get_user_configs
Retrieve Logseq user configuration to access and manage user settings and graph preferences.
Instructions
Return Logseq user configuration.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Retrieve Logseq user configuration to access and manage user settings and graph preferences.
Return Logseq user configuration.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, and the description is extremely brief. It fails to disclose any behavioral traits such as read-only nature, potential side effects, authentication requirements, or what constitutes 'user configuration.'
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?
A single, concise sentence that immediately states the action and resource. No extraneous words or repetition.
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 parameterless getter with no output schema, the description is minimally adequate. However, it lacks details about the structure or content of the returned configuration, and the absence of annotations means behavioral context is missing.
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 tool has zero parameters with 100% schema description coverage (baseline 4). The description adds the meaning that the tool returns 'user configuration,' which is not present in the empty schema.
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?
The description 'Return Logseq user configuration' uses a specific verb ('Return') and clearly identifies the resource ('user configuration'). It distinguishes itself from sibling tools like 'get_current_graph' or 'get_page' by targeting a unique resource.
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?
No guidance on when to use this tool versus alternatives (e.g., get_app_info or get_current_graph_configs). The description gives no context about prerequisites or scenario suitability.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/Johnsonxd4/mcp-logseq'
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