MCP Server - monocle.sh

Monocle Studio includes a built-in MCP server. This lets AI coding assistants like Claude Code, Cursor, or Codex query your local telemetry data directly — find errors, inspect traces, and debug performance issues without leaving your editor.

Setup

The MCP server is available at http://localhost:4200/mcp when Monocle Studio is running. If you also want your agents to know about Monocle Studio and how to use it, run:

monocle studio install-agents

Claude Code
Cursor
Codex
Other

pnpm dlx add-mcp http://localhost:4200/mcp -n monocle-studio -a claude-code

pnpm dlx add-mcp http://localhost:4200/mcp -n monocle-studio -a cursor

pnpm dlx add-mcp http://localhost:4200/mcp -n monocle-studio -a codex

add-mcp supports 15+ clients. Run pnpm dlx add-mcp --all to install for all detected clients, or configure manually:

{
  "mcpServers": {
    "monocle-studio": {
      "type": "url",
      "url": "http://localhost:4200/mcp"
    }
  }
}

Available tools

Tool	Description
`list_traces`	List recent traces with entry point, duration, and status. Supports filtering by trace ID.
`get_trace`	Get the complete span waterfall for a trace — parent/child relationships, durations, attributes.
`list_logs`	List logs filtered by severity, search text, or trace ID.
`list_errors`	List exceptions with type, message, stacktrace, and trace context.
`list_queries`	List database queries with SQL statement, duration, and system. Filter by database type.
`clear_data`	Clear all collected telemetry for a fresh debugging session.

Examples

Once connected, you can ask your AI assistant things like:

“What errors happened in the last few requests?”
“Show me the trace for the slow /api/users endpoint”
“Find all database queries slower than 200ms”
“What’s the overall health of my app right now?”
“Clear all data and start a fresh debugging session”

The assistant will call the appropriate MCP tools, query Monocle Studio, and give you the answer in context.