The SDK can be installed with either npm, pnpm, bun or yarn package managers.
npm add @cloudinary/config
pnpm add @cloudinary/config
bun add @cloudinary/config
yarn add @cloudinary/config zod
# Note that Yarn does not install peer dependencies automatically. You will need
# to install zod as shown above.
This SDK is also an installable MCP server where the various SDK methods are exposed as tools that can be invoked by AI applications.
Node.js v20 or greater is required to run the MCP server from npm.
Claude installation steps
Add the following server definition to your claude_desktop_config.json
file:
{
"mcpServers": {
"CloudinaryConfig": {
"command": "npx",
"args": [
"-y", "--package", "@cloudinary/config",
"--",
"mcp", "start",
"--api-key", "...",
"--api-secret", "...",
"--cloud-name", "..."
]
}
}
}
Cursor installation steps
Create a .cursor/mcp.json
file in your project root with the following content:
{
"mcpServers": {
"CloudinaryConfig": {
"command": "npx",
"args": [
"-y", "--package", "@cloudinary/config",
"--",
"mcp", "start",
"--api-key", "...",
"--api-secret", "...",
"--cloud-name", "..."
]
}
}
}
You can also run MCP servers as a standalone binary with no additional dependencies. You must pull these binaries from available Github releases:
curl -L -o mcp-server \
https://github.com/cloudinary/config-js/releases/download/{tag}/mcp-server-bun-darwin-arm64 && \
chmod +x mcp-server
For a full list of server arguments, run:
npx -y --package @cloudinary/config -- mcp start --help
For supported JavaScript runtimes, please consult RUNTIMES.md.
import { CloudinaryConfig } from "@cloudinary/config";
const cloudinaryConfig = new CloudinaryConfig({
security: {
apiKey: "CLOUDINARY_API_KEY",
apiSecret: "CLOUDINARY_API_SECRET",
},
});
async function run() {
const result = await cloudinaryConfig.transformations.listTransformations({
nextCursor: "8edbc61040178db60b0973ca9494bf3a",
});
// Handle the result
console.log(result);
}
run();
A parameter is configured globally. This parameter may be set on the SDK client instance itself during initialization. When configured as an option during SDK initialization, This global value will be used as the default on the operations that use it. When such operations are called, there is a place in each to override the global value, if needed.
For example, you can set cloud_name
to "<value>"
at SDK initialization and then you do not have to pass the same value on calls to operations like listTransformations
. But if you want to do so you may, which will locally override the global setting. See the example code below for a demonstration.
The following global parameter is available. Global parameters can also be set via environment variable.
Name | Type | Description | Environment |
---|---|---|---|
cloudName | string | The cloud name of your product environment. | CLOUDINARY_CLOUD_NAME |
import { CloudinaryConfig } from "@cloudinary/config";
const cloudinaryConfig = new CloudinaryConfig({
security: {
apiKey: "CLOUDINARY_API_KEY",
apiSecret: "CLOUDINARY_API_SECRET",
},
});
async function run() {
const result = await cloudinaryConfig.transformations.listTransformations({
nextCursor: "8edbc61040178db60b0973ca9494bf3a",
});
// Handle the result
console.log(result);
}
run();
This SDK supports the following security scheme globally:
Name | Type | Scheme | Environment Variable |
---|---|---|---|
apiKey apiSecret |
http | Custom HTTP | CLOUDINARY_API_KEY CLOUDINARY_API_SECRET |
You can set the security parameters through the security
optional parameter when initializing the SDK client instance. For example:
import { CloudinaryConfig } from "@cloudinary/config";
const cloudinaryConfig = new CloudinaryConfig({
security: {
apiKey: "CLOUDINARY_API_KEY",
apiSecret: "CLOUDINARY_API_SECRET",
},
});
async function run() {
const result = await cloudinaryConfig.transformations.listTransformations({
nextCursor: "8edbc61040178db60b0973ca9494bf3a",
});
// Handle the result
console.log(result);
}
run();
Available methods
- createMetadataField - Create a metadata field
- listMetadataFields - Get metadata fields
- getMetadataField - Get metadata field
- updateMetadataField - Update metadata field
- deleteMetadataField - Delete metadata field
- searchMetadataFieldDatasource - Search across all metadata field datasources
- reorderMetadataFields - Reorder all metadata fields
- reorderMetadataField - Change position of metadata field
- updateMetadataFieldDatasource - Update datasource values
- deleteMetadataFieldDatasource - Delete datasource values
- searchDatasourceInMDField - Search datasource values in a metadata field
