Googleapis

com.googleapis.composerPublished by composer.googleapis.comOfficial publisherv1.0.0Updated Nov 7, 2026

Interact with your Google Cloud Composer resources using natural language commands.

VerifiedStreamable HTTPWeb executableCloud & InfrastructureData & Analytics

Overview

AI-generated overview

Lets an assistant manage Google Cloud Composer (Managed Airflow) environments and inspect their DAGs, runs and task instances in natural language.

What you can do
  • Create, list, inspect and delete Managed Airflow environments, and check long-running operations
  • Install, upgrade or remove PyPI packages in an environment
  • List and read DAGs, including their source code, and check import or parsing errors
  • List DAG runs and task instances, and find recent failed runs or failed tasks
  • Trigger a DAG run manually and poll its state
When to use it
Useful when you operate Google Cloud Composer and want an assistant to check environment status, debug failing DAG runs or task instances, review DAG source code, or make small environment changes such as package updates without switching to the console.
Requirements
A remote endpoint at composer.googleapis.com; no local package. A Google Cloud project with Composer environments, a target project and location for most calls, and Google Cloud authentication/authorization for the connecting client.
Before you install
Deleting an environment is destructive and irreversible, and the tool itself asks for user confirmation first. Creating environments, changing PyPI packages and triggering DAG runs change cloud state and may incur Google Cloud costs. Access is limited to small private-IP environments with default settings for creation.

Installation

In SourceWeft

  1. Open Googleapis in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/com.googleapis.composer%2Fmcp/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config.

{
  "mcpServers": {
    "googleapis": {
      "type": "http",
      "url": "https://composer.googleapis.com/mcp"
    }
  }
}

Tools

16

create_environment

Initiates the creation of a new Managed Airflow environment with default settings. This tool creates a small private IP environment with a default configuration, including default networking settings. Creating public IP environments, or customizing most settings (such as network, subnetwork, network attachment, environment size, CMEK or custom environment bucket) is not supported. If the user requests settings that aren't supported by the tool parameters, inform them that this tool can't create an environment in the requested configuration, and that they should use gcloud CLI or Cloud Console instead. Some environment configuration parameters are mandatory. Always ask about them: - Always ask the user to provide a service account that they want to use for their environment. Users are strongly recommended to use a dedicated user-managed service account and are discouraged from using the default Cloud Compute service account for security reasons. - Always ask the user to specify the IP ranges that they want to use to access the Airflow UI and web server. If the user doesn't specify IP ranges, clarify that the default is not allowing access from any IPs. We also recommend to not allow access from all IP addresses to avoid potential security risks. This tool creates an environment without pre-installed PyPI packages. Use the `manage_pypi_packages` tool to install PyPI packages after the environment is created. This tool triggers the environment creation process, which is a long-running operation. The tool returns an operation object. Use the `get_operation` tool with the operation name returned by this tool to poll for creation status. Environment creation typically takes 25-30 minutes. A completed operation will include the details of the created environment.

ParametersparentrequiredimageVersionenvironmentIdrequiredserviceAccountrequiredallowedWebServerIpRangesrequired

get_environment

Retrieves details about a specific Managed Airflow environment, including its configuration and status. Use this tool to check the current state of an environment, its Airflow version, Airflow UI URL, environment's bucket, or other configuration details.

Parametersname

list_environments

Lists all Managed Airflow environments in a given project and location. Use this tool to when you need to know which environments exist in a specific project and location. Results are paginated; use `page_size` to control the number of results per page and `page_token` from a previous response to get the next page. If `page_token` is not present in the response, there are no more results.

ParametersparentpageSizepageToken

delete_environment

Initiates the deletion of a Managed Airflow environment. Warning: This is a destructive action permanently deletes an environment and can't be undone. Always ask the user to confirm the deletion before proceeding. This tool triggers the environment deletion process, which is a long-running operation that typically takes 10-20 minutes. The tool returns an operation object. Use the `get_operation` tool with the operation name returned by this tool to poll for deletion status.

Parametersname

manage_pypi_packages

Manages PyPI packages in a Managed Airflow environment. Use this tool to install and uninstall PyPI packages in the Managed Airflow environment, or change PyPI package versions or extras. To install packages or change versions or extras, use the `update_packages` field. To remove packages, use the `remove_packages` field. At least one package must be specified in one of these fields. The same package can't be specified in both fields. This tool triggers an environment update, which is a long-running operation that can take several minutes. The tool returns an operation object. Use the `get_operation` tool to poll its status. A completed operation will include the details of the updated environment.

ParametersenvironmentrequiredremovePackagesupdatePackages

get_operation

Gets the latest status of a long-running operation. Several tools like `create_environment`, `delete_environments`, and `manage_pypi_packages` return an operation object, because they initiate processes that take time to complete. Use this tool to check if such an operation has finished and whether it was successful. Provide the `name` of the operation as returned by the tool that initiated it. A completed operation may include the details specific to the operation, described in the description of the tool that initiates the operation.

