The Digma MCP Server uses a dynamic code analysis engine to leverage the data in your APM dashboards (Datadog, Grafana, NewRelic etc.) in order to assist the AI agent during code reviews, code and test generation, fix suggestions, etc. It enables the agent to drive performance improvements and cost reduction.
Features:
- Highlight risky code in the PR and provide impact visibility
- Assess the proposed code based on real performance requirements
- Highlight the code areas that would have the most impact when optimized
- Automatically identify and fix performance bottlenecks, ineffcient queries, scaling problems and other issues
Overview
Digma MCP Server
A Model Context Protocol (MCP) server implementation for enabling agents to access observability insights using Digma for code observability and dynamic code analysis
Key Features 🚀
- 🗣️ Observability-assisted code reviews: Check the PR branch for any issues discovered by pre-prod observability.
- 🔎 Find code inefficiencies with dynamic code analysis: Identify issues in the code/queries that are slowing the app down
- 🔭 Utilize code runtime usage data from distributed tracing: Check for breaking changes or generated relevant tests
Example prompts 💬
help me review the code changes in this branch by looking at related runtime issuesI want to improve the performance of this app. What are the three most severe issues I can fix?I'm making changes to this function, based on runtime data. What other services and code would be affected?Are there any new issues in this code based on the Staging environment?Which database queries have the most impact on the application performance?