- restoreMetadataFieldDatasource - Restore datasource values
- createMetadataRule - Create a metadata rule
- listMetadataRules - Get metadata rules
- updateMetadataRule - Update metadata rule
- deleteMetadataRule - Delete metadata rule
- createStreamingProfile - Create streaming profile
- getStreamingProfiles - Get streaming profiles
- getStreamingProfile - Get streaming profile
- updateStreamingProfile - Update streaming profile
- deleteStreamingProfile - Delete custom streaming profile or revert built-in profile to the original settings
- listTransformations - Get transformations
- getTransformation - Get a transformation
- createTransformation - Create a named transformation
- updateTransformation - Update a transformation
- deleteTransformation - Delete a transformation
- listTrigger - Get event triggers
- createTrigger - Create a trigger
- updateTrigger - Update trigger URL
- deleteTrigger - Delete a trigger
- listUploadMappings - Lists upload mappings
- createUploadMapping - Creates an upload mapping
- updateUploadMapping - Updates an upload mapping
- deleteUploadMapping - Deletes an upload mapping
- replaceUploadMappings - Replaces all upload mappings
- createUploadPreset - Creates an upload preset
- listUploadPresets - lists upload presets
- getUploadPreset - Retrieves details of a single upload preset
- updateUploadPreset - Updates an upload preset
- deleteUploadPreset - Deletes an upload preset
All the methods listed above are available as standalone functions. These functions are ideal for use in applications running in the browser, serverless runtimes or other environments where application bundle size is a primary concern. When using a bundler to build your application, all unused functionality will be either excluded from the final bundle or tree-shaken away.
To read more about standalone functions, check FUNCTIONS.md.
Available standalone functions
metadataFieldsCreateMetadataField
- Create a metadata fieldmetadataFieldsDeleteMetadataField
- Delete metadata fieldmetadataFieldsDeleteMetadataFieldDatasource
- Delete datasource valuesmetadataFieldsGetMetadataField
- Get metadata fieldmetadataFieldsListMetadataFields
- Get metadata fieldsmetadataFieldsReorderMetadataField
- Change position of metadata fieldmetadataFieldsReorderMetadataFields
- Reorder all metadata fieldsmetadataFieldsRestoreMetadataFieldDatasource
- Restore datasource valuesmetadataFieldsSearchDatasourceInMDField
- Search datasource values in a metadata fieldmetadataFieldsSearchMetadataFieldDatasource
- Search across all metadata field datasourcesmetadataFieldsUpdateMetadataField
- Update metadata fieldmetadataFieldsUpdateMetadataFieldDatasource
- Update datasource valuesmetadataRulesCreateMetadataRule
- Create a metadata rulemetadataRulesDeleteMetadataRule
- Delete metadata rulemetadataRulesListMetadataRules
- Get metadata rulesmetadataRulesUpdateMetadataRule
- Update metadata rulestreamingProfilesCreateStreamingProfile
- Create streaming profilestreamingProfilesDeleteStreamingProfile
- Delete custom streaming profile or revert built-in profile to the original settingsstreamingProfilesGetStreamingProfile
- Get streaming profilestreamingProfilesGetStreamingProfiles
- Get streaming profilesstreamingProfilesUpdateStreamingProfile
- Update streaming profiletransformationsCreateTransformation
- Create a named transformationtransformationsDeleteTransformation
- Delete a transformationtransformationsGetTransformation
- Get a transformationtransformationsListTransformations
- Get transformationstransformationsUpdateTransformation
- Update a transformationtriggersCreateTrigger
- Create a triggertriggersDeleteTrigger
- Delete a triggertriggersListTrigger
- Get event triggerstriggersUpdateTrigger
- Update trigger URLuploadMappingsCreateUploadMapping
- Creates an upload mappinguploadMappingsDeleteUploadMapping
- Deletes an upload mappinguploadMappingsListUploadMappings
- Lists upload mappingsuploadMappingsReplaceUploadMappings
- Replaces all upload mappingsuploadMappingsUpdateUploadMapping
- Updates an upload mappinguploadPresetsCreateUploadPreset
- Creates an upload presetuploadPresetsDeleteUploadPreset
- Deletes an upload presetuploadPresetsGetUploadPreset
- Retrieves details of a single upload presetuploadPresetsListUploadPresets
- lists upload presetsuploadPresetsUpdateUploadPreset
- Updates an upload preset
Some of the endpoints in this SDK support retries. If you use the SDK without any configuration, it will fall back to the default retry strategy provided by the API. However, the default retry strategy can be overridden on a per-operation basis, or across the entire SDK.
