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TheNovaNodes

AnythingLLM Control Plane MCP Server

by TheNovaNodes

get_system_env

Retrieve system environment variables and configuration from AnythingLLM Admin API to monitor instance settings.

Instructions

Retrieve system environment and configuration dump from AnythingLLM Admin API.

Returns: JSON string containing system environment variables and configuration.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations provided, the description carries the full burden of disclosing behavioral traits. It only states 'Retrieve' and notes the return format, but does not explicitly declare read-only status, authentication requirements, or any potential risks (e.g., sensitive environment variables). The lack of such context makes it difficult to assess side effects or safety.

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?

The description is concise, consisting of just two short lines. It front-loads the primary purpose with a clear verb and resource, and the 'Returns' line efficiently communicates the output format without redundancy. Every sentence earns its place.

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?

For a tool with no parameters and an output schema already present, the description is largely complete. It states the purpose and return format. However, it lacks situational context such as noting that this is an admin-level read operation or that environment variables can be sensitive, which would be useful for an agent deciding to invoke it.

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

Parameters4/5

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

The tool has zero parameters, so the input schema is empty and the baseline for this dimension is 4. The description does not need to elaborate on parameters; it correctly focuses on the output, mentioning that it returns a JSON string of environment variables and configuration, which adds useful meaning beyond the schema.

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 the action ('Retrieve') and the specific resource ('system environment and configuration dump') from the AnythingLLM Admin API. This distinguishes it from sibling tools that operate on workspaces or vector counts, so it fully clarifies what the tool does.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives such as list_workspaces or get_vector_count. It does not mention context, prerequisites, or exclusions, leaving the agent without explicit usage direction.

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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