Can my agent list all experiments for a specific DVC project?

Yes. Use the 'list_experiments' tool. Provide the project ID, and the agent will iterate through the model runs, returning a detailed history of metrics and execution logs for that project.

How do I see my custom dashboard views via chat?

Use the 'list_views' tool to see all your dashboard layouts. You can then use 'get_view' with a specific ID to retrieve the structural configuration and settings for that exact UI representation.

Can I audit my DVC Studio project settings through the agent?

Absolutely. The 'list_projects' and 'get_project' tools allow your agent to analyze identifier boundaries and repository metadata, helping you verify project connections and team mappings natively.

DVC MCP Server for LangChain 6 tools — connect in under 2 minutes

Name: DVC
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 6 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect DVC through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "dvc": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using DVC, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 DVC MCP Server

Connect your DVC Studio account to any AI agent and take full control of your machine learning experiments and data versioning workflows through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with DVC through native MCP adapters. Connect 6 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

What you can do

Project Orchestration — Expose registered organization workspaces and validate available physical repositories connected within DVC Studio limits
Experiment Navigation — Iterate through explicitly generated model runs mapping precise metric arrays and discovering logged metrics history cleanly
View Management — Extract explicit UI configuration layouts and dashboard settings to retrieve structural workspace representations natively
Repository Auditing — Analyze specific identifier boundaries resolving internal team mappings and parsing direct repository metadata constraints
Metric Inspection — Retrieve complex structural arrays defining precisely which metrics were captured during specific experiment epochs
Identity Oversight — Identify the exact authorized token holder exposing mapping roles and organization scopes dynamically to verify permissions

The DVC MCP Server exposes 6 tools through the Vinkius. Connect it to LangChain 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 DVC to LangChain via MCP

Follow these steps to integrate the DVC MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 6 tools from DVC via MCP

Why Use LangChain with the DVC MCP Server

LangChain provides unique advantages when paired with DVC through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine DVC MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across DVC queries for multi-turn workflows

DVC + LangChain Use Cases

Practical scenarios where LangChain combined with the DVC MCP Server delivers measurable value.

RAG with live data: combine DVC tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query DVC, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain DVC tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every DVC tool call, measure latency, and optimize your agent's performance

DVC MCP Tools for LangChain (6)

These 6 tools become available when you connect DVC to LangChain via MCP:

get_project

Get project

get_user

Get user profile

get_view

Get view

list_experiments

List experiments

list_projects

List projects

list_views

List views

Example Prompts for DVC in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with DVC immediately.

"List all projects in my DVC Studio account"

"Show me the last 5 experiments for project 'Credit-Scoring-Model'"

"What are my dashboard views in DVC?"

Troubleshooting DVC MCP Server with LangChain

Common issues when connecting DVC to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

DVC + LangChain FAQ

Common questions about integrating DVC MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.