How to Use Agents

Agents enable conversation with data, including structured and unstructured data connected to MindsDB.

`CREATE AGENT` Syntax

Here is the syntax for creating an agent:

CREATE AGENT my_agent
USING
    model = {
        "provider": "openai",
        "model_name" : "gpt-4o",
        "api_key": "sk-abc123",
        "base_url": "http://example.com",
        "api_version": "2024-02-01"
    },
    data = {
         "knowledge_bases": ["project_name.kb_name", ...],
         "tables": ["datasource_conn_name.table_name", ...]
    },
    prompt_template='describe data',
    timeout=10;

It creates an agent that uses the defined model and has access to the connected data.

SHOW AGENTS
WHERE name = 'my_agent';

Note that you can insert all tables from a connected data source and all knowledge bases from a project using the * syntax.

    ...
    data = {
         "knowledge_bases": ["project_name.*", ...],
         "tables": ["datasource_conn_name.*", ...]
    },
    ...

`model`

This parameter defines the underlying language model, including:

provider It is a required parameter. It defines the model provider from the list below.
model_name It is a required parameter. It defines the model name from the list below.
api_key It is an optional parameter (applicable to selected providers), which stores the API key to access the model. Users can provide it either in this api_key parameter, or using environment variables.
base_url It is an optional parameter (applicable to selected providers), which stores the base URL for accessing the model. It is the root URL used to send API requests.
api_version It is an optional parameter (applicable to selected providers), which defines the API version.

The available models and providers include the following.

Anthropic

Available models:

claude-3-opus-20240229
claude-3-sonnet-20240229
claude-3-haiku-20240307
claude-2.1
claude-2.0
claude-instant-1.2

Bedrock

Available models include all models accessible from Bedrock.Note that in order to use Bedrock as a model provider, you should ensure the following packages are installed: langchain_aws and transformers.The following parameters are specific to this provider:

aws_region_name is a required parameter.
aws_access_key_id is a required parameter.
aws_secret_access_key is a required parameter.
aws_session_token is an optional parameter. It may be required depending on the AWS permissions setup.

Google

Available models:

gemini-2.5-pro-preview-03-25
gemini-2.0-flash
gemini-2.0-flash-lite
gemini-1.5-flash
gemini-1.5-flash-8b
gemini-1.5-pro

Ollama

Available models:

gemma
llama2
mistral
mixtral
llava
neural-chat
codellama
dolphin-mixtral
qwen
llama2-uncensored
mistral-openorca
deepseek-coder
nous-hermes2
phi
orca-mini
dolphin-mistral
wizard-vicuna-uncensored
vicuna
tinydolphin
llama2-chinese
openhermes
zephyr
nomic-embed-text
tinyllama
openchat
wizardcoder
phind-codellama
starcoder
yi
orca2
falcon
starcoder2
wizard-math
dolphin-phi
nous-hermes
starling-lm
stable-code
medllama2
bakllava
codeup
wizardlm-uncensored
solar
everythinglm
sqlcoder
nous-hermes2-mixtral
stable-beluga
yarn-mistral
samantha-mistral
stablelm2
meditron
stablelm-zephyr
magicoder
yarn-llama2
wizard-vicuna
llama-pro
deepseek-llm
codebooga
mistrallite
dolphincoder
nexusraven
open-orca-platypus2
all-minilm
goliath
notux
alfred
megadolphin
xwinlm
wizardlm
duckdb-nsql
notus

OpenAI

Available models:

gpt-3.5-turbo
gpt-3.5-turbo-16k
gpt-3.5-turbo-instruct
gpt-4
gpt-4-32k
gpt-4-1106-preview
gpt-4-0125-preview
gpt-4.1
gpt-4.1-mini
gpt-4o
o4-mini
o3-mini
o1-mini

Nvidia NIM

Available models:

microsoft/phi-3-mini-4k-instruct
mistralai/mistral-7b-instruct-v0.2
writer/palmyra-med-70b
mistralai/mistral-large
mistralai/codestral-22b-instruct-v0.1
nvidia/llama3-chatqa-1.5-70b
upstage/solar-10.7b-instruct
google/gemma-2-9b-it
adept/fuyu-8b
google/gemma-2b
databricks/dbrx-instruct
meta/llama-3_1-8b-instruct
microsoft/phi-3-medium-128k-instruct
01-ai/yi-large
nvidia/neva-22b
meta/llama-3_1-70b-instruct
google/codegemma-7b
google/recurrentgemma-2b
google/gemma-2-27b-it
deepseek-ai/deepseek-coder-6.7b-instruct
mediatek/breeze-7b-instruct
microsoft/kosmos-2
microsoft/phi-3-mini-128k-instruct
nvidia/llama3-chatqa-1.5-8b
writer/palmyra-med-70b-32k
google/deplot
meta/llama-3_1-405b-instruct
aisingapore/sea-lion-7b-instruct
liuhaotian/llava-v1.6-mistral-7b
microsoft/phi-3-small-8k-instruct
meta/codellama-70b
liuhaotian/llava-v1.6-34b
nv-mistralai/mistral-nemo-12b-instruct
microsoft/phi-3-medium-4k-instruct
seallms/seallm-7b-v2.5
mistralai/mixtral-8x7b-instruct-v0.1
mistralai/mistral-7b-instruct-v0.3
google/paligemma
google/gemma-7b
mistralai/mixtral-8x22b-instruct-v0.1
google/codegemma-1.1-7b
nvidia/nemotron-4-340b-instruct
meta/llama3-70b-instruct
microsoft/phi-3-small-128k-instruct
ibm/granite-8b-code-instruct
meta/llama3-8b-instruct
snowflake/arctic
microsoft/phi-3-vision-128k-instruct
meta/llama2-70b
ibm/granite-34b-code-instruct

