FormBricks Python API Docs | dltHub

FormBricks is a feedback and survey platform that provides client-side (public) and management REST APIs to create and manage surveys, responses, people, webhooks, and related resources. The REST API base URL is https://app.formbricks.com/api/v1 and Management API requests require a personal API key; the Public Client API is unauthenticated..

dlt is an open-source Python library that handles authentication, pagination, and schema evolution automatically. dlthub provides AI context files that enable code assistants to generate production-ready pipelines. Install with uv pip install "dlt[workspace]" and start loading FormBricks data in under 10 minutes.

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What data can I load from FormBricks?

Here are some of the endpoints you can load from FormBricks:

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How do I authenticate with the FormBricks API?

The Management API requires a personal API Key created in the FormBricks app settings. Client-side Public APIs do not require authentication. Include the Management API key in requests as the API Key (Authorization header or API Key header as configured in your account).

1. Get your credentials

1. Sign in to your FormBricks account at https://app.formbricks.com. 2) Go to Settings -> API Keys (or Management API / API Key Setup). 3) Generate a new personal API Key. 4) Copy and store the key securely; use it in Authorization headers when calling Management API endpoints.

2. Add them to .dlt/secrets.toml

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[sources.formbricks_source]
api_key = "your_formbricks_api_key_here"

dlt reads this automatically at runtime — never hardcode tokens in your pipeline script. For production environments, see setting up credentials with dlt for environment variable and vault-based options.

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How do I set up and run the pipeline?

Set up a virtual environment and install dlt:

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uv venv && source .venv/bin/activate
uv pip install "dlt[workspace]"

1. Install the dlt AI Workbench:

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dlt ai init --agent <your-agent> # <agent>: claude | cursor | codex

This installs project rules, a secrets management skill, appropriate ignore files, and configures the dlt MCP server for your agent. Learn more →

2. Install the rest-api-pipeline toolkit:

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dlt ai toolkit rest-api-pipeline install

This loads the skills and context about dlt the agent uses to build the pipeline iteratively, efficiently, and safely. The agent uses MCP tools to inspect credentials — it never needs to read your secrets.toml directly. Learn more →

3. Start LLM-assisted coding:

Use /find-source to load data from the FormBricks API into DuckDB.

The rest-api-pipeline toolkit takes over from here — it reads relevant API documentation, presents you with options for which endpoints to load, and follows a structured workflow to scaffold, debug, and validate the pipeline step by step.

4. Run the pipeline:

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python formbricks_pipeline.py

If everything is configured correctly, you'll see output like this:

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Pipeline formbricks_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset formbricks_data
The duckdb destination used duckdb:/formbricks.duckdb location to store data
Load package 1749667187.541553 is LOADED and contains no failed jobs

Inspect your pipeline and data:

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dlt pipeline formbricks_pipeline show

This opens the Pipeline Dashboard where you can verify pipeline state, load metrics, schema (tables, columns, types), and query the loaded data directly.

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Python pipeline example

This example loads responses and surveys from the FormBricks API into DuckDB. It mirrors the endpoint and data selector configuration from the table above:

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import dlt
from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources

@dlt.source
def formbricks_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://app.formbricks.com/api/v1",
            "auth": {
                "type": "bearer",
                "api_key": api_key,
            },
        },
        "resources": [
            {"name": "responses", "endpoint": {"path": "responses", "data_selector": "data"}},
            {"name": "surveys", "endpoint": {"path": "projects/{projectId}/surveys", "data_selector": "data"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="formbricks_pipeline",
        destination="duckdb",
        dataset_name="formbricks_data",
    )
    load_info = pipeline.run(formbricks_source())
    print(load_info)

To add more endpoints, append entries from the resource table to the "resources" list using the same name, path, and data_selector pattern.

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How do I query the loaded data?

Once the pipeline runs, dlt creates one table per resource. You can query with Python or SQL.

Python (pandas DataFrame):

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import dlt

data = dlt.pipeline("formbricks_pipeline").dataset()
sessions_df = data.responses.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM formbricks_data.responses LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("formbricks_pipeline").dataset()
data.responses.df().head()

See how to explore your data in marimo Notebooks and how to query your data in Python with dataset.

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What destinations can I load FormBricks data to?

dlt supports loading into any of these destinations — only the destination parameter changes:

Change the destination in dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. See the full destinations list.

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Troubleshooting

Authentication failures

If you receive 401/403 errors when calling Management API endpoints: ensure you are using a personal API Key generated in the FormBricks app settings. Verify you include the key in the Authorization header (Bearer) or configured API key header. Also confirm you are calling the Management API (not the public client API).

Rate limits and errors

FormBricks may return standard HTTP error codes and JSON error bodies (examples in Postman show responses like { "code": "internal_server_error", "message": "..." }). Handle 4xx/5xx responses by logging the error code and message. Implement retry/backoff for 5xx responses.

Pagination quirks

List endpoints return arrays under the "data" key. If the API supports pagination (offset/limit or cursor), apply the query parameters documented per-endpoint in the official docs; otherwise retrieve all pages by following documented paging parameters.

Ensure that the API key is valid to avoid 401 Unauthorized errors. Also, verify endpoint paths and parameters to avoid 404 Not Found errors.

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Next steps

Continue your data engineering journey with the other toolkits of the dltHub AI Workbench:

• data-exploration — Build custom notebooks, charts, and dashboards for deeper analysis with marimo notebooks.
• dlthub-runtime — Deploy, schedule, and monitor your pipeline in production.

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dlt ai toolkit data-exploration install
dlt ai toolkit dlthub-runtime install

• How to deploy a pipeline
• How to explore your data in marimo Notebooks
• How to query your data in Python with dataset
• Join the dlt community on Slack