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openmetadata-mcp-server

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update-ml-model

Apply JSON Patch operations to modify fields (e.g., description) of an ML model identified by its UUID.

Instructions

Update an ML model using JSON Patch operations

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesML Model UUID to update
operationsYesJSON Patch operations array (e.g. [{op:'add', path:'/description', value:'...'}])

Implementation Reference

  • The updateMlModel handler function: sends a PATCH request to /mlmodels/{id} with JSON Patch operations.
    export async function updateMlModel(params: z.infer<typeof updateMlModelSchema>) {
      assertWriteAllowed();
      return omClient.patch(`/mlmodels/${params.id}`, params.operations);
    }
  • The updateMlModelSchema Zod schema: defines required 'id' (string UUID) and 'operations' (array of JSON Patch operation objects).
    export const updateMlModelSchema = z.object({
      id: z.string().describe("ML Model UUID to update"),
      operations: z.array(z.record(z.string(), z.any())).describe("JSON Patch operations array (e.g. [{op:'add', path:'/description', value:'...'}])"),
    });
  • src/index.ts:314-314 (registration)
    Registration of the 'update-ml-model' tool in the MCP server, wiring the schema and handler.
    tool("update-ml-model", "Update an ML model using JSON Patch operations", updateMlModelSchema.shape, wrapToolHandler(updateMlModel));
  • Import of updateMlModelSchema and updateMlModel from src/tools/mlmodels.ts.
      getContainerByNameSchema, getContainerByName, createContainerSchema, createContainer,
      updateContainerSchema, updateContainer, deleteContainerSchema, deleteContainer,
    } from "./tools/containers.js";
    import {
      listMlModelsSchema, listMlModels, getMlModelSchema, getMlModel,
      getMlModelByNameSchema, getMlModelByName, createMlModelSchema, createMlModel,
      updateMlModelSchema, updateMlModel, deleteMlModelSchema, deleteMlModel,
Behavior2/5

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

With no annotations, the description carries full burden. It does not disclose side effects, authorization needs, error behaviors, or whether the update is partial or full. Only states the operation.

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

Conciseness5/5

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

Single sentence, no superfluous words. Efficiently conveys the core action and method.

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

Completeness2/5

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

Lacks explanation of the update's effect (whether it returns updated model, partial vs full update), error conditions (model not found), or any behavioral details. Incomplete for a mutation tool with no annotations.

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 descriptions already detail parameters (UUID and JSON Patch array). Description only restates the method, adding no new semantic value. Schema coverage is 100%, so baseline 3 applies.

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?

Description clearly states verb 'Update' and resource 'ML model', and specifies method 'using JSON Patch operations'. This distinguishes it from create-ml-model and delete-ml-model among siblings.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus create-ml-model or delete-ml-model. No context on prerequisites or scenarios where JSON Patch is appropriate.

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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