REST API

Erdo’s REST API lets you integrate your data platform into any application. Query datasets, write data, manage conversations, create automations, and more — all via standard HTTP requests. Base URL: https://api.erdo.ai OpenAPI spec: the API Reference section in the sidebar is generated from the full machine-readable OpenAPI spec — every /v1 endpoint with its request and response schemas. Point a code generator or a coding agent at the spec to build a typed client. Authentication: All requests require a Bearer token in the Authorization header.

curl https://api.erdo.ai/v1/datasets \
  -H "Authorization: Bearer YOUR_API_KEY"

Getting an API Key

Click your profile in the bottom-left corner of Erdo and go to API Keys. Create a new key and copy the token — it’s shown only once. An API key is an account-level credential: it acts as you, and works in any organization you’re a member of. The organization stored on the key is only its default org — the one used when a request doesn’t name one. It is not a hard scope. To act in a specific organization, send the X-Organization-ID header with the org’s id or slug. The backend validates on every request that you’re a member of that org, so a key can never reach an org you don’t belong to:

# Uses the key's default org
curl https://api.erdo.ai/v1/datasets \
  -H "Authorization: Bearer YOUR_API_KEY"

# Targets a specific org you belong to
curl https://api.erdo.ai/v1/datasets \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "X-Organization-ID: acme"

Manage keys from the CLI too: erdo token create --name ci, erdo token list, erdo token revoke <id>. Set a command’s org with erdo --org acme <command> or change the active default with erdo org use acme.

Scoped Tokens

For building apps where your end-users interact with Erdo, use scoped tokens to restrict access to specific datasets and threads.

API Surface

API keys and scoped tokens work on the documented API surface: every /v1 endpoint, the /mcp endpoint, and the endpoints used by the published SDKs (scoped-token minting, thread messaging, agent invocation, dataset reads). Requests to any other path return 403 permission_denied — other routes are internal to the Erdo app and not a stable contract to build against. If you need a capability that isn’t on /v1 yet, tell us rather than coupling to an internal route.

Datasets

List Datasets

GET /v1/datasets

Returns all datasets in your organization.

Parameter	Type	Description
`limit`	number	Max results (default 20, max 100)
`offset`	number	Pagination offset

curl "https://api.erdo.ai/v1/datasets?limit=10" \
  -H "Authorization: Bearer YOUR_API_KEY"

{
  "datasets": [
    {
      "id": "uuid",
      "slug": "my-org.sales-data",
      "name": "Sales Data",
      "description": "Monthly sales figures",
      "type": "file",
      "status": "active"
    }
  ],
  "total": 42
}

Create Dataset

POST /v1/datasets-create

Create a new empty dataset. Uses your organization’s default storage backend. After creation, use Write Rows to add data.

Parameter	Type	Description
`name`	string	Name for the dataset
`description`	string	Optional description
`instructions`	string	Optional instructions for AI agents analyzing this dataset

curl -X POST "https://api.erdo.ai/v1/datasets-create" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"name": "Daily Metrics", "description": "Automated metrics from our monitoring pipeline"}'

{
  "id": "uuid",
  "slug": "my-org.daily-metrics",
  "name": "Daily Metrics",
  "description": "Automated metrics from our monitoring pipeline",
  "type": "file",
  "status": "active"
}

Upload a File as a Dataset

POST /v1/datasets-upload

Upload a file and create a dataset from it in one call. The file’s schema is extracted before the response returns, so the dataset is immediately queryable. Prefer this over Create Dataset + Write Rows when your data already exists as a file.

Parameter	Type	Description
`filename`	string	Filename with extension — drives type detection (`.csv`, `.tsv`, `.xlsx`, `.json`, `.jsonl`, `.pdf`, `.docx`, `.txt`, `.md`, …)
`content_base64`	string	The raw file bytes, base64-encoded (max 20 MB decoded; use the web app’s resumable upload for larger files)
`name`	string	Optional display name; defaults to the filename
`description`	string	Optional description shown to AI agents analyzing the dataset

# base64 -w0 keeps the output on one line (GNU coreutils wraps at 76 cols by
# default, which would break the JSON string); on macOS `base64 -i leads.csv`.
curl -X POST "https://api.erdo.ai/v1/datasets-upload" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d "{\"filename\": \"leads.csv\", \"name\": \"Leads\", \"content_base64\": \"$(base64 -w0 leads.csv)\"}"

ready reports whether schema extraction succeeded; when false, the file stored but is not yet queryable (a warning explains why).

