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therealsachin

Langfuse MCP Server

get_comment

Retrieve detailed information about a specific comment using its unique identifier to analyze feedback or trace data in Langfuse analytics.

Instructions

Get detailed information about a specific comment.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
commentIdYesThe unique identifier of the comment to retrieve

Implementation Reference

  • The main handler function that executes the 'get_comment' tool logic: calls the Langfuse client to retrieve the comment by ID, formats the response as MCP content, and handles errors.
    export async function getComment(
      client: LangfuseAnalyticsClient,
      args: GetCommentArgs
    ) {
      try {
        const data = await client.getComment(args.commentId);
        return {
          content: [{ type: 'text' as const, text: JSON.stringify(data, null, 2) }],
        };
      } catch (error: any) {
        return {
          content: [{ type: 'text' as const, text: `Error getting comment: ${error.message}` }],
          isError: true,
        };
      }
    }
  • Zod schema for validating the input arguments to the 'get_comment' tool, requiring a commentId string.
    export const getCommentSchema = z.object({
      commentId: z.string({
        description: 'The unique identifier of the comment to retrieve'
      }),
    });
  • src/index.ts:836-849 (registration)
    Tool registration in the listTools handler: defines the 'get_comment' tool's metadata, description, and input schema for MCP discovery.
    {
      name: 'get_comment',
      description: 'Get detailed information about a specific comment.',
      inputSchema: {
        type: 'object',
        properties: {
          commentId: {
            type: 'string',
            description: 'The unique identifier of the comment to retrieve',
          },
        },
        required: ['commentId'],
      },
    },
  • src/index.ts:1141-1144 (registration)
    Dispatch/registration in the callTool switch statement: parses arguments using the schema and invokes the getComment handler.
    case 'get_comment': {
      const args = getCommentSchema.parse(request.params.arguments);
      return await getComment(this.client, args);
    }
  • TypeScript type definition inferred from the getCommentSchema for type safety.
    export type GetCommentArgs = z.infer<typeof getCommentSchema>;
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves detailed information but doesn't describe what 'detailed information' includes, whether it's a read-only operation, potential error conditions, or any performance or permission aspects. This leaves significant gaps in understanding the tool's behavior.

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, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core action, making it easy to parse quickly, and there's no wasted verbiage.

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 annotations and output schema, the description is incomplete for a retrieval tool. It doesn't explain what 'detailed information' entails, such as the structure or fields returned, which is crucial for an agent to understand the tool's output. This gap makes it inadequate for full contextual understanding.

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 has 100% description coverage, with the 'commentId' parameter well-documented as 'The unique identifier of the comment to retrieve'. The description adds no additional semantic context beyond this, such as format examples or constraints, so it meets the baseline for high schema coverage without extra value.

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

Purpose4/5

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

The description clearly states the verb ('Get') and resource ('detailed information about a specific comment'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_comments', which retrieves multiple comments rather than a specific one, leaving some room for improvement in sibling distinction.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'list_comments' for listing multiple comments or other retrieval tools, nor does it specify prerequisites or contexts for usage, leaving the agent without clear selection criteria.

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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