Can I search for specific keywords across all my notebooks?

Yes. The `search_notecards` tool allows your AI agent to perform a global search across your entire Zoho Notebook account, returning all cards that match your query string instantly.

How do I add a new checklist or note to a specific notebook?

You can use the `create_notecard` tool. Provide the parent `notebook_id`, a title, and the content. You can also specify the type as 'text' or 'checklist' to match your organizational needs.

Is it possible to see the full content of a card via chat?

Absolutely. Use the `get_notecard_details` tool and provide the notebook and card IDs. Your agent will retrieve the full body content and metadata for that specific note.

Zoho Notebook MCP Server for LlamaIndex 10 tools — connect in under 2 minutes

Name: Zoho Notebook
Availability: InStock
Author: Vinkius

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Zoho Notebook as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

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 llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to Zoho Notebook. "
            "You have 10 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Zoho Notebook?"
    )
    print(response)

asyncio.run(main())

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About Zoho Notebook MCP Server

Connect your Zoho Notebook account to any AI agent and take control of your personal and professional knowledge base through natural conversation.

LlamaIndex agents combine Zoho Notebook tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through the Vinkius and query live data alongside vector stores and SQL databases in a single turn — ideal for hybrid search, data enrichment, and analytical workflows.

What you can do

Notebook Organization — List all your notebooks, create new ones for specific projects, or delete obsolete collections directly from your agent
Notecard Discovery — Browse and list all notecards within any notebook to find relevant information and retrieve unique card IDs
Content Capture — Create new text or checklist notecards instantly by providing a title and body content through simple commands
Rich Notecards — Retrieve full metadata and content for specific cards, including support for different types (text, checklist, etc.)
Global Search — Search across all your notebooks and cards by keyword to find specific ideas or data points instantly
Idea Management — Update existing notecards with new information or permanently delete obsolete items through conversation
Workspace Auditing — Verify your notebook hierarchy and retrieve unique IDs required for automated knowledge workflows

The Zoho Notebook MCP Server exposes 10 tools through the Vinkius. Connect it to LlamaIndex 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 Zoho Notebook to LlamaIndex via MCP

Follow these steps to integrate the Zoho Notebook MCP Server with LlamaIndex.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 10 tools from Zoho Notebook

Why Use LlamaIndex with the Zoho Notebook MCP Server

LlamaIndex provides unique advantages when paired with Zoho Notebook through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Zoho Notebook tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Zoho Notebook tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Zoho Notebook, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Zoho Notebook tools were called, what data was returned, and how it influenced the final answer

Zoho Notebook + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the Zoho Notebook MCP Server delivers measurable value.

Hybrid search: combine Zoho Notebook real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Zoho Notebook to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Zoho Notebook for fresh data

Analytical workflows: chain Zoho Notebook queries with LlamaIndex's data connectors to build multi-source analytical reports

Zoho Notebook MCP Tools for LlamaIndex (10)

These 10 tools become available when you connect Zoho Notebook to LlamaIndex via MCP:

create_notebook

Useful for organizing notecards. Create notebook

create_notecard

Create notecard

delete_notebook

Delete notebook

delete_notecard

Delete notecard

get_notebook

Get notebook details

get_notecard

Get notecard details

list_notebooks

Returns notebook IDs which are needed to fetch notecards. List all notebooks

list_notecards

Notebook ID is required. List notecards in notebook

search_notecards

Search notecards

update_notecard

Update notecard

Example Prompts for Zoho Notebook in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with Zoho Notebook immediately.

"List all my notebooks in Zoho Notebook."

"Create a new text note in 'nb-101' called 'Gift Ideas' with content 'Buy a watch for John'."

"Search for notes about 'React navigation'."

Troubleshooting Zoho Notebook MCP Server with LlamaIndex

Common issues when connecting Zoho Notebook to LlamaIndex through the Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Zoho Notebook + LlamaIndex FAQ

Common questions about integrating Zoho Notebook MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Zoho Notebook tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.