list_personal_variablesList your personal variables for one environment. They override both organization and environment variables and are visible only to you. Secret values are always masked. Requires organization context.
| Name | Required | Description | Default |
|---|---|---|---|
| projectId | No | Public ID (GUID) of the project. If omitted, uses the active project context. | |
| environmentId | Yes | Public ID (GUID) of the environment |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Read-only behavior is already conveyed by the readOnlyHint annotation, and the description reinforces it with 'List' and adds useful behavioral details: secret values are always masked and variables are personal/visible only to the user. No hidden side effects are implied or omitted.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three short sentences. It front-loads the core purpose and then adds only the most relevant scoping and masking details, with no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a straightforward read-only list operation, the description provides sufficient context: environment scope, personal visibility, override behavior, and secret masking. It does not define the output schema, but that is not necessary for this simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema descriptions fully cover both parameters with GUID semantics and the optional/default behavior of projectId. The tool description does not add additional parameter-level detail, but since schema coverage is 100%, the baseline score is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly identifies the action (list), resource (personal variables), scope (one environment), and key properties (override org/environment variables, visible only to the user, secret values masked). It is easily distinguishable from sibling variable tools such as get_environment_variables.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
States the prerequisite ('Requires organization context') and describes the intended variable category with visibility and override behavior. It does not explicitly name alternatives or say when not to use it, but the context makes the appropriate use case clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The tools are mostly distinct with clear descriptions. Some pairs like get_header_policies vs get_resolved_headers or get_environment_verification vs get_monitoring_sync_status could be slightly confusing, but the descriptions clarify scope and purpose.
All tools follow a consistent snake_case verb_noun pattern (get_, list_, create_, update_, manage_, etc.). Even the few bare verbs like 'search' and 'set_context' are consistent with the naming scheme.
With 165 tools, the server is extremely heavy. This far exceeds the 'too many' threshold of 25+, making it difficult for an agent to navigate and select the right tool efficiently.
The tool surface covers a very broad API lifecycle domain: specs, environments, test cases, monitors, mock servers, security, governance, documentation, and team management. Read and write operations are present across most areas, with no obvious missing core functionality.