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Getting Started / Maple MCP server

Maple MCP server

Connect Claude, Cursor, and other AI agents to your Maple telemetry over the Model Context Protocol — endpoint, authentication, manifest, and the tools it exposes.

Maple ships a hosted Model Context Protocol (MCP) server, so an AI agent can investigate your production telemetry the way an engineer would: list services, search traces and logs, find and triage error issues, inspect dashboards, and create or update alert rules — all against your real data and scoped to your organisation.

Endpointhttps://api.maple.dev/mcp
TransportStreamable HTTP
Manifest (server.json)maple.dev/.well-known/mcp.json · api.maple.dev/.well-known/mcp.json
Registry namedev.maple/maple
AuthMaple API key as Bearer token, or OAuth 2.1

Connecting a client

Any MCP client that speaks Streamable HTTP can connect. Two authentication options:

API key. Create a key under Settings → API keys in the dashboard and pass it as a Bearer token:

{
  "mcpServers": {
    "maple": {
      "type": "http",
      "url": "https://api.maple.dev/mcp",
      "headers": { "Authorization": "Bearer maple_ak_…" }
    }
  }
}

For Claude Code: claude mcp add --transport http maple https://api.maple.dev/mcp --header "Authorization: Bearer maple_ak_…".

OAuth. Clients that support the MCP authorization flow need no key at all. The server advertises its protected-resource metadata at https://api.maple.dev/.well-known/oauth-protected-resource/mcp and its authorization server at https://api.maple.dev/.well-known/oauth-authorization-server; dynamic client registration and PKCE (S256) are supported, so a conforming client discovers everything from the endpoint URL alone and opens a browser sign-in on first use.

Requests are scoped to the organisation the key or the signed-in user belongs to. A user in several organisations selects one during the OAuth consent step.

What the server exposes

The tool set mirrors the Maple API and the dashboard. Broadly:

  • Discovery — list_services, service_map, get_service_top_operations, list_metrics, explore_attributes, describe_warehouse_tables
  • Traces and logs — search_traces, find_slow_traces, inspect_trace, inspect_span, search_logs, mine_log_patterns, query_data, run_sql
  • Errors and incidents — find_errors, list_error_issues, error_detail, list_error_issue_events, get_incident_timeline, diagnose_service, compare_periods, plus triage actions (claim_error_issue, transition_error_issue, set_issue_severity, comment_on_error_issue, propose_fix)
  • Sessions — search_sessions, get_session_traces, get_session_transcript
  • Dashboards — list_dashboards, get_dashboard, create_dashboard, add_dashboard_widget, update_dashboard_widget, inspect_chart_data, describe_dashboard_schema
  • Alerting — list_alert_rules, get_alert_rule, create_alert_rule, update_alert_rule, delete_alert_rule, list_alert_incidents, list_alert_checks
  • Setup — audit_setup, get_instrumentation_recommendations, register_agent

The server also ships prompts for common investigations (incident triage, latency analysis, debugging errors) and an instructions resource that explains Maple’s data model to the model. Call tools/list for the authoritative, always-current list — the exact set evolves with the product.