get_current_graph
Retrieve metadata for the currently active Logseq graph, including its name and settings.
Instructions
Return metadata for the current Logseq graph.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Retrieve metadata for the currently active Logseq graph, including its name and settings.
Return metadata for the current Logseq graph.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full responsibility for behavioral disclosure. It only states it returns metadata, implying a read operation, but lacks details on side effects, authentication needs, or rate limits. The absence of such information reduces transparency.
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 extremely concise at six words, front-loaded with the key action and resource. Every word serves a purpose, with no unnecessary information.
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?
Given the simple nature of the tool (zero parameters, no output schema), the description is minimally adequate. However, it lacks specification of what metadata is returned, which could leave an agent uncertain about the tool's output structure and completeness.
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, and schema coverage is 100%, so the description does not need to add parameter details. Per guidelines, the baseline for zero parameters is 4, and the description does not detract from this, even though it adds no extra semantic value.
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 clearly states the tool returns metadata for the current Logseq graph, using a specific verb and resource. However, it does not differentiate from siblings like get_current_graph_configs or get_current_graph_favorites, which also return graph-related data, making the purpose slightly vague.
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 explicit guidance on when to use this tool versus alternatives. The description implies it is for general graph metadata, but there is no mention of exclusions or context, leaving the agent to infer usage without clear direction.
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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