Can I train a machine learning model using SQL through my agent?

Yes. Use the `execute_sql_query` tool with the 'CREATE MODEL' statement. Your agent will dispatch the command to MindsDB, which will automatically handle the data processing and training of your predictor asynchronously.

How do I connect an external database like PostgreSQL to MindsDB using the agent?

The `execute_sql_query` tool supports the 'CREATE DATABASE' syntax. You can command your agent to link a new data source by providing the connection parameters, allowing MindsDB to query your existing data natively.

Can my agent retrieve the status of an ongoing model training?

Absolutely. Use the `get_model` tool by providing the model name and project. Your agent will report the current training state, accuracy metrics, and any errors encountered during the AI generation process.

MindsDB (AI Database & Predictors) MCP Server for LlamaIndex 6 tools — connect in under 2 minutes

Name: MindsDB (AI Database & Predictors)
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 6 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add MindsDB (AI Database & Predictors) 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 MindsDB (AI Database & Predictors). "
            "You have 6 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in MindsDB (AI Database & Predictors)?"
    )
    print(response)

asyncio.run(main())

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About MindsDB (AI Database & Predictors) MCP Server

Connect your MindsDB instance to any AI agent and take full control of your machine learning workflows, automated predictions, and data integrations through natural SQL-based conversation.

LlamaIndex agents combine MindsDB (AI Database & Predictors) tool responses with indexed documents for comprehensive, grounded answers. Connect 6 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

Predictive Orchestration — Execute arbitrary SQL statements to trigger automated machine learning commands, including 'CREATE MODEL' and 'SELECT ... PREDICT' directly from your agent
Model Lifecycle Audit — List trained AI tables (models) across your projects and retrieve detailed meta-features tracking generation progress or internal accuracy metrics
Data Source Integration — Enumerate external databases connected through MindsDB (e.g., PostgreSQL, Snowflake, ClickHouse) to audit your data pipeline boundaries securely
Virtual View Management — List virtual data views and SQL structural mappings that act as proxy tables for complex data transformation logic
Cluster Diagnostics — Retrieve active cluster status and version statistics to verify the availability and health of your MindsDB environment
Advanced SQL Execution — Run sophisticated queries combining scalar data with ML predictions to fetch literal insights across any schema entity natively

The MindsDB (AI Database & Predictors) MCP Server exposes 6 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 MindsDB (AI Database & Predictors) to LlamaIndex via MCP

Follow these steps to integrate the MindsDB (AI Database & Predictors) 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 6 tools from MindsDB (AI Database & Predictors)

Why Use LlamaIndex with the MindsDB (AI Database & Predictors) MCP Server

LlamaIndex provides unique advantages when paired with MindsDB (AI Database & Predictors) through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine MindsDB (AI Database & Predictors) tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain MindsDB (AI Database & Predictors) tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query MindsDB (AI Database & Predictors), a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what MindsDB (AI Database & Predictors) tools were called, what data was returned, and how it influenced the final answer

MindsDB (AI Database & Predictors) + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the MindsDB (AI Database & Predictors) MCP Server delivers measurable value.

Hybrid search: combine MindsDB (AI Database & Predictors) real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query MindsDB (AI Database & Predictors) 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 MindsDB (AI Database & Predictors) for fresh data

Analytical workflows: chain MindsDB (AI Database & Predictors) queries with LlamaIndex's data connectors to build multi-source analytical reports

MindsDB (AI Database & Predictors) MCP Tools for LlamaIndex (6)

These 6 tools become available when you connect MindsDB (AI Database & Predictors) to LlamaIndex via MCP:

execute_sql_query

E.g: CREATE DATABASE, SELECT ... WHERE, CREATE MODEL ... PREDICT. Wrap logic safely. VERY IMPORTANT: queries returning a large number of rows MUST be explicitly wrapped in a LIMIT statement or risk hitting context overflow. Execute arbitrary SQL statements bounding MindsDB elements

get_model

Get an explicitly trained AI prediction engine

get_status

Acts as a ping tracer returning valid core version/health specs. Get active cluster diagnostic and version statistics

list_databases

List external databases connected through MindsDB

list_models

Use when checking which algorithms are ready to query predictions. List trained AI tables (models) available in a project

list_views

List virtual data views stored inside a target project

Example Prompts for MindsDB (AI Database & Predictors) in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with MindsDB (AI Database & Predictors) immediately.

"List all ML models in the 'mindsdb' project"

"Execute SQL: SELECT price, price_explain FROM mindsdb.home_price_predictor WHERE sqft = 2500"

"Show me all connected databases in my MindsDB instance"

Troubleshooting MindsDB (AI Database & Predictors) MCP Server with LlamaIndex

Common issues when connecting MindsDB (AI Database & Predictors) to LlamaIndex through the Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

MindsDB (AI Database & Predictors) + LlamaIndex FAQ

Common questions about integrating MindsDB (AI Database & Predictors) 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 MindsDB (AI Database & Predictors) tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.