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Lightdash MCP Server

by syucream

lightdash_list_dashboards

Retrieve all dashboards for a specified project UUID.

Instructions

List all dashboards in a project

Input Schema

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

Implementation Reference

  • Handler for the 'lightdash_list_dashboards' tool. Parses the arguments using ListDashboardsRequestSchema, then calls the Lightdash API at /api/v1/projects/{projectUuid}/dashboards. Returns the results as formatted JSON text.
    case 'lightdash_list_dashboards': {
      const args = ListDashboardsRequestSchema.parse(
        request.params.arguments
      );
      const { data, error } = await lightdashClient.GET(
        '/api/v1/projects/{projectUuid}/dashboards',
        {
          params: {
            path: {
              projectUuid: args.projectUuid,
            },
          },
        }
      );
      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),
          },
        ],
      };
    }
  • Zod schema for input validation of the 'lightdash_list_dashboards' tool. Requires a single 'projectUuid' field (UUID string) described as obtainable from the project list.
    export const ListDashboardsRequestSchema = z.object({
      projectUuid: z
        .string()
        .uuid()
        .describe(
          'The UUID of the project. You can obtain it from the project list.'
        ),
    });
  • src/mcp.ts:69-73 (registration)
    Registration of the 'lightdash_list_dashboards' tool in the ListTools handler. Defines its name, description ('List all dashboards in a project'), and input schema (converted from Zod to JSON Schema via zodToJsonSchema).
    {
      name: 'lightdash_list_dashboards',
      description: 'List all dashboards in a project',
      inputSchema: zodToJsonSchema(ListDashboardsRequestSchema),
    },
Behavior3/5

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

With no annotations, the description only states the tool lists dashboards. It does not disclose pagination, filtering, or return format, but the operation is inherently read-only and simple. No contradictions.

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?

A single sentence with no redundancy, directly communicating the tool's purpose.

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?

Given the tool's simplicity (one parameter, no output schema), the description is mostly complete. However, it could hint at the return value (e.g., listing dashboard names or UUIDs).

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?

The input schema fully covers the single parameter with a clear description and a hint to obtain the UUID. The tool description does not add additional context 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 clearly states the tool lists all dashboards in a project, using a specific verb and resource scope. It distinguishes from sibling tools like lightdash_list_charts and lightdash_list_projects.

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 alternatives (e.g., getting dashboards as code) or any prerequisites beyond the required projectUuid. The description is purely functional.

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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