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standardbeagle

Harvest MCP Server

harvest_list_projects

Retrieve and filter projects from Harvest time tracking system to manage project visibility and access client-specific data.

Instructions

List all projects with filtering options. Use about {"tool": "harvest_list_projects"} for detailed parameters and examples.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
is_activeNoFilter by active status
client_idNoFilter by client ID
pageNoPage number
per_pageNoResults per page (max 100)

Implementation Reference

  • MCP server handler dispatches to HarvestClient.getProjects with tool arguments and formats response as JSON text content.
    case 'harvest_list_projects':
      const projects = await harvestClient.getProjects(typedArgs);
      return {
        content: [
          {
            type: 'text',
            text: JSON.stringify(projects, null, 2),
          },
        ],
      };
  • Tool definition with name, description, and input schema for MCP registration and validation.
      name: 'harvest_list_projects',
      description: 'List all projects with filtering options. Use about {"tool": "harvest_list_projects"} for detailed parameters and examples.',
      inputSchema: {
        type: 'object',
        properties: {
          is_active: { type: 'boolean', description: 'Filter by active status' },
          client_id: { type: 'string', description: 'Filter by client ID' },
          page: { type: 'number', description: 'Page number' },
          per_page: { type: 'number', description: 'Results per page (max 100)' }
        }
      }
    },
  • Core implementation fetches projects from Harvest API endpoint /projects with built query parameters.
    async getProjects(options?: any) {
      const queryString = this.buildQueryString(options);
      return this.makeRequest(`/projects${queryString}`);
    }
  • src/index.ts:69-73 (registration)
    Registers all tools (including harvest_list_projects) for MCP listTools request handling.
    server.setRequestHandler(ListToolsRequestSchema, async () => {
      return {
        tools: tools,
      };
    });
  • Utility method builds query string from filter parameters used by getProjects.
    private buildQueryString(params?: Record<string, any>): string {
      if (!params) return '';
      
      const queryParams = new URLSearchParams();
      Object.entries(params).forEach(([key, value]) => {
        if (value !== undefined && value !== null) {
          queryParams.append(key, String(value));
        }
      });
      
      const queryString = queryParams.toString();
      return queryString ? `?${queryString}` : '';
    }
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'filtering options' and pagination (implied by 'page' and 'per_page' parameters), but doesn't describe important behaviors like rate limits, authentication requirements, response format, or whether this is a read-only operation (though 'List' implies it).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is brief but contains redundant information - it references the tool name itself in the about instruction. The first sentence is useful, but the second sentence about 'about' adds no value for AI agent selection and could confuse rather than help.

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?

For a list tool with 4 parameters and no output schema, the description is insufficient. It doesn't explain what information is returned about projects, how pagination works in practice, or typical use cases. With no annotations and no output schema, more context about the operation would be helpful.

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 100%, so the schema already documents all four parameters thoroughly. The description adds minimal value beyond stating 'filtering options' exists, which the schema already shows through 'is_active' and 'client_id'. Baseline 3 is appropriate when schema does the heavy lifting.

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 ('projects') with scope ('all'), making the purpose immediately understandable. However, it doesn't specifically differentiate from sibling tools like 'harvest_list_clients' or 'harvest_list_tasks' beyond mentioning '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?

The description provides no guidance on when to use this tool versus alternatives like 'harvest_get_project' (for single project details) or 'harvest_list_project_assignments' (for project assignments). It mentions 'filtering options' but doesn't specify use cases or exclusions.

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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