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therealsachin

Langfuse MCP Server

list_projects

Retrieve available Langfuse projects to analyze analytics, costs, and usage data across multiple configurations.

Instructions

List configured Langfuse projects available to this MCP server.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The main handler function for the 'list_projects' tool. It retrieves the current project ID using the client and returns it as a JSON-formatted text content block.
    export async function listProjects(client: LangfuseAnalyticsClient) {
      const projectId = client.getProjectId();
    
      return {
        content: [
          {
            type: 'text' as const,
            text: JSON.stringify({ projects: [projectId] }, null, 2),
          },
        ],
      };
    }
  • Zod validation schema for the 'list_projects' tool input parameters. This tool takes no arguments.
    export const listProjectsSchema = z.object({});
  • src/index.ts:150-157 (registration)
    Registration of the 'list_projects' tool in the allTools array, which is used to respond to ListToolsRequest. Defines name, description, and input schema.
    {
      name: 'list_projects',
      description: 'List configured Langfuse projects available to this MCP server.',
      inputSchema: {
        type: 'object',
        properties: {},
      },
    },
  • src/index.ts:1000-1003 (registration)
    Dispatch logic in the CallToolRequest handler that validates input using listProjectsSchema and invokes the listProjects handler function.
    case 'list_projects': {
      const args = listProjectsSchema.parse(request.params.arguments);
      return await listProjects(this.client);
    }
  • src/index.ts:52-52 (registration)
    Import statement that brings the handler and schema into the main index file for use in tool dispatching.
    import { listProjects, listProjectsSchema } from './tools/list-projects.js';
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 mentions 'available to this MCP server', hinting at access scope, but fails to describe key behaviors like pagination, sorting, filtering, or response format. This is inadequate for a list operation with zero annotation coverage.

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 redundancy. It is appropriately sized and front-loaded, with no wasted words, making it easy for an agent to parse quickly.

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. It does not explain what 'configured' means, how projects are returned (e.g., list format, fields), or any behavioral constraints. For a list tool with no structured support, more context is needed to guide the agent effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description does not add parameter details, but this is acceptable given the schema's completeness. A baseline of 4 is appropriate for a tool with no parameters.

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 ('List') and resource ('configured Langfuse projects'), making the purpose unambiguous. However, it does not explicitly differentiate from sibling tools like 'get_projects' or 'project_overview', which prevents a perfect score.

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 such as 'get_projects' or 'project_overview'. It lacks context on use cases, prerequisites, or exclusions, leaving the agent to infer usage from the tool name alone.

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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