Load Monnify data to DuckDB
Build a Monnify to DuckDB pipeline with your coding agent. One prompt scaffolds it with the dltHub AI harness, plus the Monnify API base URL, auth, endpoints, and incremental loading.
Monnify is a payment gateway platform that provides APIs for managing collections, transactions, and payment settlement. Everything needed to build a working Monnify → DuckDB pipeline is on this page: the API's base URL, authentication, endpoints, pagination and incremental field — plus a prompt that hands the whole job to your coding agent.
Build your Monnify to DuckDB pipeline
Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.
PromptRunuvx dlthub-init@latestto build a pipeline from Monnify to DuckDB and run it on dltHub
That scaffolds a dltHub workspace and installs the dltHub AI harness — the project rules, the secrets-management skill, and the dlt MCP server your agent needs to work safely. From there it reads the Monnify API, proposes the endpoints to load, then writes, runs and validates the pipeline while you review rather than type. Credentials are inspected through MCP tools, so your agent never reads secrets.toml itself. How the LLM-native workflow works →
Prefer to write it yourself? Every fact the agent uses is below.
Monnify API at a glance
| Base URL | https://api.monnify.com |
| Example endpoint | GET api/v1/transactions/search |
| Records found at | content |
| Authentication | uses a two-step OAuth 2.0 flow: Basic auth for login, followed by Bearer token authentication for subsequent requests — sent in the Authorization header, prefixed Bearer |
| Pagination | Page-number |
| Incremental field | from/to timestamps |
| Record id | transactionReference |
| API reference | https://developers.monnify.com/api |
These values come from the Monnify API reference — the authoritative source if anything here looks out of date.
How do I authenticate with the Monnify API?
Authentication requires a two-step process: first, use Basic authentication with a base64-encoded 'apiKey:secretKey' string to obtain an access token via the login endpoint. Subsequently, provide this token in an 'Authorization: Bearer ' header for all protected API requests.
1. Get your credentials
To obtain your Monnify API credentials: 1. Log in to your Monnify dashboard. 2. Navigate to 'Settings' in the sidebar. 3. Select 'API Keys & Webhooks'. 4. Use the toggle button on your dashboard to switch between 'Test' (sandbox) mode and 'Live' (production) mode to view the corresponding credentials. Your API Key and Secret Key will be displayed here. Your Contract Code can be found under 'Settings' > 'Contracts' or within the 'API Keys & Contracts' section.
2. Add them to .dlt/secrets.toml
[sources.monnify_source] monnify_api_key = "MK_TEST_xxxxxxxxxxxx" monnify_secret_key = "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" monnify_contract_code = "1234567890"
dlt reads this file automatically at runtime. With the harness, the setup-secrets skill prompts you for the values and never handles the raw credential in chat. For production, see setting up credentials with dlt.
What Monnify data can I load into DuckDB?
These are the Monnify endpoints dlt can load into DuckDB:
| Resource | Endpoint | Method | Data selector | Description |
|---|---|---|---|---|
| transactions | api/v1/transactions/search | GET | content | Search all collection transactions |
| disbursement_transactions | api/v2/disbursements/search-transactions | GET | content | Search all disbursement transactions |
| wallet_statement | api/v1/disbursements/wallet/{accountNumber}/statement | GET | content | Get wallet statement transactions |
| bulk_transfer_transactions | api/v2/disbursements/bulk/{batchReference}/transactions | GET | content | Get transactions in a bulk transfer batch |
| all_single_transfers | api/v1/disbursements/single-transfers | GET | content | Get paginated list of single transfers |
How do I load only new Monnify records?
Monnify exposes from/to timestamps on api/v1/transactions/search, so dlt can request only the records that changed since the last run. Set it as the cursor_path and dlt tracks the high-water mark for you between runs.
{"name": "transactions", "endpoint": { "path": "api/v1/transactions/search", "data_selector": "content", "incremental": {"cursor_path": "from/to timestamps", "initial_value": "2024-01-01T00:00:00Z"}, }}
On the first run dlt loads everything from initial_value; on every run after that it requests only what changed and appends with write_disposition="merge" if you set a primary key. See incremental loading.
What does the generated Monnify pipeline look like?
A standard dlt REST API pipeline — the same code you would write by hand, loading auth/v1/login and api/v1/merchant/transactions/init from the Monnify API into DuckDB:
import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def monnify_source(api_key_secret_key=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://api.monnify.com", "auth": {"type": "bearer", "token": api_key_secret_key}, }, "resources": [ {"name": "transactions", "endpoint": {"path": "api/v1/transactions/search", "data_selector": "content"}}, {"name": "disbursement_transactions", "endpoint": {"path": "api/v2/disbursements/search-transactions", "data_selector": "content"}} ], } yield from rest_api_resources(config) def load_monnify_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="monnify_pipeline", destination="duckdb", dataset_name="monnify_data", ) load_info = pipeline.run(monnify_source()) print(load_info) if __name__ == "__main__": load_monnify_to_duckdb()
Run it with python monnify_pipeline.py. The agent iterates on this until it loads cleanly — you review and approve, rather than write it from scratch.
How do I query Monnify data in DuckDB?
dlt creates one table per resource. Query the loaded data with Python or SQL — or ask your agent to, through the MCP server's execute_sql_query tool.
Python (pandas DataFrame):
import dlt data = dlt.pipeline("monnify_pipeline").dataset() df = data.transactions.df() print(df.head())
SQL:
SELECT * FROM monnify_data.transactions LIMIT 10;
See querying your data with dataset and exploring it in marimo notebooks.
How do I deploy the Monnify to DuckDB pipeline in production?
The pipeline runs locally, which is ideal for prototyping and one-off analysis. When you need it on a schedule, monitored on every load, and shared with your team, deploy the same dlt code on the dltHub platform — no infrastructure to maintain. The prompt above already ends with "run it on dltHub", so your agent can take it there directly.
- Deploy & schedule — run the pipeline as a managed job with automatic retries.
- Monitor — observable job queues, alerting, and load metrics for every run.
- Transform — promote raw Monnify loads into governed, documented models.
- Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.
What other destinations can I load Monnify data to?
dlt loads into any of these — only the destination argument changes:
| Destination | Example value |
|---|---|
| PostgreSQL | "postgres" |
| BigQuery | "bigquery" |
| Snowflake | "snowflake" |
| Redshift | "redshift" |
| Databricks | "databricks" |
| Filesystem (S3, GCS, Azure) | "filesystem" |
Set dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. On the dltHub platform the same pipeline runs against a managed Iceberg lakehouse. See the full destinations list.
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