Skip to main content
Glama
raqueljezweb

AnythingLLM MCP Server

by raqueljezweb

list_workspaces

Retrieve all available workspaces in AnythingLLM to manage documents, chats, and AI agents.

Instructions

List all available workspaces in AnythingLLM

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

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 behavioral disclosure. It states it's a list operation but doesn't mention any behavioral traits such as pagination, rate limits, authentication requirements, or what 'available' means (e.g., active vs. archived workspaces). This leaves significant gaps for a tool that likely returns multiple items.

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 a single, efficient sentence that directly states the tool's purpose with no wasted words. It's front-loaded and appropriately sized for a simple list operation, making it easy for an agent to parse quickly.

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

Completeness3/5

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

Given the tool's simplicity (0 parameters, no output schema), the description is adequate as a basic overview. However, without annotations or output schema, it fails to address behavioral aspects like return format or limitations, which are important for a list operation. This results in a minimal viable score.

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 0 parameters, and the schema description coverage is 100%, so there's no need for parameter details in the description. The description appropriately focuses on the tool's purpose without redundant parameter information, earning a high baseline score for this context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('List') and resource ('all available workspaces in AnythingLLM'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_workspace' or 'search_workspace', which prevents a perfect score.

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 like 'get_workspace' (for a single workspace) or 'search_workspace' (for filtered results). It lacks any context about prerequisites, timing, or exclusions, leaving the agent with minimal usage direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/raqueljezweb/anythingllm-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server