71
Plugins
223
Modules
152,151
Monthly Downloads
9
Categories
Popular Plugins
Kubernetes Pod
flytekitplugins-pod
By default, Flyte tasks decorated with @task are essentially single functions that are loaded in one container. But often, there is a need to run a job with more than one container.
Deck
flytekitplugins-deck-standard
This plugin provides additional renderers to improve task visibility within Flytekit.
Kubeflow MPI
flytekitplugins-kfmpi
This plugin uses the Kubeflow MPI Operator and provides an extremely simplified interface for executing distributed training.
OmegaConf
flytekitplugins-omegaconf
Flytekit python natively supports serialization of many data types for exchanging information between tasks.
JSONL (JSON Lines) Type Plugin
flyteplugins-jsonl
JSONL (JSON Lines) file and directory types for Flyte, backed by orjson for
Bigquery
flytekitplugins-bigquery
BigQuery enables us to build data-intensive applications without operational burden. Flyte backend can be connected with the BigQuery service. Once enabled, it can allow you to query a BigQuery table.
Polars
flytekitplugins-polars
Polars is a blazingly fast DataFrames library implemented in Rust using Apache Arrow Columnar Format as memory model.
DBT
flytekitplugins-dbt
Flytekit plugin for performing DBT tasks. Currently it supports dbt run , dbt test, dbt source freshness tasks.
Kubernetes Pod
flytekitplugins-pod
By default, Flyte tasks decorated with @task are essentially single functions that are loaded in one container. But often, there is a need to run a job with more than one container.
Deck
flytekitplugins-deck-standard
This plugin provides additional renderers to improve task visibility within Flytekit.
Kubeflow MPI
flytekitplugins-kfmpi
This plugin uses the Kubeflow MPI Operator and provides an extremely simplified interface for executing distributed training.
OmegaConf
flytekitplugins-omegaconf
Flytekit python natively supports serialization of many data types for exchanging information between tasks.
JSONL (JSON Lines) Type Plugin
flyteplugins-jsonl
JSONL (JSON Lines) file and directory types for Flyte, backed by orjson for
Bigquery
flytekitplugins-bigquery
BigQuery enables us to build data-intensive applications without operational burden. Flyte backend can be connected with the BigQuery service. Once enabled, it can allow you to query a BigQuery table.
Polars
flytekitplugins-polars
Polars is a blazingly fast DataFrames library implemented in Rust using Apache Arrow Columnar Format as memory model.
DBT
flytekitplugins-dbt
Flytekit plugin for performing DBT tasks. Currently it supports dbt run , dbt test, dbt source freshness tasks.
Kubernetes Pod
flytekitplugins-pod
By default, Flyte tasks decorated with @task are essentially single functions that are loaded in one container. But often, there is a need to run a job with more than one container.
Deck
flytekitplugins-deck-standard
This plugin provides additional renderers to improve task visibility within Flytekit.
Kubeflow MPI
flytekitplugins-kfmpi
This plugin uses the Kubeflow MPI Operator and provides an extremely simplified interface for executing distributed training.
OmegaConf
flytekitplugins-omegaconf
Flytekit python natively supports serialization of many data types for exchanging information between tasks.
JSONL (JSON Lines) Type Plugin
flyteplugins-jsonl
JSONL (JSON Lines) file and directory types for Flyte, backed by orjson for
Bigquery
flytekitplugins-bigquery
BigQuery enables us to build data-intensive applications without operational burden. Flyte backend can be connected with the BigQuery service. Once enabled, it can allow you to query a BigQuery table.
Polars
flytekitplugins-polars
Polars is a blazingly fast DataFrames library implemented in Rust using Apache Arrow Columnar Format as memory model.
DBT
flytekitplugins-dbt
Flytekit plugin for performing DBT tasks. Currently it supports dbt run , dbt test, dbt source freshness tasks.
Kubernetes Pod
flytekitplugins-pod
By default, Flyte tasks decorated with @task are essentially single functions that are loaded in one container. But often, there is a need to run a job with more than one container.
Deck
flytekitplugins-deck-standard
This plugin provides additional renderers to improve task visibility within Flytekit.
Kubeflow MPI
flytekitplugins-kfmpi
This plugin uses the Kubeflow MPI Operator and provides an extremely simplified interface for executing distributed training.
OmegaConf
flytekitplugins-omegaconf
Flytekit python natively supports serialization of many data types for exchanging information between tasks.
JSONL (JSON Lines) Type Plugin
flyteplugins-jsonl
JSONL (JSON Lines) file and directory types for Flyte, backed by orjson for
Bigquery
flytekitplugins-bigquery
BigQuery enables us to build data-intensive applications without operational burden. Flyte backend can be connected with the BigQuery service. Once enabled, it can allow you to query a BigQuery table.