{
  "dataset_id": "uuid",
  "slug": "my-org.leads",
  "name": "Leads",
  "ready": true
}

Delete Dataset

DELETE /v1/datasets/:slug

Permanently delete a dataset and all its data. Requires admin permission on the dataset.

curl -X DELETE "https://api.erdo.ai/v1/datasets/my-org.daily-metrics" \
  -H "Authorization: Bearer YOUR_API_KEY"

Search Datasets

GET /v1/datasets-search

Search datasets by name.

Parameter	Type	Description
`query`	string	Search text

curl "https://api.erdo.ai/v1/datasets-search?query=revenue" \
  -H "Authorization: Bearer YOUR_API_KEY"

Get Dataset Schema

GET /v1/datasets/:id/schema

Get detailed schema for a dataset including column names, types, statistics, and sample data. Call this before writing data to understand the column structure.

curl "https://api.erdo.ai/v1/datasets/my-dataset-uuid/schema" \
  -H "Authorization: Bearer YOUR_API_KEY"

Query Dataset (SQL)

POST /v1/datasets/:slug/query

Run a SQL query against a dataset. The SQL dialect depends on the storage backend (PostgreSQL, ClickHouse, or DuckDB for file datasets).

Parameter	Type	Description
`query`	string	SQL query to execute
`limit`	number	Max rows (default 100)

curl -X POST "https://api.erdo.ai/v1/datasets/my-org.sales-data/query" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"query": "SELECT * FROM data WHERE revenue > 10000 ORDER BY date DESC", "limit": 50}'

{
  "columns": ["date", "revenue", "orders"],
  "rows": [["2025-03-15", "42300", "156"], ["2025-03-14", "38900", "142"]],
  "row_count": 2
}

For file datasets (CSV/Excel), the table name is always data. For database datasets, use the actual table name from the schema.

Query Dataset (Natural Language)

POST /v1/datasets/:slug/query-nl

Query a dataset using natural language. Erdo generates and executes the correct SQL for you.

Parameter	Type	Description
`question`	string	Natural language question

curl -X POST "https://api.erdo.ai/v1/datasets/my-org.sales-data/query-nl" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"question": "What were the top 5 products by revenue last month?"}'

Fetch Dataset Contents

POST /v1/datasets/:slug/fetch

Fetch raw contents of a dataset without writing SQL.

Parameter	Type	Description
`limit`	number	Max rows (default 1000)
`sql_query`	string	Optional SQL filter

Get Dataset Context

GET /v1/dataset-context

Get detailed context for multiple datasets at once — schemas, column types, statistics, and sample data.

Parameter	Type	Description
`dataset_slugs`	string[]	Specific dataset slugs (empty = all)
`limit`	number	Max datasets (default 10)

Writing Data

Write data into your datasets from any application. Rows are written to whatever storage backend the dataset uses (Postgres, ClickHouse, or CSV file storage).

Write Rows

POST /v1/datasets/:slug/rows

Write or upsert rows to a dataset.

Parameter	Type	Description
`rows`	object[]	Array of row objects with column names as keys
`key_column`	string	Optional. Column to upsert on (update existing, insert new)

Append rows (no key column):

curl -X POST "https://api.erdo.ai/v1/datasets/my-org.metrics/rows" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "rows": [
      {"date": "2025-03-17", "revenue": 42300, "orders": 156},
      {"date": "2025-03-18", "revenue": 45100, "orders": 163}
    ]
  }'

Upsert rows (with key column):

curl -X POST "https://api.erdo.ai/v1/datasets/my-org.metrics/rows" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "rows": [
      {"date": "2025-03-17", "revenue": 43500, "orders": 160}
    ],
    "key_column": "date"
  }'

{
  "rows_affected": 2
}

Storage-specific behavior:

Storage	Append	Upsert (`key_column`)	Notes
Postgres	Insert rows	`ON CONFLICT DO UPDATE`	Key column must have a unique constraint
ClickHouse	Batch insert	Insert (use ReplacingMergeTree for dedup)
CSV/File	Append to CSV	Not supported (always appends)	New columns are added automatically

Delete Rows

DELETE /v1/datasets/:slug/rows

Delete rows from a dataset. Works for both file (CSV) and database-backed datasets.

