How do I chat with a specific bot?

Use the `send_bot_message` tool and provide the Bot ID and your message content. The AI agent will relay your message to the GPTBots platform and return the bot's response.

Can I check the status of a triggered workflow?

Yes. When you use `trigger_workflow`, it returns a Record ID. You can then pass that Record ID to the `query_workflow` tool to monitor its execution status (e.g., Running, Success, Failed).

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

Name: GPTBots
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 GPTBots 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 GPTBots. "
            "You have 8 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in GPTBots?"
    )
    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 GPTBots MCP Server

Connect your GPTBots account to your AI agent and manage your enterprise AI infrastructure conversationally. Interact with your deployed bots, trigger complex automated workflows, and upload new documents to your knowledge bases without leaving your development environment.

LlamaIndex agents combine GPTBots 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 Interaction — List active conversations, review chat histories, and send messages directly to your deployed AI agents
Knowledge Management — Browse available knowledge documents and upload new content to keep your bots' context up to date
Workflow Automation — Trigger configured AI workflows and query their execution status programmatically
Database Queries — List tables and records hosted within the GPTBots platform database

The GPTBots 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 GPTBots to LlamaIndex via MCP

Follow these steps to integrate the GPTBots 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 GPTBots

Why Use LlamaIndex with the GPTBots MCP Server

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

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

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

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

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

GPTBots + LlamaIndex Use Cases

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

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

Data enrichment: query GPTBots 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 GPTBots for fresh data

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

GPTBots MCP Tools for LlamaIndex (8)

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

create_knowledge_document

Upload or create a document in the Knowledge Base

get_conversation

Get details and history of a specific conversation

list_conversations

List chat conversations with a bot

list_databases

List tables in the platform database

list_knowledge_documents

List documents in a Knowledge Base

query_workflow

Check the execution status of a triggered workflow

send_bot_message

Send a message to a GPTBots Agent

trigger_workflow

Trigger an automated workflow

Example Prompts for GPTBots in LlamaIndex

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

"List all recent conversations for bot ID 'bot_123xyz'."

"Trigger the onboarding workflow (ID: 'wf_456') and pass the parameter email='test@example.com'."

Troubleshooting GPTBots MCP Server with LlamaIndex

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

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

GPTBots + LlamaIndex FAQ

Common questions about integrating GPTBots 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 GPTBots tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.