Polars
flytekitplugins-polars
Polars is a blazingly fast DataFrames library implemented in Rust using Apache Arrow Columnar Format as memory model.
DBT
flytekitplugins-dbt
Flytekit plugin for performing DBT tasks. Currently it supports dbt run , dbt test, dbt source freshness tasks.
Great Expectations
flytekitplugins-great_expectations
Great Expectations helps enforce data quality. The plugin supports the usage of Great Expectations as task and type.
Dask
flytekitplugins-dask
Flyte can execute dask jobs natively on a Kubernetes Cluster, which manages the virtual dask cluster's lifecycle
OpenAI
flyteplugins-openai
This plugin provides a drop-in replacement for OpenAI packages. It provides
Databricks
flyteplugins-databricks
This plugin provides Databricks integration for Flyte, enabling you to run Spark jobs on Databricks as Flyte tasks.
AWS Athena
flytekitplugins-athena
Flyte backend can be connected with Athena. Once enabled, it allows you to query AWS Athena service (Presto + ANSI SQL Support) and retrieve typed schema (optionally).
FSSpec
flytekitplugins-data-fsspec
This plugin provides an implementation of the data persistence layer in Flytekit that uses fsspec. Once this plugin
AWS SageMaker
flytekitplugins-awssagemaker
The plugin currently features a SageMaker deployment connector.
Human-in-the-Loop (HITL)
flyteplugins-hitl
Human-in-the-Loop (HITL) plugin for Flyte. This plugin provides an event-based API for pausing workflows and waiting for human input.
Great Expectations
flytekitplugins-great_expectations
Great Expectations helps enforce data quality. The plugin supports the usage of Great Expectations as task and type.
Dask
flytekitplugins-dask
Flyte can execute dask jobs natively on a Kubernetes Cluster, which manages the virtual dask cluster's lifecycle
OpenAI
flyteplugins-openai
This plugin provides a drop-in replacement for OpenAI packages. It provides
Databricks
flyteplugins-databricks
This plugin provides Databricks integration for Flyte, enabling you to run Spark jobs on Databricks as Flyte tasks.
AWS Athena
flytekitplugins-athena
Flyte backend can be connected with Athena. Once enabled, it allows you to query AWS Athena service (Presto + ANSI SQL Support) and retrieve typed schema (optionally).
FSSpec
flytekitplugins-data-fsspec
This plugin provides an implementation of the data persistence layer in Flytekit that uses fsspec. Once this plugin
AWS SageMaker
flytekitplugins-awssagemaker
The plugin currently features a SageMaker deployment connector.
Human-in-the-Loop (HITL)
flyteplugins-hitl
Human-in-the-Loop (HITL) plugin for Flyte. This plugin provides an event-based API for pausing workflows and waiting for human input.
Great Expectations
flytekitplugins-great_expectations
Great Expectations helps enforce data quality. The plugin supports the usage of Great Expectations as task and type.
Dask
flytekitplugins-dask
Flyte can execute dask jobs natively on a Kubernetes Cluster, which manages the virtual dask cluster's lifecycle
OpenAI
flyteplugins-openai
This plugin provides a drop-in replacement for OpenAI packages. It provides
Databricks
flyteplugins-databricks
This plugin provides Databricks integration for Flyte, enabling you to run Spark jobs on Databricks as Flyte tasks.
AWS Athena
flytekitplugins-athena
Flyte backend can be connected with Athena. Once enabled, it allows you to query AWS Athena service (Presto + ANSI SQL Support) and retrieve typed schema (optionally).
FSSpec
flytekitplugins-data-fsspec
This plugin provides an implementation of the data persistence layer in Flytekit that uses fsspec. Once this plugin
AWS SageMaker
flytekitplugins-awssagemaker
The plugin currently features a SageMaker deployment connector.
Human-in-the-Loop (HITL)
flyteplugins-hitl
Human-in-the-Loop (HITL) plugin for Flyte. This plugin provides an event-based API for pausing workflows and waiting for human input.
Great Expectations
flytekitplugins-great_expectations
Great Expectations helps enforce data quality. The plugin supports the usage of Great Expectations as task and type.
Dask
flytekitplugins-dask
Flyte can execute dask jobs natively on a Kubernetes Cluster, which manages the virtual dask cluster's lifecycle
OpenAI
flyteplugins-openai
This plugin provides a drop-in replacement for OpenAI packages. It provides
Databricks
flyteplugins-databricks
This plugin provides Databricks integration for Flyte, enabling you to run Spark jobs on Databricks as Flyte tasks.
AWS Athena
flytekitplugins-athena
Flyte backend can be connected with Athena. Once enabled, it allows you to query AWS Athena service (Presto + ANSI SQL Support) and retrieve typed schema (optionally).
