Skip to main content
Glama
andreperez

AnythingLLM MCP Server

by andreperez

anythingllm_update_workspace

Idempotent

Update workspace settings such as name, temperature, prompt, and similarity threshold to customize behavior.

Instructions

Update workspace settings (name, temperature, prompt, similarity threshold, etc.).

Args: slug: Workspace slug to update name: New workspace name openAiTemp: LLM temperature (0.0-1.0) openAiHistory: Chat history length (0-100) openAiPrompt: System prompt override similarityThreshold: Similarity threshold (0.0-1.0) topN: Top N results for context (1-20) chatMode: Chat mode: 'chat' or 'query'

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNo
slugYes
topNNo
chatModeNo
openAiTempNo
openAiPromptNo
openAiHistoryNo
similarityThresholdNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

The description does not disclose key behavioral details such as whether unspecified settings are preserved or reset to defaults when only a subset of parameters is provided. Annotations indicate idempotent and non-destructive behavior, but the description adds no operational context, leaving a critical ambiguity for an update tool.

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 opens with a clear, concise lead sentence followed by a compact Args list. Each parameter line is minimal and informative, with no redundancy or unnecessary detail.

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?

While all parameters are documented and an output schema exists, the description fails to clarify the update semantics—specifically whether it performs partial updates or full replacements of workspace settings. This is essential for correct invocation, so the description is not fully complete.

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

Parameters5/5

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

The schema has zero description coverage, but the tool description thoroughly explains all 8 parameters with concise meanings and ranges (e.g., temperature 0.0-1.0, topN 1-20) and clarifies chatMode values. This fully compensates for the lack of schema descriptions.

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 'Update workspace settings' and enumerates specific settings (name, temperature, prompt, similarity threshold), making the operation and resource explicit. The verb 'update' differentiates it from sibling tools like create_workspace and delete_workspace.

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

Usage Guidelines3/5

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

The description provides no explicit guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites. Usage is implied by the tool name and 'update' verb, but there is no context such as 'use for existing workspaces' or 'do not use for creation'.

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/andreperez/anythingllm-mcp'

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