Writer

Available models:

palmyra-x5
palmyra-x4

Users can define the model for the agent choosing one of the following options. Option 1. Use the model parameter to define the specification.

CREATE AGENT my_agent
USING
    model = {
        "provider": "openai",
        "model_name" : "got-4o",
        "api_key": "sk-abc123",
        "base_url": "https://example.com/",
        "api_version": "2024-02-01"
    },
    ...

Option 2. Define the default model in the MindsDB configuration file. If you define default_llm in the configuration file, you do not need to provide the model parameter when creating an agent. If provide both, then the values from the model parameter are used.

You can define the default models in the Settings of the MindsDB Editor GUI.

"default_llm": {

      "provider": "openai",
      "model_name" : "got-4o",
      "api_key": "sk-abc123",
      "base_url": "https://example.com/",
      "api_version": "2024-02-01"

}

`data`

This parameter stores data connected to the agent, including knowledge bases and data sources connected to MindsDB. The following parameters store the list of connected data.

knowledge_bases stores the list of knowledge bases to be used by the agent.
tables stores the list of tables from data sources connected to MindsDB.

`prompt_template`

This parameter stores instructions for the agent. It is recommended to provide data description of the data sources listed in the knowledge_bases and tables parameters to help the agent locate relevant data for answering questions.

`timeout`

This parameter defines the time the agent can take to come back with an answer. For example, when the timeout parameter is set to 10, the agent has 10 seconds to return an answer. If the agent takes longer than 10 seconds, it aborts the process and comes back with an answer indicating its failure to return an answer within the defined time interval.

`SELECT FROM AGENT` Syntax

Query an agent to generate responses to questions.

SELECT answer
FROM my_agent 
WHERE question = 'What is the average number of orders per customers?';

You can redefine the agent’s parameters at the query time as below.

SELECT answer
FROM my_agent 
WHERE question = 'What is the average number of orders per customers?';
USING
    model = {
        "provider": "openai",
        "model_name" : "gpt-4.1",
        "api_key": "sk-abc123"
    },
    data = {
         "knowledge_bases": ["project_name.kb_name", ...],
         "tables": ["datasource_conn_name.table_name", ...]
    },
    prompt_template='describe data',
    timeout=10;

The USING clause may contain any combination of parameters from the CREATE AGENT command, depending on which parameters users want to update for the query. For example, users may want to check the performance of other models to decide which model works better for their use case.

SELECT answer
FROM my_agent 
WHERE question = 'What is the average number of orders per customers?';
USING
    model = {
        "provider": "google",
        "model_name" : "gemini-2.5-flash",
        "api_key": "ABc123"
    };

`ALTER AGENT` Syntax

Update existing agents with new data, model, or prompt.

ALTER AGENT my_agent
USING
    model = {
        "provider": "openai",
        "model_name" : "gpt-4.1",
        "api_key": "sk-abc123",
        "base_url": "http://example.com",
        "api_version": "2024-02-01"
    },
    data = {
         "knowledge_bases": ["project_name.kb_name", ...],
         "tables": ["datasource_conn_name.table_name", ...]
    },
    prompt_template='describe data';

Note that all parameters are optional. Users can update any combination of parameters.

See detailed descriptions of parameters in the CREATE AGENT section.

Here is how to connect new data to an agent.

ALTER AGENT my_agent
USING
    data = {
         "knowledge_bases": ["mindsdb.sales_kb"],
         "tables": ["mysql_db.car_sales", "mysql_db.car_info"]
    };

And here is how to update a model used by the agent.

ALTER AGENT my_agent
USING
    model = {
        "provider": "openai",
        "model_name" : "gpt-4.1",
        "api_key": "sk-abc123"
    };

`DROP AGENT` Syntax

Here is the syntax for deleting an agent:

DROP AGENT my_agent;

Overview

Agents

MCP API

How to Use Agents

`CREATE AGENT` Syntax

`model`

`data`

`prompt_template`

`timeout`

`SELECT FROM AGENT` Syntax

`ALTER AGENT` Syntax

`DROP AGENT` Syntax

Overview

Agents

MCP API

​CREATE AGENT Syntax

​model

​data

​prompt_template

​timeout

​SELECT FROM AGENT Syntax

​ALTER AGENT Syntax

​DROP AGENT Syntax

`CREATE AGENT` Syntax

`model`

`data`

`prompt_template`

`timeout`

`SELECT FROM AGENT` Syntax

`ALTER AGENT` Syntax

`DROP AGENT` Syntax