streamable-httpupdated 2mo ago
The customer-context layer for your revenue team — available to Claude and any MCP client.
O que dá para fazer com backengine mcp?
What is BackEngine?
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.
Connecting
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.
Clients with native remote MCP support
{
"mcpServers": {
"backengine": {
"type": "streamable-http",
"url": "https://backengine-prod.backengine.ai/mcp"
}
}
}
Clients that require a stdio bridge
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"]
}
}
}
Tools
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. |
Links
- Website: https://backengine.ai
- MCP endpoint: https://backengine-prod.backengine.ai/mcp
- Model Context Protocol: https://modelcontextprotocol.io
Instalação
Adicione backengine mcp ao seu cliente. Escolha o que você usa.
claude mcp add --transport http backengine-mcp https://backengine-prod.backengine.ai/mcpcodex mcp add backengine-mcp --url https://backengine-prod.backengine.ai/mcp{
"mcpServers": {
"backengine-mcp": {
"url": "https://backengine-prod.backengine.ai/mcp"
}
}
}Add to `~/.cursor/mcp.json`, or `.cursor/mcp.json` for a single project.
{
"servers": {
"backengine-mcp": {
"type": "http",
"url": "https://backengine-prod.backengine.ai/mcp"
}
}
}Add to `.vscode/mcp.json` in your workspace.
{
"mcpServers": {
"backengine-mcp": {
"url": "https://backengine-prod.backengine.ai/mcp"
}
}
}Add to `claude_desktop_config.json`, then restart Claude Desktop.
{
"mcpServers": {
"backengine-mcp": {
"serverUrl": "https://backengine-prod.backengine.ai/mcp"
}
}
}Add to `~/.codeium/windsurf/mcp_config.json`.
10 ferramentas
backengine mcp expõe 10 ferramentas a um agente conectado.
- 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.
Pontuação
73 / 100
Boa
- Documentação22/25
- Manutenção22/25
- Confiança9/20
- Capacidade8/15
- Instalação12/15
- Documents what it does and how to connect
- Has a resolvable package or endpoint
- Exposes at least one tool, prompt or resource
- README has substantive content
- Includes a code example
- Documents its configuration
- Mentions credentials or security posture
- Last commit 53 days ago
- Has a release history
- Repository is not archived
- No licence detected
- Namespace verified in the official MCP registry
- Claimed by its owner
- Published under an organisation
- 10 tool(s) documented
- Provides prompt templates
- Provides resources
- 6 documented install method(s)
- Published to a package registry
- Offers a hosted endpoint — no local install
Histórico de versões
| Versões | Publicada |
|---|---|
| 8.1.1Mais recente | 10 de jul. de 2026 |
| 8.0.4 | 30 de jun. de 2026 |
| 8.0.3 | 30 de jun. de 2026 |
| 1.0.0 | 29 de jun. de 2026 |