LangSmith (LLM Observability & Hub) MCP Server for AutoGen 6 tools — connect in under 2 minutes
Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add LangSmith (LLM Observability & Hub) as an MCP tool provider through the Vinkius and every agent in the group can access live data and take action.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.tools.mcp import McpWorkbench
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
async with McpWorkbench(
server_params={"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"},
transport="streamable_http",
) as workbench:
tools = await workbench.list_tools()
agent = AssistantAgent(
name="langsmith_llm_observability_hub_agent",
tools=tools,
system_message=(
"You help users with LangSmith (LLM Observability & Hub). "
"6 tools available."
),
)
print(f"Agent ready with {len(tools)} tools")
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About LangSmith (LLM Observability & Hub) MCP Server
Connect your LangSmith account to any AI agent and take full control of your LLM observability, tracing, and prompt management through natural conversation.
AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use LangSmith (LLM Observability & Hub) tools. Connect 6 tools through the Vinkius and assign role-based access — a data analyst queries while a reviewer validates, with optional human-in-the-loop approval for sensitive operations.
What you can do
- Trace Orchestration — List active tracing projects and retrieve detailed execution logs for specific LLM invocation runs directly from your agent
- Performance Telemetry — Extract precise metrics including token consumption, prompt latency, and exact error strings from your AI pipelines
- Prompt Hub Access — Navigate and retrieve managed prompt templates, variable definitions, and version histories hosted in the LangChain Hub
- Evaluation Datasets — Enumerate curated 'golden' datasets used for automated evaluation of prompt logic or few-shot injection models
- Human-in-the-Loop Audit — Monitor active annotation queues where human reviewers assess the alignment, accuracy, and safety of generated LLM traces
- Agentic Step Analysis — Deep-dive into multi-turn agentic workflows to understand nested tool calls and internal reasoning paths securely
The LangSmith (LLM Observability & Hub) MCP Server exposes 6 tools through the Vinkius. Connect it to AutoGen in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect LangSmith (LLM Observability & Hub) to AutoGen via MCP
Follow these steps to integrate the LangSmith (LLM Observability & Hub) MCP Server with AutoGen.
Install AutoGen
Run pip install "autogen-ext[mcp]"
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Integrate into workflow
Use the agent in your AutoGen multi-agent orchestration
Explore tools
The workbench discovers 6 tools from LangSmith (LLM Observability & Hub) automatically
Why Use AutoGen with the LangSmith (LLM Observability & Hub) MCP Server
AutoGen provides unique advantages when paired with LangSmith (LLM Observability & Hub) through the Model Context Protocol.
Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use LangSmith (LLM Observability & Hub) tools to solve complex tasks
Role-based architecture lets you assign LangSmith (LLM Observability & Hub) tool access to specific agents — a data analyst queries while a reviewer validates
Human-in-the-loop support: agents can pause for human approval before executing sensitive LangSmith (LLM Observability & Hub) tool calls
Code execution sandbox: AutoGen agents can write and run code that processes LangSmith (LLM Observability & Hub) tool responses in an isolated environment
LangSmith (LLM Observability & Hub) + AutoGen Use Cases
Practical scenarios where AutoGen combined with the LangSmith (LLM Observability & Hub) MCP Server delivers measurable value.
Collaborative analysis: one agent queries LangSmith (LLM Observability & Hub) while another validates results and a third generates the final report
Automated review pipelines: a researcher agent fetches data from LangSmith (LLM Observability & Hub), a critic agent evaluates quality, and a writer produces the output
Interactive planning: agents negotiate task allocation using LangSmith (LLM Observability & Hub) data to make informed decisions about resource distribution
Code generation with live data: an AutoGen coder agent writes scripts that process LangSmith (LLM Observability & Hub) responses in a sandboxed execution environment
LangSmith (LLM Observability & Hub) MCP Tools for AutoGen (6)
These 6 tools become available when you connect LangSmith (LLM Observability & Hub) to AutoGen via MCP:
get_run
Get precise telemetry for a single LLM invocation run
list_annotation_queues
List active human-in-the-loop annotation queues
list_datasets
List all evaluation and fine-tuning datasets mapped in LangSmith
list_projects
Maps out the boundaries of distinct AI pipelines currently monitored by LangSmith. List all active LangSmith tracing projects/sessions
list_prompts
Extract prompt templates hosted in the LangChain Hub
list_runs
Isolates the raw interactions containing prompts sent to and responses received from the AI models. List explicit LLM invocation runs within a specific project
Example Prompts for LangSmith (LLM Observability & Hub) in AutoGen
Ready-to-use prompts you can give your AutoGen agent to start working with LangSmith (LLM Observability & Hub) immediately.
"List all active tracing projects in LangSmith"
"Show me the telemetry for the last run in the 'Production-Bot-V2' project"
"List all prompts hosted in our Hub repository"
Troubleshooting LangSmith (LLM Observability & Hub) MCP Server with AutoGen
Common issues when connecting LangSmith (LLM Observability & Hub) to AutoGen through the Vinkius, and how to resolve them.
McpWorkbench not found
pip install "autogen-ext[mcp]"LangSmith (LLM Observability & Hub) + AutoGen FAQ
Common questions about integrating LangSmith (LLM Observability & Hub) MCP Server with AutoGen.
How does AutoGen connect to MCP servers?
Can different agents have different MCP tool access?
Does AutoGen support human approval for tool calls?
Connect LangSmith (LLM Observability & Hub) with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect LangSmith (LLM Observability & Hub) to AutoGen
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.