The customer-context layer for your revenue team — available to Claude and any MCP client.
## 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](https://modelcontextprotocol.io), 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 ```json { "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`](https://www.npmjs.com/package/mcp-remote): ```json { "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