---
title: Getting Started with Software Delivery MCP Tools
description: >-
  Connect AI agents to your CI Visibility and Test Optimization data using the
  Datadog MCP Server.
breadcrumbs: Docs > Getting Started > Getting Started with Software Delivery MCP Tools
---

# Getting Started with Software Delivery MCP Tools

{% callout %}
# Important note for users on the following Datadog sites: app.ddog-gov.com

{% alert level="danger" %}
This product is not supported for your selected [Datadog site](https://docs.datadoghq.com/getting_started/site.md). ().
{% /alert %}

{% /callout %}

## Overview{% #overview %}

The [Datadog MCP Server](https://docs.datadoghq.com/bits_ai/mcp_server/setup.md) enables AI agents to access your Software Delivery data through the [Model Context Protocol (MCP)](https://modelcontextprotocol.io/). The `software-delivery` toolset provides tools for interacting with [CI Visibility](https://docs.datadoghq.com/continuous_integration.md) and [Test Optimization](https://docs.datadoghq.com/tests.md) directly from AI-powered clients like Cursor, Claude Code, or OpenAI Codex.

## Use cases{% #use-cases %}

The Software Delivery MCP tools unlock AI-assisted workflows for:

- **Debugging pipeline failures**: Ask your AI agent to find recent pipeline failures, analyze error logs, and suggest fixes.
- **Identifying flaky tests**: Query for flaky tests in your repository and get prioritized recommendations for which to fix first.
- **Analyzing CI performance**: Get aggregated statistics on pipeline durations, failure rates, and trends over time.
- **Triaging test failures**: Understand which tests are failing, their ownership, and historical patterns.
- **Reviewing code coverage**: Get coverage summaries for branches or commits, including patch coverage and breakdowns by service or code owner.

## Available tools{% #available-tools %}

The `software-delivery` toolset includes the following tools:

{% dl %}

{% dt %}
`search_datadog_ci_pipeline_events`
{% /dt %}

{% dd %}
Search CI pipeline events with filters and get details on failures, durations, and statuses.
{% /dd %}

{% dt %}
`aggregate_datadog_ci_pipeline_events`
{% /dt %}

{% dd %}
Aggregate CI pipeline events for statistics like average durations, failure counts, and percentile analysis.
{% /dd %}

{% dt %}
`get_datadog_flaky_tests`
{% /dt %}

{% dd %}
Find flaky tests with triage details including failure rate, category, owners, and CI impact.
{% /dd %}

{% dt %}
`aggregate_datadog_test_events`
{% /dt %}

{% dd %}
Aggregate test events to analyze reliability and performance trends.
{% /dd %}

{% dt %}
`search_datadog_test_events`
{% /dt %}

{% dd %}
Search test events with filters and get details on them.
{% /dd %}

{% dt %}
`get_datadog_code_coverage_branch_summary`
{% /dt %}

{% dd %}
Fetch aggregated code coverage summary metrics for a repository branch, including total coverage, patch coverage, and service/codeowner breakdowns.
{% /dd %}

{% dt %}
`get_datadog_code_coverage_commit_summary`
{% /dt %}

{% dd %}
Fetch aggregated code coverage summary metrics for a repository commit, including total coverage, patch coverage, and service/codeowner breakdowns.
{% /dd %}

{% /dl %}

## Example prompts{% #example-prompts %}

After you are connected, try prompts like:

- Show me all the pipelines for my commit `58b1488`.
- What's causing the `integration-test` job to fail on my branch?
- Find active flaky tests for the checkout service sorted by failure rate.
- How many failed pipelines have there been in the last 2 weeks?
- Show me the 95th percentile of pipeline duration grouped by pipeline name.
- What's the code coverage on the `main` branch for `github.com/my-org/my-repo`?
- Show me coverage metrics for commit `abc123abc123abc123abc123abc123abc123abcd`.

## Setup{% #setup %}

To use the Software Delivery tools, connect to the Datadog MCP Server with the `software-delivery` toolset enabled. Add the `toolsets` query parameter to the endpoint URL for your [Datadog site](https://docs.datadoghq.com/getting_started/site.md):

```text
https://mcp./api/unstable/mcp-server/mcp?toolsets=core,software-delivery
```

For full setup instructions including client configuration for Cursor, Claude Code, VS Code, and other AI clients, see [Set Up the Datadog MCP Server](https://docs.datadoghq.com/bits_ai/mcp_server/setup.md).

## Further reading{% #further-reading %}

- [Datadog MCP Server Setup](https://docs.datadoghq.com/bits_ai/mcp_server/setup.md)
- [CI Visibility](https://docs.datadoghq.com/continuous_integration.md)
- [Test Optimization](https://docs.datadoghq.com/tests.md)
- [Connect your AI agents to Datadog tools and context using the Datadog MCP Server](https://www.datadoghq.com/blog/datadog-remote-mcp-server/)