
Keypup Engineering Analytics
io.keypup由 keypup.io 发布官方发布者v1.0.1更新于 Oct 25, 2026
Generate answers & visualizations from your engineering data to track software development health.
概览
Keypup 的远程 MCP 服务器让 AI 助手用自然语言查询你的工程分析数据,并生成关于交付、质量和团队工作量的只读报表。
- 可以做什么
- 列出你所属的公司(团队),浏览可用数据集及其字段,包括自定义字段和带说明的公式运算符。对议题、拉取请求、活动事件、评论、提交和评审运行聚合报表查询,支持指标、分组维度、筛选、排序和分页。把自然语言问题转换为结构化查询并执行。汇总合并吞吐量、周期时间、评审周转时间、缺陷开启与关闭比例、评审人工作量等结果。
- 适用场景
- 当你想不写查询语句就了解软件交付、代码评审和团队工作量时使用;也适合让助手代为起草并运行 Keypup 报表。适合工程管理者和团队负责人以对话方式探索 Keypup 数据,而不是直接使用 GraphQL API。
- 运行要求
- 远程 streamable HTTP 端点,无需本地安装包。必须认证:推荐使用支持动态客户端注册的 OAuth 2.1(浏览器登录),或在 Authorization 请求头中以 Bearer 前缀传入 Keypup API 令牌。建议令牌包含 viz:reports:read 和 hq:companies:read 权限范围。需要一个属于相关公司的 Keypup 账户。
安装
在 SourceWeft 中
- 打开 控制台中的 Keypup Engineering Analytics,将其添加到工作区。
- 连接 所需的 凭据。它们会被私密存储,绝不会在公开页面上展示。
- 为需要使用其工具的对话启用该服务。
Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。
交给智能体安装
把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。
阅读 https://sourceweft.com/mcp/io.keypup%2Fengineering-analytics/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。其他 MCP 客户端
把它添加到你客户端的 mcpServers 配置中。 客户端会在首次连接时完成 OAuth 登录。
{
"mcpServers": {
"keypup-engineering-analytics": {
"type": "http",
"url": "https://hq.keypup.io/mcp"
}
}
}README
Keypup MCP Server
[Install in VS Code] [Install in Cursor] [Add to Kiro]
Ask your Keypup engineering data in plain language to track delivery, quality and team workload.
The Keypup MCP (Model Context Protocol) server plugs your Keypup engineering analytics directly into any MCP-compatible AI assistant — Claude, Cursor, Kiro, ChatGPT Desktop, Gemini CLI, VS Code, and others.
Once connected, you ask questions about your engineering activity in plain language and the AI builds and runs the underlying reporting queries for you. No query language to learn, no code to write.
Unlike the GraphQL API, which is designed for developers writing application code, the MCP server is designed to be driven conversationally by an AI on your behalf.
Beta: The Keypup MCP server is currently in beta. The exposed capabilities are continuously expanded during this phase. Feedback and use cases are welcome via the in-app chat.
What it can do
The server exposes a focused set of read-only tools that let an AI explore and query your Keypup data:
- Discover your companies — list the companies (teams) you belong to.
- Explore datasets — browse the available datasets and the fields each one exposes.
- Discover formula operators — list the functions and operators available when building metrics, dimensions, and filters.
- Run reporting queries — execute aggregated queries against any dataset, with metrics, dimensions (group-by), filters, sorting, and pagination.
- Generate a query from natural language — turn a plain-language request into a ready-to-run structured query that the AI can then execute.
The AI orchestrates these tools automatically. A typical flow:
- List your companies
- Pick the relevant dataset
- Look up the fields it needs
- Build the query
- Run it
- Summarize the results
You only ask the question.
Tools
Datasets
The reporting engine runs over the following datasets (facts):
ISSUES_PULL_REQUESTS— issues and pull requests.ACTIVITY_EVENTS— transitions on issues/PRs (status changes, assignments, work logged, open/close/reopen).COMMENTS— comments on issues, PRs and reviews.COMMITS— commits attached to pull requests.REVIEWS— pull request reviews.
Example questions
Delivery & throughput
- "How many pull requests did we merge each month over the last 6 months?"
- "What's our weekly issue closing rate this quarter?"
- "How many commits were made per author last month?"
Cycle time & performance
- "What's the average time between PR creation and merge over the last 12 weeks?"
- "Show me the review turnaround time trend for the last 3 months."
- "Which repositories have the slowest cycle time?"
Quality & process
- "How many bugs were raised vs. closed each week this quarter?"
- "What proportion of our pull requests resolve at least one issue?"
- "How many PRs were merged without a review?"
Workload & collaboration
- "Who are our most active reviewers this month?"
- "How is work distributed across the team right now?"
- "How many comments do our pull requests receive on average?"
Open-ended exploration
- "Summarize our engineering activity over the last month."
- "Compare open vs. closed issues over time."
- "What labels are most common on our issues?"
You can refine iteratively: "now break that down by repository", "restrict it to the backend team", and so on.
Setup
Endpoint
The server uses the streamable HTTP transport and supports two authentication methods:
- OAuth 2.1 (recommended) — the client registers itself dynamically and you authorize access through your browser. No token to copy or store.
- API token — a Keypup API token passed in the
Authorizationheader. Use this when your client does not support OAuth dynamic client registration.
Option 1 — OAuth (recommended)
If your client supports OAuth 2.1 with dynamic client registration (e.g. via a Client ID Metadata Document), point it at the endpoint with no credentials:
On first connection the client opens a browser window to sign in to Keypup and
authorize access. There is no token to generate, copy, or rotate — this is the
configuration shipped in this repo's .mcp.json.
If your client does not open an authorization prompt (or fails to register), it likely does not support dynamic client registration yet. Use the API token method below instead.
Option 2 — API token
For clients without OAuth dynamic client registration support, add a keypup
server entry pointing at the endpoint, with your API token in the Authorization
header:
Notes:
- Replace
my_keypup_api_tokenwith the token you generate (see below). Keep theBearerprefix. - The server name (
keypup) is arbitrary — name it however you like.
Once saved, restart or reconnect the MCP server in your client. The Keypup tools should appear in the client's tool list, and you can start asking questions.
Generating an API token
Only needed for Option 2 (API token). If you authenticate via OAuth, skip this section.
The MCP server authenticates with the same API tokens used by the GraphQL API.
- Go to Settings → Account and open the API Token tab.
- Click Create token.
- Set a descriptive name (e.g., "MCP - Claude Desktop") and an expiration. Setting an expiration is strongly recommended.
- Select the token scopes. The minimal recommended scopes for the MCP server are:
- Reports read (
viz:reports:read) — required to explore datasets/fields and run reporting queries. - Companies read (
hq:companies:read) — required to list the companies you belong to and resolve the company ID used in queries.
- Reports read (
- Click Create. The token is shown only once and can be copied for one minute — copy it into your MCP client configuration right away.
Following the principle of least privilege, grant only the scopes you need. The two scopes above are enough to use the full analytics capabilities of the MCP server.
The token grants the same level of data access you already have in the Keypup user interface — queries are automatically scoped to the companies you are a member of.
Security
- All Keypup MCP tools are read-only — they never modify your data.
- Queries are automatically scoped to the companies you belong to (data isolation).
- Treat your API token like a password. Anyone holding it can query your Keypup data within the granted scopes.
- Prefer short-lived tokens with an expiration, and rotate them periodically.
- Keep tokens out of shared or version-controlled files. Store them in your MCP client's local configuration only.
Resources
来源:README.md,提交 03c8bc2
工具
0版本历史
1- v1.0.1最新Sep 16, 2026
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