A Go-based server implementation for the Model Context Protocol (MCP) with Grafana Tempo integration.
A Go-based server implementation for the Model Context Protocol (MCP) with Grafana Tempo integration. The gigapipe traces mcp mcp server wraps that behind the Model Context Protocol, so an assistant can use it through 1 defined tool rather than through you.
This MCP server allows AI assistants to query and analyze distributed tracing data from Grafana Tempo. It follows the Model Context Protocol to provide tool definitions that can be used by compatible AI clients such as Claude Desktop.
Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client. The configuration blocks on this page cover the common clients.
Everything the assistant can do here goes through one of these:
Prerequisites — The Prerequisites tool exposed by this serverYou will need one environment variable: TEMPO_URL. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.
This sits in the monitoring and observability group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. Gigapipe Traces MCP's toolset — Prerequisites — is a fair guide to whether it matches your workflow. It is maintained by gigapipehq; worth a glance at recent repository activity before you build anything load-bearing on it.
We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.
| Tool | What it does |
|---|---|
| Prerequisites | The Prerequisites tool exposed by this server. |
{
"mcpServers": {
"temposerver": {
"command": "path/to/tempo-mcp-server",
"args": [],
"env": {
"TEMPO_URL": "http://localhost:3200"
},
"disabled": false,
"autoApprove": ["tempo_query"]
}
}
}Configuration as documented by the project. Restart the client after saving.
| Variable | Description | Required |
|---|---|---|
| TEMPO_URL | Endpoint or connection string the server talks to. | 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.