Mongo DB Path Setup

11 min

This section explains how to configure a Mongo retrieval path after the custom script data is stored in the database.

followed by the step-by-step setup.

Step 1 — Create a New Path

Go to the Builder section.

Click + Add Path and create a new path.

Example path name: mongo search path

Step 2 — Add a JSON API Node

Inside the path, click Add Node and select JSON API.

This node will be used to fetch stored Mongo data.

Step 3 — Configure the JSON API Request

Set the request method to POST.

In the Request URL field, enter the Mongo API endpoint.

URL:

<https://MONGO-FETCH>

Go to the Body tab and set Content Type as JSON.

Use the following request body:

{ "bot_ref": "{{bot.id}}", "fields_to_fetch": [ "Doctor Name", //retreival fields "Experience" ], "filters": [ { "Speciality": "{{Speciality}}" } ], "database": "customer_data", "collection_name": "{{bot.id}}" }

This request retrieves data by matching the exact field value passed in user_query.

Request Body Explanation

Field	Description
bot_ref	Unique identifier of the bot. This ensures the request fetches data specific to that bot.
fields_to_fetch	Specifies which fields should be returned from the database. Only the listed fields will be retrieved.
filters	Used to search for records matching specific field values stored in the database.
database	Name of the Mongo database where the data is stored.
collection_name	Mongo collection where the records are stored. In this case it uses the bot ID.

Example:

If user_query = Cardiology, the API will return the doctor record where Speciality = Cardiology.

Speciality

Step 4 — Test the API Request

Click Send Request to test the API.

The system will prompt you to enter test values for:

bot.id

Speciality

Enter sample values and submit the request.

Example:

bot.id → 145265

Speciality → Cardiology

Where to Find bot.id? Bot ID (bot.id) – Found in the Builder URL (last number in the URL). Example: 145265

Once the request is successful, the API response will appear in the Response section.

Example response:

{ "Response": [ { "Doctor Name": "Dr. Arjun Mehta", "Experience": "15 Years", "_id": "69b3bf53e69521c8608e1dd" } ] }

This means the system found a matching record from the stored Mongo data.

Step 6 — Map the Response to Attributes

In the Attributes section, create attributes to store the response.

You can store the full response or individual fields.

Example mappings:

Response

or specific values:

Doctor Name Response.0.Doctor Name Experience Response.0.Experience

This stores the returned Mongo values in attributes for later use in the path.

Step 7 — Save the Node

After testing the request and mapping the response, click Save.

The JSON API node is now ready to retrieve Mongo data during conversations.

How Retrieval Works

Data is first stored in MongoDB through the custom script

The JSON API node sends a filter request

Mongo searches for records matching the exact field value

The matched result is returned in the API response

The response is stored in attributes

Those attributes can be used in the next node to reply to the user

Example

Stored record:

{ "Doctor Name": "Dr. Arjun Mehta", "Speciality": "Cardiology", "Location": "Bangalore", "Experience": "15 Years" }

Filter used in request:

{ "Speciality": "Cardiology" }

Returned result:

Dr. Arjun Mehta

📚 Next Step

Once the Mongo API response is stored in an attribute, you can use that attribute in the next node to send the retrieved answer back to the user.

👉 Continue to the next section: 4. Workflow SetupWorkflow Setup