streamable-httpupdated 2mo ago
The customer-context layer for your revenue team — available to Claude and any MCP client.
backengine mcp 能做什么?
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
安装
把 backengine mcp 添加到你的客户端。选择你正在使用的那个。
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 个工具
backengine mcp 向已连接的智能体提供 10 个工具。
- 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.
评分
73 / 100
良好
- 文档22/25
- 维护22/25
- 可信度9/20
- 能力8/15
- 安装体验12/15
- 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
版本历史
| 版本 | 发布于 |
|---|---|
| 8.1.1最新 | 2026年7月10日 |
| 8.0.4 | 2026年6月30日 |
| 8.0.3 | 2026年6月30日 |
| 1.0.0 | 2026年6月29日 |