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io.github.mikerawsonnz/llm-observability-orchestration

Official1 toolLive

by mikerawsonnz · Python

Run a prompt through a LangChain (system + human) chain over Gemini on Vertex AI; optional LangSmith

io.github.mikerawsonnz/llm-observability-orchestration MCP Server

This MCP server runs a prompt through a LangChain chain using a system + human message pattern, executing via Gemini on Vertex AI. It optionally integrates LangSmith. The repository is identified as io.github.mikerawsonnz/llm-observability-orchestration and provides one tool (toolCount: 1).

🛠️ Key Features

  • LangChain system + human prompt chaining
  • Gemini execution on Vertex AI
  • Optional LangSmith integration
  • Model Context Protocol (MCP) server / mcp-server focus

🚀 Use Cases

  • LLM prompt execution on Vertex AI with Gemini
  • Observability workflow with optional LangSmith
  • Agent-style A2A interactions using MCP (topics include a2a, ai-agents)

⚡ Developer Benefits

  • A single, focused MCP tool (toolCount: 1)
  • Developer-oriented stack: LangChain, Gemini, Vertex AI, optional LangSmith

⚠️ Limitations

  • Limited documented functionality beyond the single tool and the prompt-execution chain description
  • Readme excerpt provided is about “GOSCE Agents” rather than detailed MCP server behavior

Topics

a2aagentmcpmcp-servermodel-context-protocolneverminedx402ai-agentsgeminillm

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