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fortunto2

Prefect MCP Server

by fortunto2
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
PREFECT_API_KEYNoAPI key to authenticate with your Prefect server or Prefect Cloud
PREFECT_API_URLNoThe URL of the Prefect API serverhttp://localhost:4200/api

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Server capabilities have not been inspected yet.

Tools

Functions exposed to the LLM to take actions

NameDescription
get_flow_by_idB

Get a flow by its ID.

Args:
    flow_id: ID of the flow to retrieve.
get_flow_by_nameC

Get a flow by its name.

Args:
    name: Name of the flow to retrieve.
list_flowsB

Get a list of flows from the Prefect API.

Args:
    limit: Maximum number of flows to return (default 20).
    offset: Number of flows to skip (default 0).
search_flowsA

Search for flows by name and/or tags.

Args:
    name: Optional name to search for (case-insensitive contains match).
    tags: Optional list of tags to filter by.
    limit: Maximum number of flows to return (default 20).
get_flow_run_by_idB

Get a flow run by its ID.

Args:
    flow_run_id: ID of the flow run to retrieve.
list_flow_runsB

Get a list of flow runs from the Prefect API.

Args:
    limit: Maximum number of flow runs to return (default 20).
    offset: Number of flow runs to skip (default 0).
    flow_id: Optional ID of the flow to filter runs by.
search_flow_runs_by_stateB

Search for flow runs by state.

Args:
    state_type: Optional state type (e.g., "COMPLETED", "FAILED", "CRASHED").
    state_name: Optional state name (e.g., "Completed", "Failed").
    limit: Maximum number of flow runs to return (default 20).
cancel_flow_runB

Cancel a flow run.

Args:
    flow_run_id: ID of the flow run to cancel.
get_deployment_by_idB

Get a deployment by its ID.

Args:
    deployment_id: ID of the deployment to retrieve.
get_deployment_by_nameB

Get a deployment by its name.

Args:
    name: Name of the deployment to retrieve, in format "flow_name/deployment_name".
list_deploymentsB

Get a list of deployments from the Prefect API.

Args:
    limit: Maximum number of deployments to return (default 20).
    offset: Number of deployments to skip (default 0).
    flow_id: Optional ID of the flow to filter deployments by.
search_deployments_by_statusB

Search for deployments by schedule status.

Args:
    is_schedule_active: Filter deployments by whether their schedule is active.
    limit: Maximum number of deployments to return (default 20).
create_flow_run_from_deploymentB

Create a new flow run for the specified deployment.

Args:
    deployment_id: ID of the deployment or name in format 'flow_name/deployment_name'.
    parameters: Dictionary with parameters for the flow run (optional).
    name: Optional name for the flow run.
    timeout: Timeout in seconds, 0 means no waiting for completion (default 0).
filter_flowsB

Filter flows based on specified criteria.

Args:
    filter_criteria: Dictionary with filter criteria according to Prefect API.
                     Example: {"flows": {"tags": {"all_": ["production"]}}}
filter_flow_runsC

Filter flow runs based on specified criteria.

Args:
    filter_criteria: Dictionary with filter criteria according to Prefect API.
                     Example: {"flow_runs": {"state": {"type": {"any_": ["FAILED", "CRASHED"]}}}}
filter_deploymentsB

Filter deployments based on specified criteria.

Args:
    filter_criteria: Dictionary with filter criteria according to Prefect API.
                     Example1: {"deployments": {"is_schedule_active": {"eq_": true}}}
                     Example2: {"deployments": {"tags": {"all_": ["production"]}}}
create_flow_runB

Create a new flow run for the specified deployment (Legacy).

Args:
    deployment_id: ID of the deployment to create a run for.
    parameters: Dictionary with parameters for the flow run (optional).

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A3.5/5.0

Scored across 17 tools

Disambiguation4/5

Most tools have distinct purposes targeting specific resources (flows, deployments, flow runs) with clear action verbs, but there is some overlap between filter_* and search_* tools that could cause confusion. For example, filter_deployments and search_deployments_by_status both filter deployments but use different approaches, and create_flow_run vs create_flow_run_from_deployment are similar with minor differences.

Naming Consistency5/5

Tool names follow a highly consistent verb_noun pattern throughout, with clear conventions like get_*, list_*, create_*, filter_*, search_*, and cancel_*. All names use snake_case uniformly, making them predictable and easy to parse for an agent.

Tool Count4/5

With 17 tools, the count is slightly high but reasonable for a workflow orchestration domain like Prefect, which requires operations across flows, deployments, and runs. It covers essential CRUD and query functions without being overwhelmingly bloated, though some tools could potentially be consolidated.

Completeness5/5

The tool set provides comprehensive coverage for managing Prefect workflows, including full CRUD/lifecycle operations for flows, deployments, and flow runs (e.g., create, get, list, filter, search, cancel). There are no obvious gaps that would hinder an agent from performing typical orchestration tasks, and the surface supports complex filtering and searching needs.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources