music_library/backlog/docs/doc-6 - Programmatic-Access-to-Production-Logs.md

id, title, type, created_date, updated_date

id	title	type	created_date	updated_date
doc-6	Programmatic Access to Production Logs	other	2026-05-04 06:43	2026-05-04 06:55

Implementation Route Analysis: Programmatic Access to Production Logs

Decision: Route B — Pi Tool via pi.registerTool() ✓ SELECTED

Problem Statement

The /prod-logs pi extension (.pi/extensions/prod-logs/index.ts) provides an interactive TUI for viewing production logs from Coolify. The fetchLogs() function hits {host}/api/v1/applications/{app_uuid}/logs using a Bearer token. However, this is strictly user-interactive — the LLM cannot programmatically fetch logs.

The LLM needs a tool it can call to retrieve production logs directly into its context for analysis, debugging, and troubleshooting.

Current Architecture Context

• pi extensions are TypeScript modules in .pi/extensions/ that can register:
  • pi.registerCommand() — User-facing slash commands with interactive TUIs (what /prod-logs uses today)
  • pi.registerTool() — Tools callable by the LLM during its agent loop (same mechanism as read, write, bash, etc.)
• The existing fetchLogs() and resolveVar() are at module scope in the extension, so they're naturally shareable between the command handler and a new tool handler.
• Tidewave MCP provides Elixir-side tools via a separate MCP protocol channel.

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Route A: Tidewave MCP Tool (Elixir-side)

Description

Add a new MCP tool get_production_logs to Tidewave that calls the Coolify API from Elixir using Req.

Pros

• Architecturally consistent with existing MCP tools
• Req is battle-tested in this codebase
• Accessible by any MCP client

Cons

• Must forward Coolify env vars to Phoenix app runtime
• Rewrites the API call in Elixir (no code reuse from existing fetchLogs)
• New Elixir module to maintain

Verdict

Rejected in favor of Route B. The pi tool approach is simpler, reuses existing code and credentials directly, and keeps the change contained to a single file.

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Route B: Pi Tool via pi.registerTool() ✓ SELECTED

Description

Add a fetch_production_logs tool registration to the existing prod-logs extension. The tool is called by the LLM directly (just like read, bash, etc.), fetches logs via the existing fetchLogs() function, and returns text content to the LLM.

Pros

• Direct code reuse: Same fetchLogs() function, same resolveVar() helper, same env vars
• No infrastructure changes: No new Elixir modules, no credential forwarding, no config changes
• First-class LLM tool: The LLM calls it natively during its agent loop, the result flows through the same context pipeline as any other tool result
• Minimal change: ~50 lines added to the existing extension file
• No external dependencies: typebox is already available as a pi built-in import

Cons

• pi-only (not accessible from other MCP clients — irrelevant for this use case)
• Tool definition consumes a small amount of LLM context window space (same as any tool)

Architecture Impact

• Modified file: .pi/extensions/prod-logs/index.ts (add tool registration, ~50 lines)
• No changes: No Elixir modules, no config, no schemas, no routes, no UI

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Route C: Both — Deferred

Not needed. Route B satisfies the objective alone.