGPT UI

If you are using the ChatGPT desktop application or web interface on a supported enterprise plan, you can connect the server natively without code.

1. In ChatGPT, navigate to Settings -> Apps -> Advanced settings.
2. Enable Developer mode (MCP support is gated behind this toggle).
3. Under MCP servers or Custom connectors, click to add a new server.
4. Name: Enter a descriptive label (e.g., "Oracle EPM Identity Audit").
5. Server URL: Paste the Truto MCP URL you generated in Step 1.
6. Save the configuration. ChatGPT will immediately perform an MCP handshake, retrieve the tool schemas, and make them available in your context window.

(Note: If you are configuring this for Claude instead, the process is similar: Open Claude Desktop, navigate to Settings -> Integrations -> Add MCP Server, paste the URL, and click Add.)

Method B: Via Manual Config File (SSE)

If you are building a custom LangGraph agent, using an alternative headless LLM, or deploying via a central infrastructure repo, you can configure the MCP connection using a Server-Sent Events (SSE) JSON file.

Because Truto exposes the MCP server over standard HTTPS via JSON-RPC, you can wrap it using the official @modelcontextprotocol/server-sse package.

{
  "mcpServers": {
    "oracle_epm_audit": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-sse",
        "--url",
        "https://api.truto.one/mcp/YOUR_SECURE_TOKEN"
      ]
    }
  }
}

When your agent boots up, it will execute this command, establish a connection to Truto's edge routing layer, and dynamically load the schemas for Oracle EPM groups, roles, and users.

Hero Tools for Oracle EPM Auditing

Truto automatically maps Oracle Fusion Cloud EPM REST endpoints into snake_case MCP tools. Here are five high-leverage tools your AI agent can use to orchestrate identity audits.

1. List All EPM Users

Tool name: list_all_oracle_fusion_cloud_epm_users

This tool retrieves the master roster of users in the Oracle Fusion Cloud EPM environment. The proxy API formats the response to include core identity fields like userlogin, firstname, lastname, and email. It automatically handles the limit offsets required by Oracle's backend.

"Fetch the complete list of users in our Oracle EPM instance. Return their email addresses and login IDs in a markdown table, and note any user accounts where the firstname or lastname fields are missing."

2. List All EPM Roles

Tool name: list_all_oracle_fusion_cloud_epm_roles

This tool retrieves the available application and predefined roles defined within the EPM instance. This is critical for understanding the baseline permissions available before mapping them back to individual users. The schema accepts optional query parameters to filter by role type.

"Retrieve all predefined roles available in Oracle EPM. Filter the list to show only application-level roles, and list their internal IDs next to their display names."

3. List All EPM Groups

Tool name: list_all_oracle_fusion_cloud_epm_groups

This tool queries the directory for EPM-specific group structures. The response schema returns the groupname, description, type, and identity fields. Because EPM relies heavily on group-based inheritance for cube and dimension security, mapping these groups is a prerequisite for a complete access review.

"Get the list of all groups in the EPM environment. Identify any groups that contain the word 'Admin' or 'Service Administrator' in their groupname or description."

4. Get Single EPM User By ID

Tool name: get_single_oracle_fusion_cloud_epm_user_by_id

When cross-referencing audit logs, the LLM needs a way to drill down into a specific identity. This tool accepts a unique user identifier in the query schema and returns the deeply nested JSON object for that specific user, including their assigned EPM groups and directly provisioned roles.

"Look up the Oracle EPM user with the login ID 'jdoe@enterprise.com'. Tell me exactly which groups this user belongs to and list their assigned predefined roles."

5. Update an EPM User By ID

Tool name: update_an_oracle_fusion_cloud_epm_user_by_id

If the MCP server is configured to allow write methods, the AI agent can orchestrate automated remediation. This tool accepts the user ID and a JSON schema representing the modification payload (e.g., disabling the account or adjusting metadata).

