Weave MCP Server + Client Linked Traces:

Created By
zbirenbauma year ago
Overview

What is Weave MCP Server + Client Linked Traces?

Weave MCP Server + Client Linked Traces is a project that enables end-to-end tracing for applications using Anthropic's Model Context Protocol (MCP). It allows developers to track requests across client-server boundaries for better observability and debugging.

How to use Weave MCP?

To use Weave MCP, set up your environment by copying the example environment file, installing dependencies, and running the client to export traces. Follow the instructions in the repository to configure your API keys and run the client application.

Key features of Weave MCP?

  • End-to-end tracing of requests between client and server.
  • Integration with OpenTelemetry for context propagation.
  • Support for multiple programming languages.
  • Ability to observe latency and debug issues across service boundaries.

Use cases of Weave MCP?

  1. Debugging complex AI systems by tracking request flows.
  2. Optimizing performance bottlenecks in distributed applications.
  3. Enhancing observability in microservices architectures.

FAQ from Weave MCP?

  • What is the purpose of MCP?

MCP connects AI models with information across different services, enhancing their capabilities.

  • How does OpenTelemetry help?

OpenTelemetry provides a standardized way to maintain trace context across services, making debugging easier.

  • Is there a known issue with the tool?

Yes, there is a race condition that may cause failures during the OpenAI call step.

Project Info
Created At
a year ago
Updated At
a year ago
Author Name
zbirenbaum
Star
0
Language
Python
License
-

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