MCP YouTube Transcript
An MCP server retrieving transcripts of YouTube videos
作者提供的说明(英文原文)
UX research platform: manage studies, browse templates, read responses and analytics.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
适用于网页版、桌面版和手机版 Claude:
https://francolabs.vercel.app/mcp在终端中运行这条命令
claude mcp add --transport http francolabs https://francolabs.vercel.app/mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"francolabs": {
"url": "https://francolabs.vercel.app/mcp"
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"francolabs": {
"type": "http",
"url": "https://francolabs.vercel.app/mcp"
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
ChatGPT 只能连接互联网上的服务器:
https://francolabs.vercel.app/mcp菜单名称可能因套餐和版本不同而略有差异。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月8日
注册名称已通过 GitHub 账户 glauberfrancodesign 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
尚未检查;我们会轮流检查各个端点
尚未检查;我们会轮流检查各个端点
尚未检查;我们会在检查端点时读取工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在作者的云端运行。通过互联网连接,无需安装,但你发送的内容会经过作者的服务器。
GitHub 仓库最后更新于–,最新版本(1.0.0)于5个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。
同一分类中有:MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
An MCP server retrieving transcripts of YouTube videos
GA4 MCP server for AI agents: schema discovery, server-side aggregation, analysis-ready defaults.
AI video summarizer: summarize and transcribe YouTube, Bilibili, TikTok and podcast videos.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
Connect AI assistants to FrancoLabs — a UX research platform — over the Model Context Protocol. Let Claude, ChatGPT and other MCP clients create and manage studies, browse templates, read participant responses and analytics, run AI-grounded analysis, and turn insights into product opportunities on your behalf.
https://francolabs.vercel.app/mcp2025-06-18)io.github.glauberfrancodesign/francolabsSettings → Connectors → *Add custom connector* → URL:
https://francolabs.vercel.app/mcp
Complete the OAuth consent screen — you choose exactly which scopes to grant and can toggle read-only access.
Enable Developer Mode, then Settings → Connectors → *Add* → same URL. Authenticate via the OAuth flow.
Generate a Personal Access Token in Settings → Integrations, then:
claude mcp add --transport http francolabs \
"https://francolabs.vercel.app/mcp" \ --header "Authorization: Bearer "
A tool listed with two scopes needs both. AI marks tools that call a language model and use AI credits; the model only sees the deterministic digest and curated insights, with e-mail addresses and phone numbers masked first.
| Tool | Scope | Description |
|---|---|---|
list_question_types | templates:read | Question/block types with the exact settings shape and a valid example |
list_templates | templates:read | Study templates, optionally by category |
list_workspaces | projects:read | Workspaces (teams) you belong to and your role in each |
list_projects | projects:read | Your projects, optionally by status |
get_project | projects:read | A single project by id |
get_plan | projects:read | The workspace plan and current usage: limits, what is enforced now, grants and when extended access ends, and the per-person AI-create cap |
create_project | projects:write | Create a project (optionally in a specific workspace) |
| Tool | Scope | Description |
|---|---|---|
list_studies | studies:read | Studies, filtered by status and/or project |
get_study | studies:read | A full study with blocks and settings |
create_study | studies:write | Create a Draft study; blocks are validated against list_question_types |
update_study | studies:write | Update title, blocks, project; settings is a partial update |
set_study_status | studies:write | Launch a Draft, pause, resume a Paused study, or complete it |
delete_study | studies:write | Permanently delete a study and its responses |
generate_study_from_objective | studies:read | AI — turn a research objective into a typed study skeleton |
review_study_quality | studies:read | AI — survey-design review with a quality score per block |
| Tool | Scope | Description |
|---|---|---|
list_responses | responses:read | Raw participant responses, newest first — may contain personal data written by respondents; pass redact: true to mask e-mails and phones |
get_study_analytics | responses:read | Aggregated KPIs: responses, completion, duration, NPS, distributions |
get_study_digest | responses:read | Deterministic, PII-free statistical digest for every question type |
run_universal_analysis | responses:read + studies:write | AI — run/refresh the full analysis (replaces non-pinned AI insights) |
analysis_chat | responses:read | AI — ask a question grounded in the digest and cached analysis |
get_insights | responses:read | Curated insight cards, pinned first |
upsert_insight | responses:read + studies:write | Create or edit a curated insight card |
rate_insight | responses:read + studies:write | Record 👍/👎 feedback on an insight |
suggest_tags | responses:read + studies:write | AI — tag insights with a consistent product taxonomy |
set_insight_tags | responses:read + studies:write | Replace the tags of one insight |
research_memory_query | responses:read + studies:write | AI — cross-study question answered from past curated insights |
| Tool | Scope | Description |
|---|---|---|
list_opportunities | responses:read | Product opportunities distilled for a study |
create_opportunity_from_insights | responses:read + studies:write | AI — distill insights into draft opportunities |
suggest_next_research_steps | responses:read | AI — 3–5 follow-up studies that de-risk open opportunities |
generate_decision_packet | responses:read + studies:write | AI — stakeholder-ready decision package (Markdown) |
list_decision_packets | responses:read | Decision packages already generated for a study |
export_opportunity | responses:read + studies:write | Export an opportunity to Linear as an issue — internal users only |
list_external_task_links | responses:read | Linear issues already created from a study's opportunities |
| Tool | Scope | Description |
|---|---|---|
list_contacts | contacts:read | Respondent contacts of the workspace — personal data (e-mail, name, locale/country, research consent, tags, response counts) |
get_contact | contacts:read | One contact with the studies they answered — personal data |
tag_contacts | contacts:write | Add/remove tags on contacts to segment respondents — never put sensitive information in tags |
create_project and create_study write into a workspace — pass workspaceId (see list_workspaces), or omit it to use your oldest workspace by default. Write tools also require an editor role (owner, admin or member) in the study's workspace; viewers can only read.
Two resources are also exposed: francolabs://templates and francolabs://question-types.
templates:read · projects:read · projects:write · studies:read · studies:write · responses:read · contacts:read · contacts:write
`contacts:read` and `contacts:write` give access to personal data of your respondents (e-mail, name, locale/country, research consent, tags and response history). They are opt-in: the consent screen and the Read-only token preset leave them unchecked; grant them only to assistants that need your contacts base. responses:read returns raw answers, which can also contain personal data typed by respondents.
Tools you didn't grant are hidden from tools/list. A read-only grant blocks every write tool server-side, regardless of scopes.
This repository mirrors the server's source for transparency. The server runs as a Supabase Edge Function (src/mcp, src/mcp-oauth, src/_shared).
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