CELPass: CELPIP practice and CRS calculator

CELPIP practice questions with answers, sample answers, and Canada's November 2026 CRS calculator.

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质量与安全性

A
描述质量
100%
模式完整度
98%
命名质量
100%
投毒风险
100%
权限匹配度
100%
协议合规性
100%

基于对工具定义和协议合规性的自动分析。

上下文开销

~1,204token 数(工具定义)
~1.1 KB典型响应大小
对注意力有中等影响(占 128k 上下文窗口的 0.94%)

这是每次将服务器的工具加载到模型上下文窗口时所消耗的大致 token 数。数值越高,可用于其他任务的注意力就越少。

安装

一键安装

将以下内容添加到你的 `claude_desktop_config.json` 文件中:

{
  "mcpServers": {
    "celpip": {
      "url": "https://celpass.com/mcp"
    }
  }
}

远程端点

https://celpass.com/mcpstreamable-http

它能做什么

工具清单

工具(5)

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🟢calculate_crs_november_2026(current_crs_score, spouse_counted, canadian_work_years, high_wage_jobs, job_offer_noc_code)

Estimate the CRS points an Express Entry candidate gains on November 3, 2026, when Canadian work experience becomes the Labour Market Integration factor: unchanged work-length points plus 70/40/20 extra points after 12+ months in a 2×/1.5×/1.3× high-wage occupation, or 100/70/50 points for a job offer in one (no LMIA needed), whichever is higher, never both. Max 150 (140 with a spouse). Give NOC codes; the tool looks up each occupation's level on IRCC's list. Only this factor changes.

输入模式

{
  "type": "object",
  "properties": {
    "current_crs_score": {
      "type": "integer",
      "minimum": 0,
      "maximum": 1200,
      "description": "CRS score in the profile today (optional)"
    },
    "spouse_counted": {
      "type": "boolean",
      "description": "True if a spouse or common-law partner is coming to Canada and isn't a citizen or PR"
    },
    "canadian_work_years": {
      "type": "integer",
      "minimum": 0,
      "maximum": 5,
      "description": "Years of skilled (TEER 0–3) work in Canada in the last 10 years, as counted today; 5 means 5 or more"
    },
    "high_wage_jobs": {
      "type": "array",
      "description": "Canadian jobs (part of that work experience) and the months spent in each. Omit if none.",
      "items": {
        "type": "object",
        "properties": {
          "noc_code": {
            "type": "string",
            "pattern": "^\\d{5}$",
            "description": "5-digit NOC 2021 code, e.g. 21231"
          },
          "months": {
            "type": "number",
            "minimum": 0
          }
        },
        "required": [
          "noc_code",
          "months"
        ]
      }
    },
    "job_offer_noc_code": {
      "type": "string",
      "pattern": "^\\d{5}$",
      "description": "NOC code of a qualifying full-time job offer, if any"
    }
  },
  "required": [
    "spouse_counted",
    "canadian_work_years"
  ]
}
🟢find_high_wage_occupation(query)

Search IRCC's high-wage occupation list (in effect November 3, 2026; 186 NOC 2021 codes) by job title words or NOC code. Returns each match's level (2×, 1.5× or 1.3× the average median wage) and the CRS points it earns. An occupation that isn't listed earns no high-wage or job offer points.

输入模式

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "minLength": 1,
      "description": "Job title words or a NOC code, e.g. 'software engineer' or '72201'"
    }
  },
  "required": [
    "query"
  ]
}
🟢get_celpip_practice_question(skill, part)

Get one random CELPIP practice item from CELPass in the real test format. Reading (parts 1–4): a passage or diagram with multiple-choice questions and fill-in blanks shown as ____(n). Listening (parts 1–6): the questions plus a listen_url where the learner plays the recording (no transcript). Speaking (parts 1–8): the task, any picture, and the preparation and speaking times. Writing (tasks 1–2): the email or survey task with its time limit and word count. No answers are included: mark Reading and Listening with check_celpip_answers, and compare Speaking and Writing with get_celpip_sample_answers. Each day has a new set of items (3 per part), the same for everyone; calls return a random one from today's set.

输入模式

{
  "type": "object",
  "properties": {
    "skill": {
      "type": "string",
      "enum": [
        "reading",
        "listening",
        "speaking",
        "writing"
      ],
      "description": "Default reading"
    },
    "part": {
      "type": "integer",
      "minimum": 1,
      "maximum": 8,
      "description": "Part number (Reading 1–4, Listening 1–6, Speaking 1–8, Writing 1–2); omit for any part"
    }
  }
}
🟢check_celpip_answers(question_id, answers)

Mark a learner's answers to a Reading or Listening item from get_celpip_practice_question: returns the score, the correct letter for each question and an explanation of why each option is right or wrong.

输入模式

{
  "type": "object",
  "properties": {
    "question_id": {
      "type": "string",
      "description": "question_id returned with the question"
    },
    "answers": {
      "type": "object",
      "description": "Question number → chosen letter, e.g. {\"1\": \"C\", \"2\": \"A\"}",
      "additionalProperties": {
        "type": "string"
      }
    }
  },
  "required": [
    "question_id",
    "answers"
  ]
}
🟢get_celpip_sample_answers(question_id)

Sample answers at several CELPIP levels (4–5, 7–8, 9–10, 11–12) for a Speaking or Writing task from get_celpip_practice_question, with how CELPIP rates it. Use them to give the learner feedback on their own answer.

输入模式

{
  "type": "object",
  "properties": {
    "question_id": {
      "type": "string",
      "description": "question_id returned with the Speaking or Writing task"
    }
  },
  "required": [
    "question_id"
  ]
}

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已验证未记录版本5 个工具