Tutor Lesson-Script & Transcript Retrieval MCP

Tutor Lesson-Script & Transcript Retrieval MCP

Enables retrieval of tutor lesson scripts from Supabase and diarized transcripts from PencilSpaces, with Google OAuth gating to a domain.

Category
访问服务器

README

Tutor Lesson-Script & Transcript Retrieval MCP Server

A minimal remote MCP server exposing one tool, get_lesson_script, that returns the markdown tutor script for a lesson from ps_lessons.script on your Supabase project.

Retrieval only — no scoring or rubric logic.

The tool

get_lesson_script(lesson: str) -> str

Accepts a lesson code ("401.1", "413.2"), a concept ("Suffix s", "sh"), or a name ("Orientation", "Unit 1 Recap", "Unit 3 Passwords and Play"). It is scoped to curriculum_id = your-curriculum-uuid.

Behavior:

  • One match → returns that lesson's markdown script.
  • No match → a short message with the closest lesson names.
  • Several matches (e.g. "401" → 401.1 and 401.2) → lists them and asks you to be specific.
  • Match but empty script → says the lesson exists but isn't populated yet.

Environment variables

Variable Purpose
SUPABASE_URL https://your-project-ref.supabase.co
SUPABASE_SERVICE_ROLE_KEY Supabase → Project Settings → API → service_role key. Server-side only.
CURRICULUM_ID The curriculum UUID this tool is scoped to (set your own).
CACHE_TTL Optional; seconds to cache lesson rows (default 60).

Copy .env.example to .env and fill in the key for local runs.

Run locally

pip install -r requirements.txt
export $(grep -v '^#' .env | xargs)   # or set the vars however you prefer
python server.py                      # serves Streamable HTTP at http://localhost:8000/mcp

Test it with the MCP Inspector (no code needed):

npx @modelcontextprotocol/inspector
# Transport: Streamable HTTP   URL: http://localhost:8000/mcp
# then call get_lesson_script with {"lesson": "401.1"}

(Opening /mcp in a browser returns HTTP 406 — that's expected; it needs MCP headers.)

Deploy on Render

  1. Push this repo to GitHub.
  2. Render dashboard → New → Blueprint, point at the repo (uses render.yaml). Or New → Web Service with build pip install -r requirements.txt and start python server.py.
  3. Set env vars SUPABASE_URL, SUPABASE_SERVICE_ROLE_KEY, and CURRICULUM_ID in the Render dashboard.
  4. Deploy. Your endpoint is https://<service-name>.onrender.com/mcp.

Free Render instances sleep after inactivity and cold-start in ~30–60s. Hit the endpoint once to warm it before a live demo, or use a paid instance.

Add as a Claude custom connector

In Claude → Customize → Connectors → + → Add custom connector:

  • Name: Tutor Lesson Scripts
  • URL: https://<service-name>.onrender.com/mcp
  • Leave OAuth blank (this server is unauthenticated — see note below).

Then enable it per chat via the + button → Connectors, and ask, e.g., "Use Tutor Lesson Scripts to get the script for lesson 401.1."

(On Team/Enterprise plans an Owner adds the connector under Organization Settings → Connectors first, then members connect.)

Demo suggestion

Warm the endpoint, then in a fresh chat: "Get me the tutor script for 418.1." → Claude returns the markdown (spell step reads hills → jets → tan → call, etc.). Pick and rehearse one lesson beforehand so the demo is smooth.

Security note

This server is unauthenticated for a dev demo: anyone with the URL can read lesson scripts, and the service-role key stays on the server (never sent to clients). Before anything beyond dev, put it behind OAuth (Claude custom connectors support an OAuth Client ID/Secret) or a gateway, and/or use a restricted key.


Phase 3: Transcript retrieval + Google auth

Two read-only PencilSpaces tools, and Google OAuth restricting the whole server (all three tools) to @yourdomain.org.

New tools

  • list_recordings(start_date, end_date) — recordings in a date range, each labeled with its lesson name (space title). Dedupes space lookups. Returns structured rows: recordingId, spaceId, lessonName, date, durationMinutes, hostUserIds.
  • get_transcript(recording_id, space_id=None) — the diarized transcript plus lesson name and host userId(s). status is one of ready | processing | empty | legacy | invalid_id | not_authorized | error. Segments are diarized by opaque userId (no name resolution — the eval skill corrects PS misattributions).

Flow: list_recordings → user picks one → get_transcript → the tutor-eval skill calls get_lesson_script. Pass spaceId from the list into get_transcript so it doesn't re-fetch the space.

Two auth layers

  • User → server: Google OAuth, gated to @yourdomain.org (below).
  • Server → PencilSpaces: PENCIL_SPACES_TOKEN Bearer secret. The token's account must be a host of the spaces, or the endpoints 401.

New environment variables

SERVER_BASE_URL (this server's public HTTPS URL), GOOGLE_OAUTH_CLIENT_ID, GOOGLE_OAUTH_CLIENT_SECRET, ALLOWED_EMAIL_DOMAIN (e.g. yourdomain.org), JWT_SIGNING_KEY (random, stable), PENCIL_API_BASE, PENCIL_SPACES_TOKEN.

Google Cloud OAuth setup

  1. In the yourdomain.org Google Workspace, create/select a Google Cloud project (must be under that org so "Internal" is available).
  2. APIs & Services → OAuth consent screen → Internal (this is the primary domain gate — only @yourdomain.org accounts can complete sign-in). Add scopes openid and .../auth/userinfo.email.
  3. APIs & Services → Credentials → Create credentials → OAuth client ID → Web application. Set:
    • Authorized JavaScript origins: https://your-service-name.onrender.com
    • Authorized redirect URI: https://your-service-name.onrender.com/auth/callback (must match exactly; /auth/callback is FastMCP's default).
  4. Copy the Client ID (…apps.googleusercontent.com) and Secret (GOCSPX-…) into Render env vars. The server allows Claude's callback (https://claude.ai/api/mcp/auth_callback) as a client redirect.

PencilSpaces

Set PENCIL_API_BASE (confirm the exact API host) and PENCIL_SPACES_TOKEN (a host account's Bearer token) as Render secrets. Read-only; never writes.

Connector re-connection

Turning on auth changes the existing connector: users must re-add / re-authorize it in Claude and sign in with Google. That's expected — it's the gate for handling real transcripts.

Testing with auth on

Use the MCP Inspector's OAuth flow, or the FastMCP client: Client("https://…onrender.com/mcp", auth="oauth"). First connect opens Google login.

Verify against a real recording (one-time)

The PencilSpaces response field names in pencilspaces.py follow the phase spec but were not verified against a live payload. On the first real recording, confirm:

  • the recordings list key (recordings) and fields (recordingId, spaceId, startingTime, duration);
  • transcript state markers (code/status == TRY_AGAIN_LATER; segments null vs []);
  • that the host userId from the space's hosts array matches the userId used in transcript segments (this overlap is what the role-tagging rests on). If the host never spoke or there are multiple hosts, note it — don't try to solve it now.

Privacy (by design)

userId pass-through, no name resolution — names never enter Claude. Real student transcripts: run evaluations in your own account and delete prototype conversations when done; no shared/retained transcript stores.

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选