interview-webmcp.vercel.app

{
  "name": "set_candidate_profile",
  "kind": "act",
  "impl": "imperative",
  "description": "Set or update the candidate's field, target position, years of experience, and skills. Call this FIRST before starting an interview.",
  "inputSchema": {
    "type": "object",
    "properties": {
      "field": {
        "type": "string",
        "description": "Broad field, e.g. 'Software Engineering'."
      },
      "position": {
        "type": "string",
        "description": "Specific role, e.g. 'Senior Backend Engineer'."
      },
      "experienceYears": {
        "type": "number",
        "minimum": 0,
        "maximum": 50
      },
      "skills": {
        "type": "array",
        "items": {
          "type": "string"
        },
        "description": "Concrete technologies/skills, e.g. ['Python','AWS','PostgreSQL']."
      },
      "focusAreas": {
        "type": "array",
        "items": {
          "type": "string"
        },
        "description": "Optional weak spots the candidate wants to drill."
      }
    },
    "required": [
      "field",
      "position",
      "experienceYears",
      "skills"
    ],
    "additionalProperties": false
  }
}

{
  "name": "start_interview",
  "kind": "act",
  "impl": "imperative",
  "description": "Begin the mock interview. YOU (the AI) must write ALL the interview questions yourself, right now, in this single call — there is no built-in question bank. Pass them as the `questions` array, each genuinely tailored to the candidate's profile (use their exact field/position/skills/experience — vary the type across behavioral, technical, situational, system_design, culture_fit). After this call, IMMEDIATELY call `run_interview` (no arguments) — that ONE call runs the entire ask/wait/evaluate loop for every question and blocks until the candidate finishes, returning the full transcript and final report at the end. Do not try to ask questions one at a time yourself.",
  "inputSchema": {
    "type": "object",
    "properties": {
      "difficulty": {
        "type": "string",
        "enum": [
          "junior",
          "mid",
          "senior"
        ]
      },
      "questions": {
        "type": "array",
        "minItems": 3,
        "maxItems": 20,
        "description": "ALL the questions for this interview, in order, written by you and tailored to the candidate's profile. Vary the `type` across the list.",
        "items": {
          "type": "object",
          "properties": {
            "text": {
              "type": "string",
              "description": "The exact question text."
            },
            "type": {
              "type": "string",
              "enum": [
                "behavioral",
                "technical",
                "system_design",
                "situational",
                "culture_fit"
              ]
            },
            "rubricPoints": {
              "type": "array",
              "items": {
                "type": "string"
              },
              "description": "2-4 bullet points describing what a strong answer covers."
            },
            "hint": {
              "type": "string",
              "description": "Optional short on-screen hint for the candidate."
            }
          },
          "required": [
            "text",
            "type"
          ],
          "additionalProperties": false
        }
      }
    },
    "required": [
      "questions"
    ],
    "additionalProperties": false
  }
}

{
  "name": "run_interview",
  "kind": "act",
  "impl": "imperative",
  "description": "Runs the full interview using the exact questions you passed to `start_interview`. For each one: displays it, WAITS for the candidate to type and submit their answer, evaluates it, and moves to the next — automatically, without any further tool calls from you. Returns once, at the very end, with every question/answer/evaluation and the final summary report. Call this immediately after `start_interview`.",
  "inputSchema": {
    "type": "object",
    "properties": {},
    "additionalProperties": false
  }
}

{
  "name": "get_transcript",
  "kind": "answer",
  "impl": "imperative",
  "description": "Returns the full list of asked questions, given answers, and evaluations so far.",
  "inputSchema": {
    "type": "object",
    "properties": {},
    "additionalProperties": false
  }
}

{
  "name": "end_interview",
  "kind": "act",
  "impl": "imperative",
  "description": "Ends the session and produces a final report: overall score, strengths, development areas, hire recommendation, and next steps. Only call this after `remaining_questions` reached 0 from `ask_question`, OR the candidate has explicitly asked to stop early. If questions are still remaining and the candidate hasn't asked to stop, this call will be REJECTED — call `ask_question` again instead.",
  "inputSchema": {
    "type": "object",
    "properties": {
      "force": {
        "type": "boolean",
        "description": "Set true ONLY if the candidate explicitly asked to end early / skip remaining questions. Otherwise omit — ending with unanswered questions remaining is rejected by default."
      }
    },
    "additionalProperties": false
  }
}

{
  "name": "reset_session",
  "kind": "act",
  "impl": "imperative",
  "description": "Clear all state. Returns to the profile screen so a new interview can start.",
  "inputSchema": {
    "type": "object",
    "properties": {},
    "additionalProperties": false
  }
}