Skip to main content
Glama
jhliberty

Basecamp MCP Server

by jhliberty

get_question_answers

Retrieve answers to daily check-in questions using project and question IDs. Supports paginated responses for efficient data management on Basecamp projects.

Instructions

Get answers on daily check-in question

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number for paginated response
project_idYesThe project ID
question_idYesThe question ID

Implementation Reference

  • src/index.ts:525-537 (registration)
    Registration of the 'get_question_answers' tool in the listTools handler, including input schema
    {
      name: 'get_question_answers',
      description: 'Get answers on daily check-in question',
      inputSchema: {
        type: 'object',
        properties: {
          project_id: { type: 'string', description: 'The project ID' },
          question_id: { type: 'string', description: 'The question ID' },
          page: { type: 'number', description: 'Page number for paginated response' },
        },
        required: ['project_id', 'question_id'],
      },
    },
  • TypeScript interface defining the structure of QuestionAnswer objects returned by the tool
    export interface QuestionAnswer {
      id: string;
      content: string;
      created_at: string;
      creator: Person;
    }
  • Core helper function in BasecampClient that performs the API call to retrieve question answers
    async getQuestionAnswers(projectId: string, questionId: string, page = 1): Promise<QuestionAnswer[]> {
      const response = await this.client.get(
        `/buckets/${projectId}/questions/${questionId}/answers.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 answers') without detailing traits like whether it's read-only, requires authentication, has rate limits, returns paginated data, or what happens on errors. The mention of 'daily check-in question' hints at context but lacks operational specifics needed for safe invocation.

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 front-loads the core purpose without unnecessary words. It's appropriately sized for a simple tool, but could be more informative by adding context or differentiation. There's no waste, but it risks under-specification due to brevity.

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 tool's complexity (3 parameters, no output schema, no annotations), the description is incomplete. It doesn't explain the return values, error handling, or behavioral traits, leaving gaps for an AI agent. With no output schema and minimal description, it inadequately supports correct tool selection and invocation.

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 clear parameter documentation (page, project_id, question_id). The description adds no additional meaning beyond the schema, as it doesn't explain parameter relationships, formats, or usage examples. With high schema coverage, the baseline is 3, but the description fails to compensate or enhance understanding.

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 ('Get answers on daily check-in question'), which is clear but vague. It specifies the resource ('answers') and context ('daily check-in question'), but doesn't distinguish it from sibling tools like 'get_daily_check_ins' or explain what 'answers' entail. The verb 'Get' is generic, lacking specificity about the operation type (e.g., list, retrieve, fetch).

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 is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, context (e.g., after using 'get_daily_check_ins'), or exclusions. With sibling tools like 'get_daily_check_ins' and 'get_comments', there's no indication of how this tool differs or when it's appropriate, leaving usage unclear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Related Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/jhliberty/basecamp-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server