Connecting to Hivel via MCP
Hivel MCP lets you bring your engineering metrics directly into the AI assistant you already use for work — Claude, Cursor, or any other MCP-compatible client.
Instead of logging into Hivel to pull up a dashboard, you can ask your AI assistant questions about your Git and Jira metrics in plain language, right from the tool where you're already writing code or planning work.
Hivel MCP is currently available for read-only queries against your Git and Jira metrics. It does not modify data in Hivel or your connected tools.
What Hivel MCP Helps With
Once connected, your AI client can query the same underlying data that powers your Hivel Cockpit dashboards — Git activity and Jira/PM metrics — directly inside your conversation.
Git-Related Metrics
Ask about cycle time, review time, PR volume, hotfix rate, and contributor activity without switching tabs.
Example questions:
What was the average review time for the Payments team last month?
Which repositories had the highest hotfix rate this quarter?
Show me the top 5 contributors by merged PRs in the last 30 days.
Why this is useful: You can pull a quick metric while you're already in Cursor reviewing code or in Claude planning a sprint retro, without breaking flow to open Hivel.
Project Management Metrics
Ask about sprint status, issue counts, and task distribution across your connected PM tools.
Example questions:
How many issues are still open in the current sprint for Team
List overdue tasks assigned to Person A
What percentage of this sprint's stories are done vs. in progress?
How to Connect
MCP connection details can be found under Configurations → Integrations → MCP. Reveal and copy the config for your client, follow the setup steps above, and you're ready to query Hivel from your own AI instance.
You'll need your MCP connection details. These include a server URL and a set of headers unique to your account, including your access token.
Yo can connect with Hivel agent via app.hivel.ai. Go to our integrations page and clivk on Hivel agent tab.
Claude Connector Settings
You can also connect using Claude's connector settings directly. In Claude, go to Settings → Connectors and add Hivel as a custom connector using the server URL from your Hivel MCP Connection tab. Use the code given below
Log in to Hivel, and use the Claude connector to connect Hivel to Claude.
Keep in mind that if you log out of Hivel, you'll need to repeat all of the steps above to reconnect.
A Note on Sessions
Hivel MCP access is tied to your active AI client session, not stored permanently on Hivel's side.
As long as you stay logged into your AI instance (Claude, Cursor, etc.), the connection stays live and you can keep asking questions.
If you log out of your AI client, access is lost, and you'll need to reconnect MCP by repeating the setup steps above.
This is expected behavior — it's the same session-based model most MCP integrations follow, and it keeps your credentials from persisting somewhere outside your control.
Example: Here is how data will appear on your screen
Prompt: Can you give me the commit count for all teams in Q2 and compare it with Q1
Prompt: Please provide details of Work Items closed by X Engineer in the current sprint
When to Use MCP vs. Cockpit vs. Lucy
Use MCP when you want to:
Ask about metrics without leaving your coding or planning tool
Get a quick answer mid-conversation with your AI assistant
Combine Hivel data with other context already in that conversation (e.g., "given this PR, what's our team's usual review time?")
Use Cockpit dashboards when you need:
Deep drilldowns or detailed PR-level analysis
Custom filters or precise metric investigation
Comprehensive sprint planning or historical trend analysis
Use Lucy when you want to:
Ask Hivel-native questions directly inside the Hivel platform without any setup
Example Prompts to Try
Git Metrics:
Compare cycle time and coding time for Team X over the last quarter
Which repos have the most unreviewed PRs right now?
Who are the top contributors in the @Checkout repository this month?
PM Tools:
Show me all blocked issues in the current sprint
Which team has the most overdue tasks in Jira?
How many stories are done vs. in progress this sprint?
For more information or assistance, please contact our support team at support@hivel.ai.
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