# ai.getvda/llm-observability-orchestration-agent-langchain

> ai.getvda/llm-observability-orchestration-agent-langchain — ai-getvda-llm-observability-orchestration-agent-langchain. Use this tool when you need to monitor and manage large language models (LLMs) for improved performance and reliability. It solves problems related to LLM observability, scalability, and automation, providing inputs such as model metrics and outputs like optimized model configurations. Use it in contexts where LLMs are deployed, such as natural language processing, text generation, and conversational AI applications.

Canonical page: https://skillsregistry.net/skills/ai-getvda-llm-observability-orchestration-agent-langchain  
JSON: https://api.skillsregistry.net/v1/skills/ai-getvda-llm-observability-orchestration-agent-langchain

## Description

LLM Observability & Orchestration Agent (Langchain)

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Updated:** 2026-09-03

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/ai.getvda%2Fllm-observability-orchestration-agent-langchain)

## Use it

MCP endpoint published by the skill: `https://langchain-langchain-core-langsmit-d042fc.getvda.ai/mcp`

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "ai-getvda-llm-observability-orchestration-agent-langchain"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ai-getvda-llm-observability-orchestration-agent-langchain` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ai-getvda-llm-observability-orchestration-agent-langchain/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt