Load Composio data to DuckDB
Build a Composio to DuckDB pipeline with your coding agent. One prompt scaffolds it with the dltHub AI harness, plus the Composio API base URL, auth, endpoints, and incremental loading.
Composio is a platform that powers tool discovery, execution, authentication, and context management for AI agents with 1000+ toolkits. Everything needed to build a working Composio → 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 Composio to DuckDB pipeline
Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.
PromptRunuvx dlthub-init@latestto build a pipeline from Composio 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 Composio 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.
Composio API at a glance
| Base URL | https://backend.composio.dev |
| Example endpoint | GET api/v3/toolkits |
| Records found at | items |
| Authentication | all requests require an API key in a specific request header — sent in the x-api-key header |
| Pagination | Cursor-based via cursor, next cursor at next_cursor, page size via limit. Pagination is cursor-based. The cursor parameter is a base64 encoded string representing page and limit. It is not required for the first page. Different endpoints have different maximum page size limits (e.g., 50, 500, or 1000). |
| Incremental field | cursor |
| API reference | https://docs.composio.dev/reference/authenticating-to-composio |
These values come from the Composio API reference — the authoritative source if anything here looks out of date.
How do I authenticate with the Composio API?
Authentication requires passing an API key in the request header. Depending on the scope, use 'x-api-key' for project-level keys or 'x-org-api-key' for organization-level keys.
1. Get your credentials
To obtain your Composio API credentials, navigate to the Composio dashboard. For a project-level API key, go to Settings > Project Settings and locate the API Keys section to copy your key. For organization-level access, go to Organization Settings > General Settings and copy a token from the Organization Access Tokens section.
2. Add them to .dlt/secrets.toml
[sources.composio_source] COMPOSIO_API_KEY = "your_project_api_key_here" COMPOSIO_ORG_API_KEY = "your_organization_api_key_here"
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 Composio data can I load into DuckDB?
These are the Composio endpoints dlt can load into DuckDB:
| Resource | Endpoint | Method | Data selector | Description |
|---|---|---|---|---|
| toolkits | /api/v3/toolkits | GET | items | List all available toolkits. |
| tools | /api/v3/tools | GET | items | List or search catalog of available tools. |
| sessions | /api/v3/tool_router/session | GET | List active tool router sessions. | |
| session_toolkits | /api/v3/tool_router/session/{session_id}/toolkits | GET | items | List toolkits available in a specific session. |
| connected_accounts | /api/v3/connected_accounts | GET | items | List user's connected accounts. |
How do I load only new Composio records?
Composio exposes cursor on api/v3/toolkits, 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": "toolkits", "endpoint": { "path": "api/v3/toolkits", "data_selector": "items", "incremental": {"cursor_path": "cursor", "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 Composio pipeline look like?
A standard dlt REST API pipeline — the same code you would write by hand, loading tools and projects from the Composio API into DuckDB:
import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def composio_source(api_key=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://backend.composio.dev", "auth": {"type": "api_key", "api_key": api_key, "name": "x-api-key", "location": "header"}, }, "resources": [ {"name": "toolkits", "endpoint": {"path": "api/v3/toolkits", "data_selector": "items"}}, {"name": "tools", "endpoint": {"path": "api/v3/tools", "data_selector": "items"}} ], } yield from rest_api_resources(config) def load_composio_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="composio_pipeline", destination="duckdb", dataset_name="composio_data", ) load_info = pipeline.run(composio_source()) print(load_info) if __name__ == "__main__": load_composio_to_duckdb()
Run it with python composio_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 Composio 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("composio_pipeline").dataset() df = data.session_toolkits.df() print(df.head())
SQL:
SELECT * FROM composio_data.session_toolkits LIMIT 10;
See querying your data with dataset and exploring it in marimo notebooks.
How do I deploy the Composio 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 Composio 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 Composio 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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