dora_metrics_deep_dive

Analyzes DORA metrics (Deployment Frequency, Mean Time to Recovery, Change Failure Rate) with deep correlation to code review patterns. Designed for CTOs to identify bottlenecks in software delivery pipelines. Inputs include GitHub repository identifiers and optional time ranges. Outputs structur...

SERVERMcp Knowledge SOURCEhttps://mcp.gapup.io
Low RISK CLASS
Category Read
Parameters 51 required
Recommended Allowedsee the rule below
Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-getgapup-mcp-knowledge/dora-metrics-deep-dive.md

What dora_metrics_deep_dive does on Mcp Knowledge

AI agents call dora_metrics_deep_dive to retrieve information from Mcp Knowledge without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

ParameterTypeRequiredDescription
repo string Yes GitHub repository in format 'owner/repo'
async boolean If true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client ti
since string Start date for analysis (ISO 8601)
until string End date for analysis (ISO 8601)
branch string Branch name to analyze (default: main)

Parameters from the server's own tool schema.

Why dora_metrics_deep_dive is rated Low

The tool reads and analyzes existing data from GitHub repositories (deployment frequency, MTTR, change failure rate, code review patterns) and produces structured analytical output. There is no indication it modifies, executes, or deletes any data.

From the tool's definition Analyzes DORA metrics...Outputs structured metrics with trend analysis and code review depth insights. Inputs include GitHub repository identifiers and optional time ranges.

Questions about dora_metrics_deep_dive

What does the dora_metrics_deep_dive tool do? +

Analyzes DORA metrics (Deployment Frequency, Mean Time to Recovery, Change Failure Rate) with deep correlation to code review patterns. Designed for CTOs to identify bottlenecks in software delivery pipelines. Inputs include GitHub repository identifiers and optional time ranges. Outputs structured metrics with trend analysis and code review depth insights. It is categorised as a Read tool in the Mcp Knowledge MCP Server, which means it retrieves data without modifying state.

What parameters does dora_metrics_deep_dive accept? +

dora_metrics_deep_dive accepts 5 parameters: repo, async, since, until, branch. Required: repo. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on dora_metrics_deep_dive? +

Register the Mcp Knowledge MCP server in PolicyLayer and add a rule for dora_metrics_deep_dive: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Mcp Knowledge. Nothing to install.

What risk level is dora_metrics_deep_dive? +

dora_metrics_deep_dive is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit dora_metrics_deep_dive? +

Yes. Add a rate_limit block to the dora_metrics_deep_dive rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block dora_metrics_deep_dive completely? +

Set action: deny in the PolicyLayer policy for dora_metrics_deep_dive. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides dora_metrics_deep_dive? +

dora_metrics_deep_dive is provided by the Mcp Knowledge MCP server (https://mcp.gapup.io). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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