Parameter	Type	Description
`key_column`	string	Column to match against
`keys`	string[]	Values to delete. Empty = delete all rows.

curl -X DELETE "https://api.erdo.ai/v1/datasets/my-org.metrics/rows" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"key_column": "date", "keys": ["2025-03-17"]}'

{
  "rows_affected": 1
}

Update Schema

POST /v1/datasets/:slug/schema

Update a dataset’s schema: add, remove, rename columns, or change column types. Operations are applied atomically — if any fails, none are applied. Supported for CSV file datasets only. After changes, column analysis is automatically refreshed.

Parameter	Type	Description
`operations`	object[]	Array of schema operations

Each operation object:

Field	Type	Description
`type`	string	`add_column`, `remove_column`, `rename_column`, or `alter_column_type`
`column`	string	Target column name
`new_name`	string	New name (for `rename_column` only)
`column_type`	string	Type hint: `text`, `integer`, `float`, `date`, `boolean` (for `add_column` and `alter_column_type`)

curl -X POST "https://api.erdo.ai/v1/datasets/my-org.metrics/schema" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "operations": [
      {"type": "add_column", "column": "region", "column_type": "text"},
      {"type": "rename_column", "column": "rev", "new_name": "revenue"},
      {"type": "alter_column_type", "column": "revenue", "column_type": "float"},
      {"type": "remove_column", "column": "temp_notes"}
    ]
  }'

{
  "columns_added": 1,
  "columns_removed": 1,
  "columns_renamed": 1,
  "columns_retyped": 1,
  "current_columns": ["date", "revenue", "region"]
}

Ask Questions

Ask a Data Question

POST /v1/ask

Ask a natural language question about your data. Invokes an AI agent that analyzes datasets, writes code, and returns a text answer.

Can take 30 seconds to 2 minutes for complex questions.

Parameter	Type	Description
`question`	string	The data question
`dataset_slugs`	string[]	Optional. Scope to specific datasets.
`timezone`	string	Optional. e.g. `America/New_York`

curl -X POST "https://api.erdo.ai/v1/ask" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"question": "What were total sales last quarter?", "dataset_slugs": ["my-org.sales-data"]}'

{
  "thread_id": "uuid",
  "status": "success",
  "answer": "Total sales last quarter were $1.2M, up 15% from the previous quarter..."
}

Integrations

Connect third-party apps and data sources so Erdo can use them — in agent runs, data questions, and datasets. Credential-based integrations (databases, API keys, service accounts) connect in a single call. OAuth-based integrations return a connect_url for the user to authorize in a browser; polling the status endpoint completes the connection.

List Integrations

GET /v1/integrations

Returns the integrations connected in your organization.

curl "https://api.erdo.ai/v1/integrations" \
  -H "Authorization: Bearer YOUR_API_KEY"

{
  "integrations": [
    {
      "id": "uuid",
      "app": "postgres",
      "name": "Production DB",
      "status": "active",
      "auth_type": "database",
      "type": "database"
    }
  ]
}

Search Connectable Apps

GET /v1/integration-apps?query=slack

Search apps that can be connected: native integrations (databases, warehouses, APIs) and thousands of SaaS apps. The auth_types field tells you how connection works — database, api_key, service_account, and basic connect directly with credentials, while OAuth-based apps go through a browser authorization step.

Parameter	Type	Description
`query`	string	Optional search term. Empty lists native integrations plus popular apps.

{
  "apps": [
    { "app": "slack", "name": "Slack", "auth_types": ["oauth"], "source": "pipedream" },
    { "app": "postgres", "name": "PostgreSQL", "auth_types": ["database"], "source": "native" }
  ]
}

Connect an Integration

POST /v1/integrations-connect

Parameter	Type	Description
`app`	string	App identifier from Search Connectable Apps
`name`	string	Optional display name for the connection
`credentials`	object	Credentials for credential-based apps. Omit for OAuth apps.
`scopes`	array	Optional scopes to grant; defaults to all the app supports
`return_url`	string	Optional absolute `http(s)` URL to send the user’s browser to after they authorize an OAuth app at `connect_url`. Defaults to Erdo’s data page; pass your own page when you embed the connect flow in your product so the user lands back on it. Ignored for credential-based apps that connect in one call.

Connecting a database — created, verified, and activated in one call:

curl -X POST "https://api.erdo.ai/v1/integrations-connect" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "app": "postgres",
    "credentials": {
      "host": "db.example.com", "port": "5432",
      "database": "analytics", "username": "readonly", "password": "..."
    }
  }'

{ "app": "postgres", "integration_id": "uuid", "status": "active" }

Connecting an OAuth app — the response carries a connect_url to open in a browser. Pass return_url when you embed the flow in your own product so the user’s browser lands back on your page (not Erdo’s) after authorizing:

curl -X POST "https://api.erdo.ai/v1/integrations-connect" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"app": "slack", "return_url": "https://portal.example.com/integrations/done"}'

{
  "app": "slack",
  "status": "pending",
  "connect_url": "https://...",
  "next_step": "Have the user open connect_url in a browser and authorize slack, then check the connection status for app=\"slack\" to confirm."
}

If verification fails for a credential-based app (wrong password, unreachable host), the call returns an error and nothing is left behind — fix the credentials and retry.

Check Connection Status

GET /v1/integrations-connect/:app

Reports whether an app is connected. For browser-authorized apps this also completes any connection the user finished since the connect call — poll it after the user opens the connect_url.

curl "https://api.erdo.ai/v1/integrations-connect/slack" \
  -H "Authorization: Bearer YOUR_API_KEY"

{
  "app": "slack",
  "connected": true,
  "integrations": [
    { "id": "uuid", "app": "slack", "name": "Slack ([email protected])", "status": "connected" }
  ],
  "note": "1 new connection(s) confirmed."
}

Discover Tables

GET /v1/integrations/:integration/tables

Discover what a connected database integration exposes. :integration is the app key (e.g. postgres) or, when several instances of the same app are connected, the integration id. Without schema_name it lists the selectable schemas (all SQL databases and warehouses). With schema_name it lists that schema’s tables with columns, types, and row estimates — supported for SQL databases (Postgres, MySQL, and compatible); warehouses (BigQuery, Snowflake, ClickHouse) list schemas but not per-table columns here.

Parameter	Type	Description
`schema_name`	string	Optional. Schema to list tables for.

curl "https://api.erdo.ai/v1/integrations/postgres/tables?schema_name=public" \
  -H "Authorization: Bearer YOUR_API_KEY"

{
  "integration_id": "uuid",
  "app": "postgres",
  "schemas": [{ "id": "public", "name": "public", "type": "schema" }],
  "tables": [
    {
      "schema_name": "public",
      "table_name": "orders",
      "columns": [{ "name": "id", "data_type": "uuid", "is_nullable": false, "is_primary_key": true }],
      "estimated_row_count": 12840
    }
  ]
}

Create a Dataset from an Integration

POST /v1/integration-datasets

Create a dataset backed by a connected database integration, making its data queryable in Erdo without copying it — queries run live against the source. Pick schemas with Discover Tables first; integrations that expose schemas require a selection (some allow only one). Apps that expose no schemas and no queryable data — Slack, Stripe, GitHub and the like — are rejected. Table and column discovery runs in the background after creation and the dataset schema appears within seconds, after which Query Dataset works against the returned slug.

Parameter	Type	Description
`integration`	string	App key (e.g. `postgres`) or integration id
`name`	string	Display name for the dataset
`description`	string	Optional description shown to AI agents
`schemas`	string[]	Selectable schema names (or ids) to include, from Discover Tables

curl -X POST "https://api.erdo.ai/v1/integration-datasets" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"integration": "postgres", "name": "Production DB", "schemas": ["public"]}'

{
  "dataset_id": "uuid",
  "slug": "my-org.production-db",
  "name": "Production DB",
  "status": "active"
}

Threads & Conversations

List Threads

GET /v1/threads

Parameter	Type	Description
`limit`	number	Max results (default 20)
`offset`	number	Pagination offset

Get Thread Messages

GET /v1/threads/:id/messages

Get all messages from a conversation thread.

