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Export Variables

export_variables
Read-only

Export an environment's variables as .env or JSON with secret values always masked. Produce output suitable for review or re-import into another environment.

Instructions

Export an environment's variables as .env or JSON text. Secret values are ALWAYS masked — MCP has no path to decrypted secrets; use the web app if you need the real values. The output is suitable for review and for feeding back into import_variables.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatNoOutput format: 'env' (KEY=VALUE lines) or 'json'. Defaults to 'env'.env
projectIdNoPublic ID (GUID) of the project. If omitted, uses the active project context.
environmentIdYesPublic ID (GUID) of the environment

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.1.1

TDQS

A4.5/5.0
Behavior5/5

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

The description adds important behavioral detail beyond the readOnlyHint annotation: secret values are ALWAYS masked and there is no MCP path to decrypted secrets. This prevents an agent from expecting plaintext secrets and clarifies a significant limitation of the tool.

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

Conciseness5/5

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

Three sentences, each earning its place: the core behavior, the critical masking limitation, and the intended downstream use. The most important operational constraint (masking) is placed prominently and no filler is present.

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

Completeness5/5

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

For a low-complexity read-only export tool with fully documented parameters, the description is complete. It tells the agent what the output looks like, what is masked, and how the output can be used, so no critical context is missing even without an output schema.

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

Parameters3/5

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

The input schema already documents all three parameters with 100% coverage, including format defaults and project/environment IDs. The description reinforces the format concept but does not add meaningful parameter-level detail beyond what the schema already provides, so the baseline score of 3 is appropriate.

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 identifies a specific verb and resource: exporting an environment's variables as .env or JSON text. It distinguishes itself from siblings like get_environment_variables by emphasizing the serialized output format and the masking behavior, which makes the tool's purpose unmistakable.

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?

The description gives clear usage context: the output is meant for review and for feeding back into import_variables, and it explicitly directs users to the web app when real secret values are needed. It does not explicitly name alternative MCP tools such as get_environment_variables or resolve_variables, so it stops short of a full when-to-use versus alternatives comparison.

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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