Parametersname

get_dag

Retrieves metadata and status of a specific DAG in a Managed Airflow environment. Use this tool when you need to check if a DAG exists, inspect its metadata (such as schedule or current state), or verify whether a newly uploaded/updated DAG file has been imported by Airflow (see `list_import_errors` tool description for more details). In particular, if a DAG was recently uploaded but `get_dag` returns NOT_FOUND, use `list_import_errors` to check if any errors occurred during the import.

ParametersdagIdrequiredenvironmentrequired

list_dags

Lists all DAGs in a Managed Airflow environment. Use this tool to get a list of all DAGs in the environment, for example to discover the DAGs present in the environment or get the state or properties of each DAG. Results are paginated; use `page_size` to control the number of results per page and `page_token` from a previous response to get the next page. If `page_token` is not present in the response, there are no more results.

ParameterspageSizepageTokenenvironmentrequired

get_dag_source_code

Retrieves the DAG source code from a Managed Airflow environment. Use this tool when you want to understand DAG implementation details, for example to understand why a DAG run has failed, or to debug DAG's behavior. The tool returns the latest version of the source code.

ParametersdagIdrequiredenvironmentrequired

get_dag_run

Retrieves details of a specific DAG run from a Managed Airflow environment. Use this tool when you need to retrieve details of a specific DAG run, for example its state, start time or end time. This tool does not return DAG run logs directly. Instead, use the `cloud_logging_filter` field from the response to query Cloud Logging for the logs for this DAG run.

ParametersdagIdrequireddagRunIdrequiredenvironmentrequired

list_dag_runs

Lists DAG runs in a Managed Airflow environment. Use this tool to get a list of DAG runs in the environment, or runs for a specific DAG, for example to determine the overall healthiness of the environment or DAG. The tool returns DAG runs in the order of creation date, most recent first. Results are paginated; use `page_size` to control the number of results per page and `page_token` from a previous response to get the next page. If `page_token` is not present in the response, there are no more results.

ParametersdagIdpageSizepageTokenenvironmentrequired

get_task_instance

Retrieves details of a specific task instance from a Managed Airflow environment. Use this tool to retrieve details of a specific task instance, such as its state, start time, end time, or parameters, to understand its status or to debug a failure. This tool does not return task instance logs directly. Instead, use the `cloud_logging_filter` field from the response to query Cloud Logging for the logs for this task instance.

ParametersdagIdrequiredtaskIdrequireddagRunIdrequiredmapIndexenvironmentrequired

find_last_failed_dag_runs

Finds failed DAG runs in a Managed Airflow environment. Use this tool to find recent DAG run failures, for example to begin troubleshooting. If the user wants to troubleshoot a specific DAG, provide the DAG ID to get the details of its last failed run. If the user doesn't know which DAG is failing, or wants to see recent failures across all DAGs, leave the DAG ID empty; in this case, the tool will return the last failed DAG run for every DAG in the environment that has at least one failure. If the response returns more than one DAG run and the user asked for troubleshooting or explaining the failure, ask the user which DAG run to troubleshoot. Results are paginated; use `page_size` to control the number of results per page and `page_token` from a previous response to get the next page. If `page_token` is not present in the response, there are no more results.

ParametersdagIdpageSizepageTokenenvironmentrequired

list_failed_task_instances

Lists failed task instances of a specific DAG run in a Managed Airflow environment. If a DAG run has failed, use this tool to get the list of task instances of this DAG run that are in the FAILED state and may have caused the DAG run failure. This tool does not return task instance logs directly. Instead, for each task instance, use the `cloud_logging_filter` field from the response to query Cloud Logging for the logs for that task instance.

ParametersdagIdrequireddagRunIdrequiredenvironmentrequired

trigger_dag

Triggers a DAG run for a specified DAG in a Managed Airflow environment. Use this tool when you need to manually start a new run of a DAG. The tool returns a DAG run object containing the details and state of the newly triggered run. You can use the `get_dag_run` tool to poll for state changes.

ParametersdagIdrequiredenvironmentrequired

list_import_errors

Lists Python import errors and parsing failures in a Managed Airflow environment. Use this tool to check if all DAGs are being parsed correctly in the environment. After uploading a DAG, use this tool alongside `get_dag` to check its parsing status: - **Success**: `get_dag` returns DAG details. - **Import failed**: `get_dag` returns `NOT_FOUND` and `list_import_errors` returns error details and stack traces referencing the DAG file created after the upload. - **Pending parsing**: `get_dag` returns `NOT_FOUND` and `list_import_errors` has no errors referencing the DAG file, created after upload. Always check the import error creation time to make sure the error is relevant to the latest upload. Results are paginated; use `page_size` to control the number of results per page and `page_token` from a previous response to get the next page. If `page_token` is not present in the response, there are no more results.

ParameterspageSizepageTokenenvironmentrequired

Version history

1
  1. v1.0.0LatestSep 16, 2026

Score

72% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 daysRequired25 pts
  • Auth declaredRequired10 pts
  • Tools listedRequired15 pts
  • DescriptionRequired15 pts
  • Logo10 pts

    Publish an icon in the registry entry.

  • Documentation15 pts

    Declare a GitHub repository with a README, or serve resource_documentation in the OAuth protected-resource metadata.

  • LicenseNot applicable

    A hosted service is used under its provider's terms, so no license is expected here. This check is left out of the percentage.