Create Thread

POST /v1/threads-create

Parameter	Type	Description
`name`	string	Optional thread name
`dataset_ids`	string[]	Optional dataset UUIDs to attach

Send Message

POST /v1/threads/:id/send

Send a message to a thread and get an AI-generated response.

Can take 30 seconds to 2 minutes.

Parameter	Type	Description
`message`	string	The message
`agent_key`	string	Optional. Default: `erdo.data-question-answerer`
`timezone`	string	Optional timezone

Memories & Skills

Memories store reusable knowledge and instructions that Erdo’s AI uses in future conversations.

Create Memory

POST /v1/memories

Parameter	Type	Description
`title`	string	Short title
`content`	string	The content or instructions
`description`	string	Brief description
`type`	string	`snippet` (knowledge) or `skill` (instructions)
`category`	string	Optional category
`tags`	string[]	Optional tags
`dataset_ids`	string[]	Optional associated dataset UUIDs

Search Memories

GET /v1/memories-search

Parameter	Type	Description
`query`	string	Search text
`limit`	number	Max results (default 10)

List Memories

GET /v1/memories

Parameter	Type	Description
`type`	string	Optional filter: `snippet` or `skill`
`category`	string	Optional category filter
`limit`	number	Max results (default 20)
`offset`	number	Pagination offset

Delete Memory

DELETE /v1/memories/:id

Soft delete — can be recovered.

Artifacts

Artifacts are AI-generated outputs from agent runs — insights, metrics, alerts, and tables.

List Artifacts

GET /v1/artifacts

Parameter	Type	Description
`type`	string	Optional: `insight`, `chart`, `metric`, `alert`, `table`, `suggestion`
`limit`	number	Max results (default 20)
`offset`	number	Pagination offset

Get Artifact

GET /v1/artifacts/:id

Screenshots

Capture a public web page to a PNG and get a signed, time-limited download URL. Only works on URLs reachable without login (a marketing site, a published Erdo page at https://pages.erdo.ai/p/{id}, etc.).

POST /v1/screenshot

curl -X POST "https://api.erdo.ai/v1/screenshot" \
  -H "Authorization: Bearer $ERDO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"url": "https://pages.erdo.ai/p/abc123", "full_page": true}'

Response: signed_url, bucket_key, media_type, width, height, expires_at.

Pages

Deploy authenticated, data-wired HTML apps to Erdo over HTTP — the same surface as the erdo_deploy_page MCP tools, for CI and scripts. See the Build Apps on Erdo guide for the page runtime, the window.erdo client, and the read/write model.

Deploy Page

POST /v1/pages

Parameter	Type	Description
`title`	string	Page title shown in Erdo
`html`	string	Full document or fragment. With the `react-tailwind` runtime, include a root element and put React code in `js`
`css`	string	Optional. Stylesheet
`js`	string	Optional. JavaScript/JSX; `window.erdo` is available
`runtime`	string	Optional. `react-tailwind` (default) or `none`
`dataset_slugs`	string[]	Optional. Datasets the page reads — granted read access (you must be able to view them); unknown slugs are a hard error
`public`	boolean	Optional. `true` makes the page publicly viewable (view-only). Default `false`

Returns the page id, editor url, optional public_url, and structured validation results. A deploy with validation errors still saves — fix them and iterate.

curl -X POST "https://api.erdo.ai/v1/pages" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "title": "Sales Dashboard",
    "html": "<div id=\"root\"></div>",
    "js": "const {rows} = await erdo.queryDataset(\"acme.sales\", {limit: 1000}); /* render */",
    "dataset_slugs": ["acme.sales"],
    "public": false
  }'

Update Page

PUT /v1/pages/:pageID

Provided fields are merged — send only js to fix a script without resending html/css. Omit any field to keep its current value. dataset_slugs replaces the current grants; public toggles visibility. Returns fresh validation results.