To change the default retry strategy for a single API call, simply provide a retryConfig object to the call:
import { CloudinaryConfig } from "@cloudinary/config";
const cloudinaryConfig = new CloudinaryConfig({
security: {
apiKey: "CLOUDINARY_API_KEY",
apiSecret: "CLOUDINARY_API_SECRET",
},
});
async function run() {
const result = await cloudinaryConfig.transformations.listTransformations({
nextCursor: "8edbc61040178db60b0973ca9494bf3a",
}, {
retries: {
strategy: "backoff",
backoff: {
initialInterval: 1,
maxInterval: 50,
exponent: 1.1,
maxElapsedTime: 100,
},
retryConnectionErrors: false,
},
});
// Handle the result
console.log(result);
}
run();
If you'd like to override the default retry strategy for all operations that support retries, you can provide a retryConfig at SDK initialization:
import { CloudinaryConfig } from "@cloudinary/config";
const cloudinaryConfig = new CloudinaryConfig({
retryConfig: {
strategy: "backoff",
backoff: {
initialInterval: 1,
maxInterval: 50,
exponent: 1.1,
maxElapsedTime: 100,
},
retryConnectionErrors: false,
},
security: {
apiKey: "CLOUDINARY_API_KEY",
apiSecret: "CLOUDINARY_API_SECRET",
},
});
async function run() {
const result = await cloudinaryConfig.transformations.listTransformations({
nextCursor: "8edbc61040178db60b0973ca9494bf3a",
});
// Handle the result
console.log(result);
}
run();
Some methods specify known errors which can be thrown. All the known errors are enumerated in the models/errors/errors.ts
module. The known errors for a method are documented under the Errors tables in SDK docs. For example, the listTransformations
method may throw the following errors:
Error Type | Status Code | Content Type |
---|---|---|
errors.ApiError | 400, 401, 403 | application/json |
errors.SDKError | 4XX, 5XX | */* |
If the method throws an error and it is not captured by the known errors, it will default to throwing a SDKError
.
import { CloudinaryConfig } from "@cloudinary/config";
import { ApiError, SDKValidationError } from "@cloudinary/config/models/errors";
const cloudinaryConfig = new CloudinaryConfig({
security: {
apiKey: "CLOUDINARY_API_KEY",
apiSecret: "CLOUDINARY_API_SECRET",
},
});
async function run() {
let result;
try {
result = await cloudinaryConfig.transformations.listTransformations({
nextCursor: "8edbc61040178db60b0973ca9494bf3a",
});
// Handle the result
console.log(result);
} catch (err) {
switch (true) {
// The server response does not match the expected SDK schema
case (err instanceof SDKValidationError): {
// Pretty-print will provide a human-readable multi-line error message
console.error(err.pretty());
// Raw value may also be inspected
console.error(err.rawValue);
return;
}
case (err instanceof ApiError): {
// Handle err.data$: ApiErrorData
console.error(err);
return;
}
default: {
// Other errors such as network errors, see HTTPClientErrors for more details
throw err;
}
}
}
}
run();
Validation errors can also occur when either method arguments or data returned from the server do not match the expected format. The SDKValidationError
that is thrown as a result will capture the raw value that failed validation in an attribute called rawValue
. Additionally, a pretty()
method is available on this error that can be used to log a nicely formatted multi-line string since validation errors can list many issues and the plain error string may be difficult read when debugging.
