A code observability MCP enabling dynamic code analysis based on OTEL/APM data to assist in code reviews, issues identification and fix, highlighting
If you want an AI assistant working directly with Digma, the digma mcp server is the bridge. A code observability MCP enabling dynamic code analysis based on OTEL/APM data to assist in code reviews, issues identification and fix, highlighting risky code etc.
A Model Context Protocol (MCP) server implementation for enabling agents to access observability insights using Digma for code observability and dynamic code analysis
Once connected, the assistant can call this tool directly:
Environment — TESTSetup follows the standard MCP pattern: clone or install the server, then register it in your client's configuration file and restart the client. The configuration snippets on this page cover Claude Desktop, Claude Code and Cursor.
Before the server will start you need to supply 2 environment variables: DIGMA_API_URL, DIGMA_API_TOKEN. Keep credentials in your client's env block or a secrets manager rather than committing them.
Developer-tool servers are usually the first ones people connect, because they turn "help me with this code" into an assistant that can actually read the repo and act on it. Digma sits in that group, and the shape of its toolset — Environment — tells you what it is really for. Worth comparing against the other developer tools servers in this directory before you commit to one, since several overlap in scope but differ sharply in setup cost and permissions.
| Tool | What it does |
|---|---|
| Environment | TEST |
{
"mcpServers": {
"digma": {
"url": "https://<DIGMA_API_URL>/mcp/DIGMA_API_TOKEN>/sse",
}
// ... other servers might be here ...
}
}Configuration as documented by the project. Restart the client after saving.
| Variable | Description | Required |
|---|---|---|
| DIGMA_API_URL | Endpoint or connection string the server talks to. | Yes |
| DIGMA_API_TOKEN | Credential the server authenticates with. | Yes |
Give your coding agent the full DevTools toolbox: traces, network, console, heap snapshots and Lighthouse.
Dashboards, Prometheus and Loki queries, incidents and alerts — observability by conversation.
Errors with full context — stack traces, issue triage and AI-powered root-cause analysis from Sentry's server.
Enables enhanced web research capabilities for large language models through intelligent search queuing and advanced content extraction.
Automates browser interactions and enables Large Language Models (LLMs) to interact with web pages through Playwright and Chrome DevTools Protocol
Guides tool usage by providing recommendations for MCP tools at each problem-solving stage.