Vexa
Meeting bot and transcripts for Google Meet, Teams and Zoom. Live or after, speakers labelled.
Description from the maker (original English)
Surface customer & prospect context from Slack, email, transcripts and tickets in any MCP client.
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Works in Claude on the web, desktop and mobile:
https://backengine-prod.backengine.ai/mcpRun this in your terminal
claude mcp add --transport http backengine https://backengine-prod.backengine.ai/mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"backengine": {
"url": "https://backengine-prod.backengine.ai/mcp"
}
}
}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": {
"backengine": {
"type": "http",
"url": "https://backengine-prod.backengine.ai/mcp"
}
}
}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.
ChatGPT connects only to servers on the internet:
https://backengine-prod.backengine.ai/mcpMenu names can differ slightly by plan and over time.
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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
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It runs in the maker’s cloud. Connect over the internet with nothing to install, but what you send passes through the maker’s servers.
The GitHub repo last changed –, and the latest version (8.1.1) reached the registry 4 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.
In the same category: Vexa, emailmd, MCP WhatsApp Cloud
Servers in the same category from other makers, sorted by stars.
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Meeting bot and transcripts for Google Meet, Teams and Zoom. Live or after, speakers labelled.
Render markdown into email-safe HTML, lint drafts for deliverability problems, and preview emails.
MCP server for WhatsApp Cloud API (Meta) — messages, media, and templates via Graph API
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BackEngine MCP Server
The customer-context layer for your revenue team — available to Claude and any MCP client.
BackEngine is a multi-tenant SaaS platform that ingests all of an organization's customer and prospect communications — Slack threads, emails, call and meeting transcripts, and support tickets — and distills them into structured, queryable context. Raw conversations are processed into signals (categorized, attributed moments), sources (the underlying transcripts, emails, and tickets), and rolling project overviews, all isolated per tenant and scoped by role and access controls. The MCP server exposes this layer over the Model Context Protocol, so an LLM client can query customer signals, reconstruct context, prep for meetings, surface at-risk accounts, and draft grounded outreach from real conversation history — without leaving the chat.
The server is remote and speaks streamable HTTP at `https://backengine-prod.backengine.ai/mcp`. You'll need a BackEngine account; the server authenticates your session on connect.
{
"mcpServers": { "backengine": { "type": "streamable-http", "url": "https://backengine-prod.backengine.ai/mcp" } } }
For clients that don't yet support remote servers directly, proxy through mcp-remote:
{
"mcpServers": { "backengine": { "command": "npx", "args": ["-y", "mcp-remote", "https://backengine-prod.backengine.ai/mcp"] } } }
The core tools for querying customer and prospect context are listed below. The exact tool set is resolved per connection — additional tools (creating and updating records, and integration-specific actions for Jira, Zendesk, HubSpot, Salesforce, and Slack) become available based on your permissions and which integrations your workspace has connected.
| Tool | Description |
|---|---|
list_projects | List customers and prospects; filter by name, type, etc. |
get_project | Retrieve a customer or prospect, optionally with its overview. |
get_project_overview | Pre-computed rolling 12-week summary for a customer or prospect. |
list_signals | List signals (categorized moments); filter by project, role, and time. |
find_similar_signals | Semantic search across signals from a natural-language query. |
list_sources | List sources — transcripts, emails, Slack threads, and tickets. |
get_source | Retrieve a source's content (summary, verbatim, or metadata only). |
list_roles | List the perspective lenses (e.g. product, sales, CS) used to filter signals. |
find_contacts | Find contacts by name, email, job title, or project. |
list_signal_speakers | List who has been speaking across signals. |