FSSpec
flytekitplugins-data-fsspec
This plugin provides an implementation of the data persistence layer in Flytekit that uses fsspec. Once this plugin
AWS SageMaker
flytekitplugins-awssagemaker
The plugin currently features a SageMaker deployment connector.
Human-in-the-Loop (HITL)
flyteplugins-hitl
Human-in-the-Loop (HITL) plugin for Flyte. This plugin provides an event-based API for pausing workflows and waiting for human input.
Recently Added
BigQuery
v2Flyte SDK (v2)flyteplugins-bigquery
This plugin provides BigQuery integration for Flyte, enabling you to run BigQuery queries as Flyte tasks.
Databricks
v2Flyte SDK (v2)flyteplugins-databricks
This plugin provides Databricks integration for Flyte, enabling you to run Spark jobs on Databricks as Flyte tasks.
Snowflake
v2Flyte SDK (v2)flyteplugins-snowflake
Run Snowflake SQL queries as Flyte tasks with parameterized inputs, key-pair authentication, batch inserts, and DataFrame support.
polars
v2Flyte SDK (v2)flyteplugins-polars
This plugin provides native support for Polars DataFrames and LazyFrames in Flyte, enabling efficient data processing with Polars' high-performance DataFrame library.
Weights & Biases
v2Flyte SDK (v2)flyteplugins-wandb
This plugin provides integration between Flyte and Weights & Biases (W&B) for experiment tracking, including support for distributed training with PyTorch Elastic.
SGLang
v2Flyte SDK (v2)flyteplugins-sglang
Serve large language models using SGLang with Flyte Apps.
vLLM
v2Flyte SDK (v2)flyteplugins-vllm
Serve large language models using vLLM with Flyte Apps.
Dgxc-lepton
Flytekitflytekitplugins-dgxc-lepton
A professional Flytekit plugin that enables seamless deployment and management of AI inference endpoints using Lepton AI infrastructure within Flyte workflows.
Browse by Category
Data & DataFrame
Databases & Warehouses
Cloud & Infrastructure
ML Training
Model Serving
Experiment Tracking
Data Validation
Workflow
Developer Tools
flyte-mcp: Flyte V2 for AI agents
Give Claude, Cursor, and Claude Code accurate, versioned answers about Flyte V2 without scraping READMEs or hallucinating import paths. 17 tools covering the SDK API, canonical example patterns, plugin registry, V1 to V2 migration, and optional cluster runtime.
Claude Code
claude mcp add flyte -- uvx flyte-mcpTry it: one-shot
uvx flyte-mcpCursor / Claude Desktop (~/.cursor/mcp.json or ~/.claude.json)
{
"mcpServers": {
"flyte": {
"command": "uvx",
"args": ["flyte-mcp"]
}
}
}What the agent can do
get_flyte_symbolFull API detail for any public Flyte V2 symbolsearch_flyte_apiKeyword search over the V2 Python APIget_flyte_patternCanonical example code by theme (caching, GPU, GenAI, ...)find_flyte_example_forNatural-language match to example themessuggest_flyte_plugin_forPlugin recommendation, prefers V2 entriesmigrate_v1_to_v2Rewrite flytekit V1 code to flyte-sdk V2 syntaxrun_flyte_taskExecute a task on the configured Flyte cluster
Get Involved
Learn, connect, and contribute to the Flyte ecosystem.
@task
from flytekit import task, workflow
@workflow
def my_pipeline(data: str) -> int:
ImageSpec
image = ImageSpec(packages=["pandas"])
map_task
map_task(process)(data=inputs)
Resources
requests=Resources(cpu="2", mem="4Gi")
Secret
secret=Secret(group="aws", key="s3")
@task
from flytekit import task, workflow
@workflow
def my_pipeline(data: str) -> int:
ImageSpec
image = ImageSpec(packages=["pandas"])
map_task
map_task(process)(data=inputs)
Resources
requests=Resources(cpu="2", mem="4Gi")
Secret
secret=Secret(group="aws", key="s3")
@task
from flytekit import task, workflow
@workflow
def my_pipeline(data: str) -> int:
ImageSpec
image = ImageSpec(packages=["pandas"])
map_task
map_task(process)(data=inputs)
Resources
requests=Resources(cpu="2", mem="4Gi")
Secret
secret=Secret(group="aws", key="s3")
@task
from flytekit import task, workflow
@workflow
def my_pipeline(data: str) -> int:
ImageSpec
image = ImageSpec(packages=["pandas"])
map_task
map_task(process)(data=inputs)
Resources
requests=Resources(cpu="2", mem="4Gi")
Secret
secret=Secret(group="aws", key="s3")
Documentation
Learn how to build, test, and publish your own Flyte plugins.
Community
Join thousands of developers on Slack to discuss Flyte and share plugins.
Contribute
Submit your plugin to the registry. Open and extensible.