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jhliberty

Basecamp MCP Server

by jhliberty

get_daily_check_ins

Retrieve daily check-in questionnaires for a specific project using project ID, with pagination support for organized responses.

Instructions

Get project's daily checking questionnaire

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number for paginated response
project_idYesThe project ID

Implementation Reference

  • The MCP tool handler for 'get_daily_check_ins' that parses arguments, calls the Basecamp client method, and returns a formatted JSON response.
    case 'get_daily_check_ins': {
      const checkIns = await client.getDailyCheckIns(typedArgs.project_id, typedArgs.page || 1);
      return {
        content: [{
          type: 'text',
          text: JSON.stringify({
            status: 'success',
            daily_check_ins: checkIns,
            count: checkIns.length
          }, null, 2)
        }]
      };
    }
  • src/index.ts:513-524 (registration)
    Tool registration in the MCP server's tools array, including name, description, and input schema definition.
    {
      name: 'get_daily_check_ins',
      description: "Get project's daily checking questionnaire",
      inputSchema: {
        type: 'object',
        properties: {
          project_id: { type: 'string', description: 'The project ID' },
          page: { type: 'number', description: 'Page number for paginated response' },
        },
        required: ['project_id'],
      },
    },
  • Helper method in BasecampClient that fetches daily check-ins (questionnaire questions) from the Basecamp API.
    async getDailyCheckIns(projectId: string, page = 1): Promise<DailyCheckIn[]> {
      const project = await this.getProject(projectId);
      const questionnaire = project.dock.find(item => item.name === 'questionnaire');
      
      if (!questionnaire) {
        throw new Error(`No questionnaire found for project ${projectId}`);
      }
    
      const response = await this.client.get(
        `/buckets/${projectId}/questionnaires/${questionnaire.id}/questions.json`,
        { params: { page } }
      );
      return response.data;
    }
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 only states the action ('Get') without detailing permissions, rate limits, pagination behavior (implied by the 'page' parameter but not explained), or response format. This is inadequate for a tool with parameters and no output schema.

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

Conciseness4/5

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 is appropriately sized and front-loaded, though it could be more informative given the lack of other context.

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 no annotations, no output schema, and a vague purpose, the description is incomplete. It doesn't explain what a 'daily checking questionnaire' is, how results are structured, or behavioral traits like pagination. For a tool with parameters and sibling alternatives, this leaves significant gaps for an AI agent.

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 both parameters ('project_id' and 'page') adequately. The description adds no additional meaning beyond what the schema provides, such as clarifying the 'daily checking questionnaire' context for 'project_id' or explaining pagination details for 'page'. Baseline 3 is appropriate as the schema does the heavy lifting.

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

Purpose3/5

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

The description states the tool's purpose as retrieving a 'daily checking questionnaire' for a project, which is clear but vague. It specifies the resource ('project's daily checking questionnaire') and verb ('Get'), but doesn't clarify what a 'daily checking questionnaire' entails or how it differs from sibling tools like 'get_question_answers' or 'get_cards' that might retrieve similar project data.

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 prerequisites, exclusions, or comparisons to sibling tools such as 'get_question_answers' or 'get_cards', leaving the agent to infer usage context without explicit direction.

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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