Validate Page

POST /v1/pages/validate

Dry-run validation without deploying: HTML structure, JS/JSX syntax and runtime smoke checks, window.erdo usage, and dataset-slug references. Accepts html (required), css, js, runtime, and dataset_slugs.

Automations (Heartbeats)

Heartbeats are recurring agents that analyze your data on a schedule.

List Heartbeats

GET /v1/heartbeats

Parameter	Type	Description
`limit`	number	Max results (default 20)
`offset`	number	Pagination offset

Create Heartbeat

POST /v1/heartbeats

Parameter	Type	Description
`name`	string	Name
`instructions`	string	What to do on each run
`interval_minutes`	number	Run frequency (min 5)
`description`	string	Optional description
`timezone`	string	Optional (default UTC)
`active_window_start`	string	Optional. e.g. `09:00`
`active_window_end`	string	Optional. e.g. `18:00`
`active_days`	number[]	Optional. 0=Sun..6=Sat
`dataset_ids`	string[]	Optional dataset UUIDs
`effort`	string	Optional: `low`, `medium`, `high`

curl -X POST "https://api.erdo.ai/v1/heartbeats" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "Revenue monitor",
    "instructions": "Check daily revenue for anomalies and alert if down >10% vs last week",
    "interval_minutes": 60,
    "dataset_ids": ["dataset-uuid"],
    "active_window_start": "09:00",
    "active_window_end": "18:00",
    "timezone": "America/New_York"
  }'

Run Heartbeat

POST /v1/heartbeats/:id/run

Trigger a heartbeat immediately, outside its schedule.

List Heartbeat Executions

GET /v1/heartbeats/:id/executions

Parameter	Type	Description
`limit`	number	Max results (default 10)

Rendering

Render Chart

POST /v1/render/chart

Render a data visualization. Supports bar, line, pie, histogram, and scatter charts. See MCP docs for full schema.

Render Table

POST /v1/render/table

Render a data table. See MCP docs for full schema.

​REST API

​Getting an API Key

​Scoped Tokens

​API Surface

​Datasets

​List Datasets

​Create Dataset

​Upload a File as a Dataset

​Delete Dataset

​Search Datasets

​Get Dataset Schema

​Query Dataset (SQL)

​Query Dataset (Natural Language)

​Fetch Dataset Contents

​Get Dataset Context

​Writing Data

​Write Rows

​Delete Rows

​Update Schema

​Ask Questions

​Ask a Data Question

​Integrations

​List Integrations

​Search Connectable Apps

​Connect an Integration

​Check Connection Status

​Discover Tables

​Create a Dataset from an Integration

​Threads & Conversations

​List Threads

​Get Thread Messages

​Create Thread

​Send Message

​Memories & Skills

​Create Memory

​Search Memories

​List Memories

​Delete Memory

​Artifacts

​List Artifacts

​Get Artifact

​Screenshots

​Pages

​Deploy Page

​Update Page

​Validate Page

​Automations (Heartbeats)

​List Heartbeats

​Create Heartbeat

​Run Heartbeat

​List Heartbeat Executions

​Rendering

​Render Chart

​Render Table

REST API

Getting an API Key

Scoped Tokens

API Surface

Datasets

List Datasets

Create Dataset

Upload a File as a Dataset

Delete Dataset

Search Datasets

Get Dataset Schema

Query Dataset (SQL)

Query Dataset (Natural Language)

Fetch Dataset Contents

Get Dataset Context

Writing Data

Write Rows

Delete Rows

Update Schema

Ask Questions

Ask a Data Question

Integrations

List Integrations

Search Connectable Apps

Connect an Integration

Check Connection Status

Discover Tables

Create a Dataset from an Integration

Threads & Conversations

List Threads

Get Thread Messages

Create Thread

Send Message

Memories & Skills

Create Memory

Search Memories

List Memories

Delete Memory

Artifacts

List Artifacts

Get Artifact

Screenshots

Pages

Deploy Page

Update Page

Validate Page

Automations (Heartbeats)

List Heartbeats

Create Heartbeat

Run Heartbeat

List Heartbeat Executions

Rendering

Render Chart

Render Table