Can I train my bot with a new URL through the agent?

Yes! Use the `add_data_source` tool and provide the Bot ID and the target URL. The bot will automatically scrape and learn from that page.

How do I review the chat history of a specific user conversation?

First, use `list_conversations` to find the active sessions. Then, use `get_conversation_history` with the Conversation ID to retrieve the full log of messages.

Does the integration allow me to create a completely new bot?

Yes. Use the `create_bot` action and provide a name and a system prompt/instructions. The bot will be instantly created in your account.

Bot9 MCP Server for LlamaIndex 8 tools — connect in under 2 minutes

Name: Bot9
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 8 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Bot9 as an MCP tool provider through 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 Bot9. "
            "You have 8 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Bot9?"
    )
    print(response)

asyncio.run(main())

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* 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 Bot9 MCP Server

Connect your Bot9 account to any AI agent and orchestrate your customer support and conversational automation workflows through natural language.

LlamaIndex agents combine Bot9 tool responses with indexed documents for comprehensive, grounded answers. Connect 8 tools through 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

Bot Management — List all configured AI bots, retrieve specific configurations, and create new bots on the fly.
Training & Data Sources — List existing knowledge base sources and dynamically add new URLs for your bots to learn from.
Conversation Oversight — Retrieve active conversation lists and export historical chat logs for analysis.
Message Automation — Send messages to your bots programmatically to test responses or simulate user interactions.

The Bot9 MCP Server exposes 8 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 Bot9 to LlamaIndex via MCP

Follow these steps to integrate the Bot9 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 8 tools from Bot9

Why Use LlamaIndex with the Bot9 MCP Server

LlamaIndex provides unique advantages when paired with Bot9 through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Bot9 tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Bot9 tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Bot9, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Bot9 tools were called, what data was returned, and how it influenced the final answer

Bot9 + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the Bot9 MCP Server delivers measurable value.

Hybrid search: combine Bot9 real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Bot9 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 Bot9 for fresh data

Analytical workflows: chain Bot9 queries with LlamaIndex's data connectors to build multi-source analytical reports

Bot9 MCP Tools for LlamaIndex (8)

These 8 tools become available when you connect Bot9 to LlamaIndex via MCP:

add_data_source

Add a URL to train the bot

create_bot

Create a new AI chatbot

get_bot

Get details of a specific bot

get_conversation_history

Retrieve message history of a conversation

list_bots

List all AI bots

list_conversations

List active conversations for a bot

list_data_sources

List knowledge base sources for a bot

send_message

Send a message to a bot and get a response

Example Prompts for Bot9 in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with Bot9 immediately.

"List all bots in my Bot9 account."

"Add the URL https://example.com/pricing to bot_123's knowledge base."

"Get the chat history for conversation conv_789 on bot_123."

Troubleshooting Bot9 MCP Server with LlamaIndex

Common issues when connecting Bot9 to LlamaIndex through the Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Bot9 + LlamaIndex FAQ

Common questions about integrating Bot9 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.