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Lightdash MCP Server

by syucream

lightdash_get_metadata

Retrieve metadata about a specific table from the Lightdash data catalog by providing the project UUID and table name.

Instructions

Get metadata for a specific table in the data catalog

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectUuidYesThe UUID of the project. You can obtain it from the project list.
tableYes

Implementation Reference

  • The handler for the lightdash_get_metadata tool. Parses arguments with GetMetadataRequestSchema, calls the Lightdash API endpoint /api/v1/projects/{projectUuid}/dataCatalog/{table}/metadata, and returns the results as JSON text.
    case 'lightdash_get_metadata': {
      const args = GetMetadataRequestSchema.parse(request.params.arguments);
      const { data, error } = await lightdashClient.GET(
        '/api/v1/projects/{projectUuid}/dataCatalog/{table}/metadata',
        {
          params: {
            path: {
              projectUuid: args.projectUuid,
              table: args.table,
            },
          },
        }
      );
      if (error) {
        throw new Error(
          `Lightdash API error: ${error.error.name}, ${
            error.error.message ?? 'no message'
          }`
        );
      }
      return {
        content: [
          {
            type: 'text',
            text: JSON.stringify(data.results, null, 2),
          },
        ],
      };
    }
  • The Zod schema for the lightdash_get_metadata tool's input parameters. Defines projectUuid (UUID string) and table (non-empty string) as required fields.
    export const GetMetadataRequestSchema = z.object({
      projectUuid: z
        .string()
        .uuid()
        .describe(
          'The UUID of the project. You can obtain it from the project list.'
        ),
      table: z.string().min(1, 'Table name cannot be empty'),
    });
  • src/mcp.ts:99-103 (registration)
    Registration of the lightdash_get_metadata tool in the server's tool list with its description and input schema.
    {
      name: 'lightdash_get_metadata',
      description: 'Get metadata for a specific table in the data catalog',
      inputSchema: zodToJsonSchema(GetMetadataRequestSchema),
    },
Behavior2/5

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

Without annotations, the description carries the full burden. It only states 'Get metadata' implying a read operation, but lacks details on authentication needs, rate limits, side effects, or what the metadata contains. The description is overly minimal.

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 concise sentence that communicates the core purpose without any unnecessary words. It is front-loaded and efficient.

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 lack of output schema and annotations, the description should provide more context about the returned metadata (e.g., fields, structure). It does not sufficiently compensate for these gaps, leaving the agent underinformed.

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 50% (projectUuid has a description, table does not). The description does not add any parameter semantics beyond what is in the schema, so it neither helps nor harms. Baseline of 3 is appropriate.

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 verb 'Get' and the resource 'metadata for a specific table' within the data catalog, distinguishing it from sibling tools like lightdash_get_catalog (which likely retrieves the entire catalog) and lightdash_get_metrics_catalog.

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 given on when to use this tool versus alternatives such as lightdash_get_catalog or lightdash_get_metrics_catalog. There is no mention of prerequisites or context for invoking the tool.

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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