Nuclino MCP Server for LangChain 12 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Nuclino through 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({
"nuclino": {
"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 Nuclino, 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 Nuclino MCP Server
Connect your Nuclino account to your AI agent and seamlessly interact with your company's unified workspace for knowledge, docs, and projects.
LangChain's ecosystem of 500+ components combines seamlessly with Nuclino through native MCP adapters. Connect 12 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
- Teams & Workspaces — Rapidly list all teams you are part of, and enumerate the nested workspaces and collections to understand your organization's hierarchy.
- Search & Query — Perform global fuzzy searches using
search_itemsto track down specific documents, notes, or project pages across the entire knowledge base. - Read Items & Files — Read the exact content configuration of any item (document) via
get_item, and list attachments or files uploaded to the platform. - Record Creation — Instantly create new items natively inside your workspace using natural language.
- Telemetrics — Enumerate members and structural fields within your Nuclino domain to keep the agent aware of context and owners.
The Nuclino MCP Server exposes 12 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 Nuclino to LangChain via MCP
Follow these steps to integrate the Nuclino 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 12 tools from Nuclino via MCP
Why Use LangChain with the Nuclino MCP Server
LangChain provides unique advantages when paired with Nuclino through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Nuclino 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 Nuclino queries for multi-turn workflows
Nuclino + LangChain Use Cases
Practical scenarios where LangChain combined with the Nuclino MCP Server delivers measurable value.
RAG with live data: combine Nuclino tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Nuclino, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Nuclino tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Nuclino tool call, measure latency, and optimize your agent's performance
Nuclino MCP Tools for LangChain (12)
These 12 tools become available when you connect Nuclino to LangChain via MCP:
create_item
Triggers real-time replication creating permanent Wiki documentation. Write a brand new knowledge Item / Page into a Workspace
delete_item
Always confirm with the user heavily before destroying knowledge. Irreversibly delete a structural Nuclino Item
get_item
Retrieve the exact Markdown payload and configuration of an Item
list_collections
Used to trace the document relationship graph paths visually within a target Workspace. List Collections (grouping directories) segmenting a Workspace
list_fields
Used to understand standard taxonomy dimensions applicable against Items. Map customizable structured property fields globally binding a Team
list_files
Exposes pure URL bindings mapping binary data records back to object storage. List physical attachments explicitly bolted onto an Item
list_items
Used to enumerate top-level document UUIDs, titles, and creation metadata natively spanning a specific Workspace layer. List all standard knowledge items (pages) in a Workspace
list_teams
Use this as the entry point to discover available root organizational unit IDs traversing down into workspaces. List all organizational Teams the authenticated user belongs to
list_users
Enumerate human identities attached globally onto a Team
list_workspaces
Returns internal workspace UUIDs essential for scoping later item queries. List all isolated Workspaces mapped within a specific Team
search_items
Use to uncover unknown UUIDs. Execute an indexed semantic search globally across a Team
update_item
Alters the sync tree immediately appending new wiki edits. Overwrite active partial Markdown states inside a listed Item
Example Prompts for Nuclino in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Nuclino immediately.
"Search Nuclino for any documentation mentioning 'SSO Security Policies'."
"Create an item titled 'Project X Architecture Brief' in the Engineering workspace."
"List all teams connected to this authentication token."
Troubleshooting Nuclino MCP Server with LangChain
Common issues when connecting Nuclino to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersNuclino + LangChain FAQ
Common questions about integrating Nuclino 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 Nuclino 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 Nuclino to LangChain
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.