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Reviewing a candidate is three steps: find the result, read its details, and (optionally) export a report.
StepEndpointMCP tool
List resultsGET /merchant-result-listlist_interview_results
Read transcript + scoresPOST /job-interview-detailsget_interview_result_details
Export PDF / HTML / JSONPOST /job-interview-pdfgenerate_interview_report

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1. Find the result

List your merchant’s results, newest first. Everything is a query parameter — no request body. 
curl -G https://cool.jobmojito.com/functions/v1/merchant-result-list \
  -H "Authorization: Bearer $SUPABASE_JWT" \
  --data-urlencode "tab=completed" \
  --data-urlencode "order_by=score" \
  --data-urlencode "limit=25"
Useful filters: interview_id (one interview), tab (completed, shortlist, undecided, decided-selected, decided-rejected, …), step (pre-screening or interview), order_by (score, created_at_newest, …), filter_text, plus limit/offset. The response has data[] and pagination. Each row includes interview_result_id, candidate_name, candidate_email, status, decision_status, and score. Grab the interview_result_id for the next step.
To browse candidates instead of results, use GET /merchant-candidate-list (list_candidates); to browse interview definitions, use GET /merchant-interview-list (list_interviews).

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2. Read the transcript and assessment

curl -X POST https://cool.jobmojito.com/functions/v1/job-interview-details \
  -H "Authorization: Bearer $SUPABASE_JWT" \
  -H "Content-Type: application/json" \
  -d '{
    "interview_result_id": "RESULT_UUID",
    "get_signed_recordings": false
  }'
You get the overall scores (score, score_sentiment, score_words_per_minute, …), AI write-ups (ai_analysis, ai_analysis_recruiter, ai_analysis_recruiter_why_hire / …_why_not_hire), any recruiter_risks, and the full transcript array. Each transcript item has question_asked, answer, per-answer ai_analysis, and a score.

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3. Export a report

Generate a shareable report as a PDF (signed URL), raw HTML, or structured JSON. Pass a single interview_result_id or an array interview_result_ids for a combined report. 
curl -X POST https://cool.jobmojito.com/functions/v1/job-interview-pdf \
  -H "Authorization: Bearer $SUPABASE_JWT" \
  -H "Content-Type: application/json" \
  -d '{
    "interview_result_id": "RESULT_UUID",
    "export_type": "pdf",
    "store_file": true,
    "export_features_result": {
      "ai_recruiter_assessment": true,
      "ai_scoring_rubric": true,
      "transcript": true,
      "analytics": true
    }
  }'
The response shape depends on export_type:
  • pdf → pdf_export_url + pdf_export_valid_until (set store_file: true).
  • html → html_export (a full HTML document string).
  • json → json_export (structured object).

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Report content toggles (export_features_result)

Set export_features_result.mojito_language_code to translate the report into another language (0.1 credit per result when it differs from the result’s own language).
Want to give a candidate another go? POST /job-interview-result-request-another-attempt (request_another_interview_attempt) re-opens a submitted result.