In some rare cases, the SDK can fail to get a response from the server or even make the request due to unexpected circumstances such as network conditions. These types of errors are captured in the models/errors/httpclienterrors.ts
module:
HTTP Client Error | Description |
---|---|
RequestAbortedError | HTTP request was aborted by the client |
RequestTimeoutError | HTTP request timed out due to an AbortSignal signal |
ConnectionError | HTTP client was unable to make a request to a server |
InvalidRequestError | Any input used to create a request is invalid |
UnexpectedClientError | Unrecognised or unexpected error |
The default server https://{defaultHost}
contains variables and is set to https://api.cloudinary.com
by default. To override default values, the following parameters are available when initializing the SDK client instance:
Variable | Parameter | Default | Description |
---|---|---|---|
defaultHost |
defaultHost: string |
"api.cloudinary.com" |
The host name for the API endpoint. |
import { CloudinaryConfig } from "@cloudinary/config";
const cloudinaryConfig = new CloudinaryConfig({
defaultHost: "<value>",
security: {
apiKey: "CLOUDINARY_API_KEY",
apiSecret: "CLOUDINARY_API_SECRET",
},
});
async function run() {
const result = await cloudinaryConfig.transformations.listTransformations({
nextCursor: "8edbc61040178db60b0973ca9494bf3a",
});
// Handle the result
console.log(result);
}
run();
The default server can be overridden globally by passing a URL to the serverURL: string
optional parameter when initializing the SDK client instance. For example:
import { CloudinaryConfig } from "@cloudinary/config";
const cloudinaryConfig = new CloudinaryConfig({
serverURL: "https://api.cloudinary.com",
security: {
apiKey: "CLOUDINARY_API_KEY",
apiSecret: "CLOUDINARY_API_SECRET",
},
});
async function run() {
const result = await cloudinaryConfig.transformations.listTransformations({
nextCursor: "8edbc61040178db60b0973ca9494bf3a",
});
// Handle the result
console.log(result);
}
run();
The TypeScript SDK makes API calls using an HTTPClient
that wraps the native
Fetch API. This
client is a thin wrapper around fetch
and provides the ability to attach hooks
around the request lifecycle that can be used to modify the request or handle
errors and response.
The HTTPClient
constructor takes an optional fetcher
argument that can be
used to integrate a third-party HTTP client or when writing tests to mock out
the HTTP client and feed in fixtures.
The following example shows how to use the "beforeRequest"
hook to to add a
custom header and a timeout to requests and how to use the "requestError"
hook
to log errors:
import { CloudinaryConfig } from "@cloudinary/config";
import { HTTPClient } from "@cloudinary/config/lib/http";
const httpClient = new HTTPClient({
// fetcher takes a function that has the same signature as native `fetch`.
fetcher: (request) => {
return fetch(request);
}
});
httpClient.addHook("beforeRequest", (request) => {
const nextRequest = new Request(request, {
signal: request.signal || AbortSignal.timeout(5000)
});
nextRequest.headers.set("x-custom-header", "custom value");
return nextRequest;
});
httpClient.addHook("requestError", (error, request) => {
console.group("Request Error");
console.log("Reason:", `${error}`);
console.log("Endpoint:", `${request.method} ${request.url}`);
console.groupEnd();
});
const sdk = new CloudinaryConfig({ httpClient });
You can setup your SDK to emit debug logs for SDK requests and responses.
You can pass a logger that matches console
's interface as an SDK option.
Warning
Beware that debug logging will reveal secrets, like API tokens in headers, in log messages printed to a console or files. It's recommended to use this feature only during local development and not in production.
import { CloudinaryConfig } from "@cloudinary/config";
const sdk = new CloudinaryConfig({ debugLogger: console });
You can also enable a default debug logger by setting an environment variable CLOUDINARY_DEBUG
to true.