"The user 'asmith@enterprise.com' has been flagged for termination in the HR system. Update this user's Oracle EPM profile to immediately suspend their login capability and revoke their group memberships."

To view the complete inventory of available proxy endpoints and detailed JSON schemas, visit the Oracle Fusion Cloud EPM integration page.

Workflows in Action

Connecting ChatGPT to Oracle EPM transforms static REST APIs into an interactive compliance engine. Here are two real-world examples of how IT admins use these tools in practice.

Scenario 1: Quarterly SOX Access Review (UAR)

During a financial audit, a compliance officer needs a matrix of all users possessing "Service Administrator" privileges across EPM applications.

"Execute a SOX compliance audit for Oracle EPM. First, list all available roles to find the exact ID for 'Service Administrator'. Then, retrieve the list of all users. For every user, check if they possess the Service Administrator role either directly or via group inheritance. Generate a final markdown table listing the User Login, First Name, Last Name, and the exact path of their administrative access."

Step-by-step execution:

1. The agent calls list_all_oracle_fusion_cloud_epm_roles to extract the target role schema.
2. The agent calls list_all_oracle_fusion_cloud_epm_users to retrieve the directory.
3. Recognizing the pagination parameters in the schema (limit, next_cursor), the LLM loops through the pages until all users are ingested.
4. The agent cross-references the data and outputs a clean markdown table, completely bypassing the need for manual CSV exports from the Oracle EPM Shared Services console.

Scenario 2: Offboarding and Anomaly Detection

Security teams need to ensure terminated employees do not retain residual access in legacy financial systems.

"Audit the user profile for 'jdoe@enterprise.com'. Check if their account is still active. If it is active, output a list of all groups they currently belong to. Then, draft an email to the IT Helpdesk summarizing their residual EPM access that needs to be manually revoked."

Step-by-step execution:

1. The agent calls get_single_oracle_fusion_cloud_epm_user_by_id using the provided email as the lookup key.
2. It parses the nested JSON payload to evaluate the account status boolean and extract the array of groups.
3. The LLM formats the technical group IDs into a human-readable IT summary and drafts the email text, saving the security analyst twenty minutes of manual console navigation.

Security and Access Control

Giving an AI agent access to a tier-one financial planning system requires strict boundaries. Truto's MCP architecture enforces security at the infrastructure layer before the request ever touches Oracle.

• Method Filtering: You can enforce strict Read-Only constraints at the token level. By passing config: { methods: ["read"] } during creation, Truto will physically drop all create, update, and delete tools from the server payload. The LLM simply cannot hallucinate a write operation because the route does not exist.
• Tag Filtering: Limit the blast radius by tagging EPM resources. Passing tags: ["identity"] ensures the MCP server only exposes user and group endpoints, hiding financial dimension or cube management endpoints from the AI.
• Require API Token Auth: By default, possession of the cryptographic MCP URL grants access. For Zero Trust environments, set require_api_token_auth: true. This forces the ChatGPT client to also pass a valid Truto API Bearer token in the Authorization header, adding a strict identity check to the edge routing layer.
• Time-to-Live (TTL): Pass an expires_at ISO datetime when generating the server. Truto schedules an alarm in the distributed caching layer that automatically destroys the MCP token and its KV storage entries at the exact requested second. This is ideal for granting auditors 48-hour access windows.

Automate the Oracle EPM Audit Trail

Building a custom integration to map JSON-RPC tool calls to Oracle Fusion Cloud EPM's complex identity architecture is a massive technical debt trap. You have to handle fragmented domain routing, manage strict asynchronous pagination, and parse obscure rate limit headers just to read a list of users.

By leveraging a managed MCP infrastructure layer, your team can instantly securely expose Oracle EPM to ChatGPT. You maintain strict control over which endpoints the LLM can see, enforce read-only boundaries, and let the managed proxy handle the upstream formatting.

Stop manually exporting CSVs from Oracle Shared Services and let your AI agents orchestrate the audit trail.