Tideways MCP Server

Tideways MCP Server – Conversational Performance Insights for PHP Applications

The Tideways MCP server bridges the gap between sophisticated application performance monitoring and AI‑driven conversational assistants. By exposing Tideways’ rich REST API through the Model Context Protocol, it allows tools like Claude Desktop or Cursor to retrieve real‑time metrics, trace data, and issue reports in a format that is natural for human conversation. Developers no longer need to manually parse API responses or build custom dashboards; the server translates raw telemetry into actionable insights that can be queried and discussed directly within an AI chat.

At its core, the server performs three key functions: it authenticates against Tideways using a secure API token, respects the platform’s rate limits with intelligent retry logic, and formats responses into concise, context‑aware messages. This ensures that assistants can ask questions such as “What’s the average response time for my recent deployments?” or “Show me the top three slowest database queries,” and receive clear, structured answers without exposing underlying technical details. The result is a smoother developer experience where performance data becomes part of everyday conversation, reducing context switching and accelerating debugging cycles.

Key capabilities include:

• Conversational Performance Insights – Raw metrics are transformed into natural language summaries, making it easy for non‑technical stakeholders to understand application health.
• Real‑time Querying – The server supports live data retrieval, allowing assistants to fetch up‑to‑date performance snapshots on demand.
• Issue Analysis – Errors, exceptions, and anomalous traces can be pulled and interpreted, helping teams pinpoint root causes quickly.
• Rate‑Limiting & Retry Logic – Built‑in compliance with Tideways’ API constraints protects against throttling while maintaining reliability.
• Robust Error Handling – User‑friendly messages guide developers when authentication fails or data is unavailable, reducing frustration.

Typical use cases span a range of development workflows. In agile sprints, teams can ask the AI to “summarize yesterday’s performance trend” or “highlight any new slow endpoints,” enabling rapid feedback loops. During code reviews, the assistant can surface performance regressions tied to recent commits. Operations teams benefit from conversational alerts that translate SLA breaches into actionable remediation steps. Because the server operates solely as an MCP endpoint, it seamlessly integrates with any AI assistant that supports the protocol, eliminating the need for bespoke plugins or manual API integration.

In summary, Tideways MCP Server empowers developers to embed deep performance intelligence into conversational AI. By turning complex telemetry into clear, context‑rich dialogue, it accelerates diagnostics, fosters collaboration across teams, and ensures that application health is always within reach of the assistant’s knowledge base.