Skip to main content
Glama
us-all

openmetadata-mcp-server

by us-all

suggest-metadata

Get autocomplete suggestions for OpenMetadata entity names based on query text. Improve search efficiency by narrowing down results to specific entity types.

Instructions

Get autocomplete suggestions for OpenMetadata entity names

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesQuery text for autocomplete suggestions
indexNoRestrict suggestions to a specific entity index
sizeNoNumber of suggestions to return
fieldNoField for suggestions (e.g. 'name')

Implementation Reference

  • The handler function that executes the suggest-metadata tool logic. Makes a GET request to /search/suggest on the OpenMetadata API with query, index, size, and field parameters.
    export async function suggestMetadata(params: z.infer<typeof suggestMetadataSchema>) {
      return omClient.get("/search/suggest", {
        q: params.q,
        index: params.index,
        size: Math.min(params.size ?? 10, 25),
        field: params.field,
      });
    }
  • Zod schema defining input parameters for suggest-metadata: q (required query), index (optional entity type), size (default 10, max enforced to 25), and field (optional suggestion field).
    export const suggestMetadataSchema = z.object({
      q: z.string().describe("Query text for autocomplete suggestions"),
      index: z.enum([
        "table_search_index", "topic_search_index", "dashboard_search_index",
        "pipeline_search_index", "mlmodel_search_index", "container_search_index",
        "query_search_index", "user_search_index", "team_search_index",
        "glossary_term_search_index", "tag_search_index", "data_product_search_index",
      ]).optional().describe("Restrict suggestions to a specific entity index"),
      size: z.coerce.number().optional().default(10).describe("Number of suggestions to return"),
      field: z.string().optional().describe("Field for suggestions (e.g. 'name')"),
    });
  • src/index.ts:170-170 (registration)
    Registration of the suggest-metadata tool on the MCP server under the 'search' category, using the schema shape and handler wrapped with error handling.
    tool("suggest-metadata", "Get autocomplete suggestions for OpenMetadata entity names", suggestMetadataSchema.shape, wrapToolHandler(suggestMetadata));
  • Helper registration function that registers the tool in the registry with its category, and conditionally registers on the MCP server if the category is enabled.
    function tool(name: string, description: string, schema: any, handler: any): void {
      registry.register(name, description, currentCategory);
      if (registry.isEnabled(currentCategory)) {
        server.tool(name, description, schema, handler);
      }
    }
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does not explicitly state that the tool is read-only, nor does it mention authentication requirements, rate limits, or side effects. While the name implies a read operation, the lack of explicit transparency is a gap for a tool with no annotation support.

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?

The description is a single, front-loaded sentence with no wasted words. It efficiently communicates the tool's purpose. Every word earns its place.

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?

Given the moderate complexity (4 params, enum, no output schema), the description is too minimal. It does not explain the nature of the suggestions (e.g., list of strings vs objects), the indexing scope, or how errors are handled. The agent lacks enough context to anticipate the tool's output, which is critical for a suggestion tool.

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?

All 4 parameters have descriptions in the input schema, achieving 100% schema coverage. The description adds no additional parameter guidance beyond what the schema provides. According to the rubric, when schema_description_coverage is high, the baseline is 3. The description does not enhance parameter understanding.

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 clearly states the tool's function: 'Get autocomplete suggestions for OpenMetadata entity names'. It specifies a verb ('Get'), resource ('autocomplete suggestions'), and domain ('OpenMetadata entity names'). This distinguishes it from sibling tools like search-metadata or semantic-search, which serve different purposes.

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 is provided on when to use this tool versus alternatives like search-metadata or semantic-search. The description lacks hints about prerequisites, input constraints, or typical use cases (e.g., for partial input fields). An agent would have to infer usage from the name alone.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/us-all/openmetadata-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server