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npow

metaflow-mcp-server

by npow

run_flow

Run a Metaflow workflow from a local Python file. Optionally set parameters, tags, and max workers for parallel execution.

Instructions

Run a Metaflow flow from a local source file.

Starts execution and returns once the run ID is assigned. The flow continues running as a subprocess. Use get_run to monitor progress.

Requires the flow source file on the local filesystem -- only works when the MCP server has access to the flow code (e.g. local dev).

Args: flow_file: Path to the flow Python file (e.g. "./myflow.py"). parameters: Optional flow parameter overrides (e.g. {"learning_rate": "0.01"}). Keys are parameter names. tags: Optional tags to apply to the run. max_workers: Max parallel workers for foreach steps.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
flow_fileYes
parametersNo
tagsNo
max_workersNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, description explains asynchronous nature and subprocess execution, but omits error handling, permission details, and potential side effects. Adequate but not comprehensive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is well-structured with a clear main sentence and a separate Args section. Slightly verbose but efficient; front-loads purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers all necessary aspects: purpose, usage, parameters, and behavior. With an output schema present, return value details are not required. Missing error handling but sufficient for typical agent use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The 'Args' section adds detailed meaning to all parameters beyond the schema, including types and usage (e.g., flow_file as path, parameters as overrides). Fully compensates for 0% schema description coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Run a Metaflow flow from a local source file' with a specific verb and resource, distinguishing it from siblings like trigger_run or get_run.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides context on asynchronous execution and local requirement, and suggests using get_run for monitoring. Lacks explicit alternatives for non-local scenarios, but the local constraint is well-stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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