MCP YouTube Transcript
An MCP server retrieving transcripts of YouTube videos
Description from the maker (original English)
Unified analytics MCP server for GA4, Mixpanel, and PostHog.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
ANTHROPIC_API_KEY, POSTHOG_API_KEY, POSTHOG_PROJECT_ID, GA4_CREDENTIALS_JSON, GA4_PROPERTY_ID, MIXPANEL_SERVICE_ACCOUNT_USERNAME, MIXPANEL_SERVICE_ACCOUNT_SECRET, MIXPANEL_PROJECT_IDValues marked secret are keys to your account. Never share them or paste them into a chat.
You need
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"analytics": {
"command": "uvx",
"args": [
"engageable"
],
"env": {
"ANTHROPIC_API_KEY": "your-value",
"POSTHOG_API_KEY": "your-value",
"POSTHOG_PROJECT_ID": "your-value",
"GA4_CREDENTIALS_JSON": "your-value",
"GA4_PROPERTY_ID": "your-value",
"MIXPANEL_SERVICE_ACCOUNT_USERNAME": "your-value",
"MIXPANEL_SERVICE_ACCOUNT_SECRET": "your-value",
"MIXPANEL_PROJECT_ID": "your-value"
}
}
}
}Run this in your terminal
claude mcp add analytics --env ANTHROPIC_API_KEY=your-value --env POSTHOG_API_KEY=your-value --env POSTHOG_PROJECT_ID=your-value --env GA4_CREDENTIALS_JSON=your-value --env GA4_PROPERTY_ID=your-value --env MIXPANEL_SERVICE_ACCOUNT_USERNAME=your-value --env MIXPANEL_SERVICE_ACCOUNT_SECRET=your-value --env MIXPANEL_PROJECT_ID=your-value -- uvx engageableFill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"analytics": {
"command": "uvx",
"args": [
"engageable"
],
"env": {
"ANTHROPIC_API_KEY": "your-value",
"POSTHOG_API_KEY": "your-value",
"POSTHOG_PROJECT_ID": "your-value",
"GA4_CREDENTIALS_JSON": "your-value",
"GA4_PROPERTY_ID": "your-value",
"MIXPANEL_SERVICE_ACCOUNT_USERNAME": "your-value",
"MIXPANEL_SERVICE_ACCOUNT_SECRET": "your-value",
"MIXPANEL_PROJECT_ID": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"analytics": {
"type": "stdio",
"command": "uvx",
"args": [
"engageable"
],
"env": {
"ANTHROPIC_API_KEY": "your-value",
"POSTHOG_API_KEY": "your-value",
"POSTHOG_PROJECT_ID": "your-value",
"GA4_CREDENTIALS_JSON": "your-value",
"GA4_PROPERTY_ID": "your-value",
"MIXPANEL_SERVICE_ACCOUNT_USERNAME": "your-value",
"MIXPANEL_SERVICE_ACCOUNT_SECRET": "your-value",
"MIXPANEL_PROJECT_ID": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
POSTHOG_PROJECT_ID envGA4_PROPERTY_ID envMIXPANEL_SERVICE_ACCOUNT_USERNAME envMIXPANEL_PROJECT_ID envThese settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026
The registry name was verified against the domain engageable.tech (the registry checks domain ownership)
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
You need to fill in: ANTHROPIC_API_KEY, POSTHOG_API_KEY, GA4_CREDENTIALS_JSON, MIXPANEL_SERVICE_ACCOUNT_SECRET
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.2.0) reached the registry 7 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
In the same category: MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
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.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
The open source analytics engine for AI agents.
One MCP server that connects to GA4, Mixpanel, PostHog, and more. 9 tools that replace per-platform integrations. Bring your own Anthropic key.
pip install engageable
export ANTHROPIC_API_KEY=sk-ant-... export POSTHOG_API_KEY=phc_... export POSTHOG_PROJECT_ID=12345 engageable-mcp
That's it. The MCP server is running on stdio. Connect it to Claude Desktop, Cursor, or any MCP client.
Add to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": { "engageable": { "command": "engageable-mcp", "args": [] } } }
Restart Claude Desktop. You'll see 9 analytics tools available.
ANTHROPIC_API_KEY=sk-ant-... docker compose -f docker-compose.mcp.yml up
Connects via SSE at http://localhost:8080/sse.
| Tool | What it does |
|---|---|
get_sources | List connected data sources |
configure_source | Connect a new data source (saves to ~/.engageable/credentials.json) |
analyze_trends | Time-series analysis with trend detection, change points, anomalies |
compare_segments | A/B tests, before/after, segment breakdown with statistical significance |
detect_anomalies | Find spikes, drops, and unusual patterns |
analyze_retention | Cohort retention curves (D1/D7/D30) |
analyze_funnel | Multi-step conversion funnel with drop-off rates |
analyze_cohort | Define and compare user cohorts |
ask | Natural language analytics questions (routes to other tools via LLM) |
| Source | Auth | What you need |
|---|---|---|
| PostHog | API key | POSTHOG_API_KEY + POSTHOG_PROJECT_ID |
| Mixpanel | Service account | MIXPANEL_SERVICE_ACCOUNT_USERNAME + MIXPANEL_SERVICE_ACCOUNT_SECRET + MIXPANEL_PROJECT_ID |
| Google Analytics 4 | Service account | GA4_CREDENTIALS_JSON (path or inline) + GA4_PROPERTY_ID |
Set these as environment variables, or use the configure_source tool to save them interactively to ~/.engageable/credentials.json. See credentials.example.json for the file format.
Engageable exposes analytics tools via the Model Context Protocol (MCP). Any MCP-compatible client (Claude, Cursor, VS Code, custom agents) can discover and call these tools.
Each tool is a self-contained pipeline: parse the request, fetch data from the right connector, run analysis, return results. The ask tool adds an LLM routing layer for natural language questions.
Responses use CSV for tabular data (50% fewer tokens than JSON) with a 1000-cell budget to keep context windows manageable.
MCP Client (Claude, Cursor, etc.)
│ ▼ ┌─────────────────────────────────────┐ │ MCP Server (stdio or SSE) │ │ - Dynamic tool registration │ │ - Credential injection │ │ - CSV response formatting │ ├─────────────────────────────────────┤ │ Composite Skills (agent-facing) │ │ analyze_trends, compare_segments, │ │ detect_anomalies, analyze_funnel, │ │ analyze_retention, analyze_cohort, │ │ ask, get_sources, configure_source │ ├─────────────────────────────────────┤ │ Connector Skills (internal) │ Analysis Skills (internal) │ ga4_query, posthog_query, │ trend_detection, significance, │ mixpanel_query, + metadata/probe │ cohort_retention, forecasting, │ │ bayesian_ab, correlation, ... └─────────────────────────────────────┘
MIT