FMEPM Connect for Oracle EPM

Read Data Integration

read_data_integration

Read-onlyIdempotent

Reads pipeline definitions for supplied pipeline codes, or a Data Integration job status. Oracle documents no GET listing every pipeline code or load rule; ask for the codes or names from its console. Pipelines show stages and jobs, with parameter values omitted. A read submits no job. This is pod-wide and cannot run under an application-restricted policy. Use it to inspect known pipelines or check an integration run. https://docs.oracle.com/en/cloud/saas/enterprise-performance-management-common/prest/get_pipeline.html

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "action": "<action>"
    },
    "name": "read_data_integration"
  }
}

Input Schema

Name	Required	Description
`jobId`	No	Data Integration process id, not an application job id.
`action`	Yes	Inspect supplied pipeline codes, or get a job's status.
`connection`	No	Connection id or label from list_connections. Defaults to the user's default connection.
`pipelineCodes`	No	Known pipeline codes, not their display names. At most ten.

Schema Changelog

Changes observed during successful MCP inspections.

AddedOct 30, 2026

TDQS

A4.1/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the readOnly and idempotent annotations, the description adds meaningful behavior: reads submit no job, pipeline parameter values are omitted, the operation is pod-wide, and it cannot run under an application-restricted policy. These are useful operational constraints not captured in annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The purpose is front-loaded in the first sentence, and subsequent sentences carry useful constraints without obvious filler. It is somewhat long, but most statements earn their place by preventing common misuse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a four-parameter read tool with no output schema, the description provides sufficient context: what is returned for pipelines, what is omitted, what is not available, and the policy limitation. The connection parameter is left to the schema, which is reasonable given full schema coverage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents action, jobId, connection, and pipelineCodes. The description reinforces that only known pipeline codes/rather than display names should be supplied, but adds little parameter-level detail beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description starts with a specific verb and resource: 'Reads pipeline definitions... or a Data Integration job status.' It clearly distinguishes the two supported inspection modes and notes that no listing endpoint is available, which helps an agent understand the tool's narrow scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives clear usage context: use for known pipeline codes or checking an integration run, and explicitly says Oracle provides no GET to list every pipeline code. It does not name sibling alternatives such as run_data_integration or check_job_status, so explicit exclusions are missing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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