DeepMark 远程 MCP 服务器是什么?
DeepMark 的远程 MCP 服务器是一个托管的 Model Context Protocol 端点,地址是 https://api.getdeepmark.com/mcp,AI 助手无需在本地安装或运行任何东西即可连接。

基本信息
DeepMark helps teachers deliver rapid, consistent marking with meaningful feedback for every student — in a fraction of the time. What once took a week, now takes one free period.
https://api.getdeepmark.com/mcpclaude mcp add deepmark --transport http https://api.getdeepmark.com/mcpCreate a complete, markable exam paper from pasted text. Provide the question paper text (required) and, if the teacher has one, the mark scheme text — DeepMark extracts it. Omit the mark scheme to have DeepMark generate schemes (lower quality, but the paper is still markable). Send RAW text: do not pre-structure it into questions or author a mark scheme yourself. Extraction runs asynchronously — this returns a job_id. Poll ingestion_get until it reaches `awaiting_confirmation`, then call paper_confirm to mint the paper. RATE LIMITED: up to 3 papers per 24 hours per account (marking existing papers is unaffected).
Mint the exam paper from a job parked at awaiting_confirmation (created via paper_create). Materialises the ExamPaper, questions, and mark schemes from the extraction draft, synchronously. Optionally override the detected identity (title/subject/board/year); omit to use what extraction detected. Idempotent — confirming an already-committed job returns its paper. Returns the exam_paper_id.
Read the current state of an ingestion job (paper creation or document ingestion). Returns the status plus a derived `awaiting` gate ('triage' | 'confirmation' | null), whether it is terminal, and the next action to take. Poll this after starting a job: a paper-creation job parks at `awaiting_confirmation` (then call paper_confirm) — it does NOT run to `complete` on its own. Stop polling on a terminal status (complete | failed | cancelled) or when an action is required.
Mark a student's typed answers against an existing exam paper. Provide the exam_paper_id and per-question answers keyed by question_number. DeepMark creates a submission and grades it through its canonical marker (per mark point / level descriptor) — results stream into the teacher's editor live. Grading is asynchronous: this returns a submission_id; poll submission_get for the per-question grades.
Read the grading state and per-question marks for a submission (created via submission_mark). Returns each question's marking_status, awarded/max marks, level, and feedback, plus an overall status ('grading' until every question is marked). Poll after submission_mark.
Retrieve the marking result for a specific answer by its ID
List all exam papers with optional filtering
Retrieve a specific exam paper by its ID with question details
Update an existing GCSE question by its ID
Update an existing mark scheme by its ID
DeepMark helps teachers deliver rapid, consistent marking with meaningful feedback for every student — in a fraction of the time. What once took a week, now takes one free period.
This MCP server exposes DeepMark's marking engine directly to your assistant, so exam papers can be created, marked and interrogated conversationally — without touching the web app.
DeepMark marks student answers against a real mark scheme, following the structure an examiner works to. It supports three marking types:
Every mark is returned with feedback tied to the specific criteria met and missed, so the reasoning is visible rather than a bare number.
Papers
paper_create — build a complete, markable exam paper from pasted textpaper_confirm — mint a paper from a job awaiting confirmationpaper_list / paper_get — browse and retrieve papers with question detailquestion_update / markScheme_update — amend questions and mark schemesingestion_get — check the state of a paper-creation or ingestion jobMarking
submission_mark — mark a set of typed answers against an existing papersubmission_get — read grading state and per-question marksmarkResult_get — retrieve the marking result for a single answerMarking is asynchronous. submission_mark returns a submission_id
immediately and grading continues in the background, streaming into the
teacher's editor as each question completes.
submission_mark → receive submission_idsubmission_get until status is completeawarded, max, level and feedbackAllow roughly 15–25 seconds per question. Papers created via paper_create
follow the same pattern — poll ingestion_get, then paper_confirm.
Marking inside a reasoning context means the class set is immediately available to question. Once a set is marked you can ask which mark points the cohort consistently missed, where a levels-of-response band clustered, or which misconception is driving the spread — the diagnostic layer that gets lost when marking is just a number returned.
Remote server — no local install. Add the URL and authenticate with Google OAuth. Access is scoped to your own account.
Uploaded scripts and mark schemes are not used to train models. DeepMark is built in line with the DfE's Generative AI Product Safety Standards.
Built for UK secondary teachers marking GCSE and A-Level extended writing — subject-agnostic and model-agnostic by design.
Website: https://deepmark.co.uk
DeepMark 的远程 MCP 服务器是一个托管的 Model Context Protocol 端点,地址是 https://api.getdeepmark.com/mcp,AI 助手无需在本地安装或运行任何东西即可连接。
把端点 https://api.getdeepmark.com/mcp 添加到任意支持 MCP 的客户端,比如 Claude Code、Cursor 或 VS Code。本页的接入代码块可以一步配置好每个客户端。
需要。DeepMark 使用 OAuth——第一次连接时,你的 MCP 客户端会打开浏览器窗口登录并授权,之后会复用这个凭证。
DeepMark 暴露的是 Streamable HTTP 端点,这是远程 MCP 服务器普遍使用、主流客户端都支持的传输方式。
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