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Model Context Protocol (MCP) enables AI agents, code editors, and chat apps like Claude, Cursor, Devin, Zed, VS Code, and GitHub Copilot to interact with external tools and data sources. AppSignal MCP gives those agents direct access to your monitoring data: errors, traces, logs, metrics, and more. AppSignal MCP is a public HTTP endpoint at https://appsignal.com/api/mcp. Agents connect to it directly, so there’s no server to install or run.

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Connect your AI tool

Pick your AI tool to set up AppSignal MCP:

Claude Code

Add the endpoint with claude mcp add.

Claude app

Add AppSignal as a custom connector.

Cursor

Add AppSignal to ~/.cursor/mcp.json.

Devin

Add AppSignal to Devin’s Cascade MCP marketplace.

Zed

Add AppSignal to Zed’s context_servers.

VS Code

Add AppSignal to .vscode/mcp.json.

GitHub Copilot CLI

Add the endpoint with copilot mcp add.

Gemini CLI

Add AppSignal to ~/.gemini/settings.json.

OpenAI Codex

Add the streamable HTTP endpoint in Codex.

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What you can access

AppSignal MCP exposes read and write access to your monitoring data across the following eight areas, plus get_more_tools for tool discovery and feedback. With an MCP token, you scope access to specific applications and choose which tools to expose. For example, you can scope a token to MyStore/production and expose get_app_resources, get_log_lines, and manage_log_line_action for a logs-focused agent. With OAuth, agents get the full AppSignal MCP toolset available to that sign-in. What you get back depends on what your apps send to AppSignal. If your app is not sending logs, get_log_lines will not return anything. AppSignal MCP is a gateway to data AppSignal already has, such as the following:
  • Error incidents (read + write): list and search exceptions, inspect stack traces, update state and severity, assign handlers, and add notes
  • Performance (read): rank slowest actions, pull traces, walk span trees, and inspect span attributes. Sample-based for standard Ruby and Elixir apps; OpenTelemetry traces for apps sending OTel data
  • Anomaly detection (read + write): browse alerts, list existing triggers, and create, update, or archive triggers
  • Check-ins (read + write): list cron and heartbeat monitors, inspect recent runs, and create, update, or delete monitors
  • Logging (read + write): query log lines with AppSignal’s expression syntax, and set up log ingestion rules: filter, trigger, and metrics actions. Useful for stitching together a customer journey across log sources, errors, and traces in one prompt — see reconstructing a customer journey
  • Metrics (read): discover metric categories (including host_metrics), list metric names and tags, and pull timeseries or aggregated values
  • Dashboards (read + write): create dashboards, and add or update chart visuals: timeseries line and area graphs, or Big Number tiles
  • App discovery (read): list your applications, environments, namespaces, users, notifiers, log sources, log views, log line actions, deploy markers, and uptime monitors
For the full list of tools, parameters, and example prompts, see the MCP Tool Reference. To set AppSignal MCP up in your editor or app, see Set up AppSignal MCP, and for logging, troubleshooting, and scope, see Using AppSignal MCP.