Dify MCP Server for LangChain 6 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Dify through the Vinkius and LangChain agents can call every tool natively — combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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({
"dify": {
"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 Dify, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
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 Dify MCP Server
Connect your Dify.ai application to any AI agent and take full control of your LLM application development and agentic workflows through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with Dify through native MCP adapters. Connect 6 tools via the 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
- Agentic Chat Orchestration — Commands the backend orchestrating absolute explicit strings sending chat messages seamlessly against standard Dify agents
- Conversation Navigation — Extracts explicitly attached array vectors representing company-wide conversation listings from your Dify project
- Message Auditing — Analyzes specific localized variables decoding active conversation message arrays to track historical interactions
- Structural Parameters — Extracts configuration limits mapping global explicit constraints inside the referenced Dify workspace
- Secure File Ingestion — Mutate explicit arrays directly transmitting local binaries mapped internally against standard Dify attachments securely
- Feedback Management — Submit message-level feedback (likes/dislikes) to instantiate absolute explicit CRM environments tracking AI performance
The Dify 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 Dify to LangChain via MCP
Follow these steps to integrate the Dify 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 Dify via MCP
Why Use LangChain with the Dify MCP Server
LangChain provides unique advantages when paired with Dify through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents — combine Dify 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 Dify queries for multi-turn workflows
Dify + LangChain Use Cases
Practical scenarios where LangChain combined with the Dify MCP Server delivers measurable value.
RAG with live data: combine Dify tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Dify, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Dify tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Dify tool call, measure latency, and optimize your agent's performance
Dify MCP Tools for LangChain (6)
These 6 tools become available when you connect Dify to LangChain via MCP:
chat
Send a chat message
feedback
Submit message feedback
get_parameters
Get app parameters
list_conversations
List conversations
list_messages
List messages in conversation
upload_file
Upload a file
Example Prompts for Dify in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Dify immediately.
"Send a message to my Dify agent: 'Explain the benefits of RAG.'"
"List my recent Dify conversations for user 'admin_123'"
"Give a 'like' to message 'msg_789' in Dify"
Troubleshooting Dify MCP Server with LangChain
Common issues when connecting Dify to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersDify + LangChain FAQ
Common questions about integrating Dify MCP Server with LangChain.
How does LangChain connect to MCP servers?
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?
Can I trace MCP tool calls in LangSmith?
Connect Dify 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 Dify to LangChain
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.