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  3. Keypup Engineering Analytics
Keypup Engineering Analytics logo
Health: ActiveRecent health check succeeded.Last checked 9/9/2026, 12:31:50 AM

Keypup Engineering Analytics

User RatingsBe the first to rate and review this MCP server! Enrichment pendingWe haven’t run our AI enrichment pass on this listing yet, so the overview, use cases, and FAQ below may be sparse or missing. We work through the catalog over time β€” check back soon.
View Repository1 GitHub StarsTotal stargazers on GitHub for the source repository (1 stars).Visit Website

Generate answers & visualizations from your engineering data to track software development health.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Remote HTTP
Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "keypup-engineering-analytics-2": {
      "url": "https://img.shields.io/badge/VS_Code-Install_Server-0098FF?style=flat-square&logo=visualstudiocode&logoColor=white)](https://insiders.vscode.dev/redirect/mcp/install?name=keypup&config=%7B%22type%22%3A%20%22http%22%2C%20%22url%22%3A%20%22https%3A//hq.keypup.io/mcp%22%7D"
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing AlternativesπŸ’» More in Developer Tools

Documentation Overview

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.

Keypup MCP server demo

The Keypup MCP (Model Context Protocol) server plugs your Keypup engineering analytics directly into any MCP-compatible AI assistant β€” 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 β€” list the companies (teams) you belong to.
  • Explore datasets β€” browse the available datasets and the fields each one exposes.
  • Discover formula operators β€” list the functions and operators available when building metrics, dimensions, and filters.
  • Run reporting queries β€” execute aggregated queries against any dataset, with metrics, dimensions (group-by), filters, sorting, and pagination.
  • Generate a query from natural language β€” 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:

  1. List your companies
  2. Pick the relevant dataset
  3. Look up the fields it needs
  4. Build the query
  5. Run it
  6. Summarize the results

You only ask the question.

Tools

ToolDescription
list_companiesList the companies (teams) the authenticated user belongs to. Returns each company's id, name, created_at and updated_at. The id is required by most other tools.
list_datasetsList the datasets (facts) available for querying, each with its id, label and description.
list_dataset_fieldsList the fields available on a given dataset for a company. Supports filtering by source (NATIVE/CUSTOM) and a regex pattern matched against the field id, plus pagination.
list_formula_operatorsList the operators and functions usable in custom formulas. Supports filtering by scope (DIMENSION/METRIC) and a regex pattern, plus pagination. Set verbose: true for full per-operator documentation.
query_datasetRun an aggregated report against a dataset. Metrics, dimensions and filters are expressed as text-based formulas, with optional sorting, limit and offset.
generate_dataset_queryTurn a natural-language prompt into a structured query compatible with query_dataset.

Datasets

The reporting engine runs over the following datasets (facts):

  • ISSUES_PULL_REQUESTS β€” issues and pull requests.
  • ACTIVITY_EVENTS β€” transitions on issues/PRs (status changes, assignments, work logged, open/close/reopen).
  • COMMENTS β€” comments on issues, PRs and reviews.
  • COMMITS β€” commits attached to pull requests.
  • REVIEWS β€” 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

Code
https://hq.keypup.io/mcp

The server uses the streamable HTTP transport and supports two authentication methods:

  1. OAuth 2.1 (recommended) β€” the client registers itself dynamically and you authorize access through your browser. No token to copy or store.
  2. API token β€” a Keypup API token passed in the Authorization header. Use this when your client does not support OAuth dynamic client registration.

Option 1 β€” 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:

config.json
{
  "mcpServers": {
    "keypup": {
      "type": "http",
      "url": "https://hq.keypup.io/mcp"
    }
  }
}

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 β€” 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 β€” 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:

config.json
{
  "mcpServers": {
    "keypup": {
      "url": "https://hq.keypup.io/mcp",
      "headers": {
        "Authorization": "Bearer my_keypup_api_token"
      }
    }
  }
}

Notes:

  • Replace my_keypup_api_token with the token you generate (see below). Keep the Bearer prefix.
  • The server name (keypup) is arbitrary β€” 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.

  1. Go to Settings β†’ Account and open the API Token tab.
  2. Click Create token.
  3. Set a descriptive name (e.g., "MCP - Claude Desktop") and an expiration. Setting an expiration is strongly recommended.
  4. Select the token scopes. The minimal recommended scopes for the MCP server are:
    • Reports read (viz:reports:read) β€” required to explore datasets/fields and run reporting queries.
    • Companies read (hq:companies:read) β€” required to list the companies you belong to and resolve the company ID used in queries.
  5. Click Create. The token is shown only once and can be copied for one minute β€” 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 β€” queries are automatically scoped to the companies you are a member of.

Security

  • All Keypup MCP tools are read-only β€” 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

  • Using the MCP server (documentation)
  • MCP server product page
  • Using the API
  • Security FAQ

Read the full README β†’View source on GitHub β†’

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Reviews

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Frequently Asked Questions about Keypup Engineering Analytics

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "keypup-engineering-analytics": { "command": "npx", "args": ["-y", "Keypup Engineering Analytics"] } }

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Technical Specs & Signals

CategoryπŸ’»Developer Tools
More technical detailsExpand β–Ύ
TransportSSE (Remote)
RuntimeNode.js
Last updatedSep 7, 2026
Views0
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Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars1
GitHub Star CountTotal stargazers on GitHub representing community popularity (1 stars).
36Quality signal: Fair Β· 36/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools16/30
Adoption & activity1/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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