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moliver28

anythingllm-mcp

by moliver28

get_workspace

Retrieve detailed information about a specific workspace using its unique slug. Perfect for accessing workspace configuration and metadata in your AI document chat platform.

Instructions

Get details of a specific workspace

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYes

Implementation Reference

  • src/index.ts:62-80 (registration)
    Tool registration - get_workspace is not present; the tool is named 'workspace_get' in the tool list (line 70). This is the registration of the workspace_get tool.
    server.setRequestHandler(ListToolsRequestSchema, async () => {
      return {
        tools: [
          { name: "auth_verify", description: "Verify API token", inputSchema: { type: "object", properties: {}, required: [] } },
          { name: "system_check_token", description: "Check API token", inputSchema: { type: "object", properties: {}, required: [] } },
          { name: "system_generate_api_key", description: "Generate API key", inputSchema: { type: "object", properties: {}, required: [] } },
          { name: "system_env_dump", description: "Get system environment", inputSchema: { type: "object", properties: {}, required: [] } },
          { name: "workspace_list", description: "List all workspaces", inputSchema: { type: "object", properties: {}, required: [] } },
          { name: "workspace_get", description: "Get workspace details", inputSchema: { type: "object", properties: { slug: { type: "string" } }, required: ["slug"] } },
          { name: "workspace_create", description: "Create workspace", inputSchema: { type: "object", properties: { name: { type: "string" }, slug: { type: "string" } }, required: ["name"] } },
          { name: "workspace_update", description: "Update workspace", inputSchema: { type: "object", properties: { slug: { type: "string" }, name: { type: "string" } }, required: ["slug"] } },
          { name: "workspace_delete", description: "Delete workspace", inputSchema: { type: "object", properties: { slug: { type: "string" } }, required: ["slug"] } },
          { name: "chat_send", description: "Send chat message", inputSchema: { type: "object", properties: { workspace: { type: "string" }, message: { type: "string" } }, required: ["workspace", "message"] } },
          { name: "chat_stream", description: "Stream chat", inputSchema: { type: "object", properties: { workspace: { type: "string" }, message: { type: "string" } }, required: ["workspace", "message"] } },
          { name: "thread_list", description: "List threads", inputSchema: { type: "object", properties: { workspace: { type: "string" } }, required: ["workspace"] } },
          { name: "document_list", description: "List documents", inputSchema: { type: "object", properties: {}, required: [] } },
          { name: "openai_list_models", description: "List models", inputSchema: { type: "object", properties: {}, required: [] } },
          { name: "openai_chat_completion", description: "Chat completion", inputSchema: { type: "object", properties: { model: { type: "string" }, messages: { type: "array" } }, required: ["model", "messages"] } },
        ],
  • Handler for workspace_get - calls the AnythingLLM API endpoint '/workspace/' with the slug parameter. This is the closest match to 'get_workspace' in the codebase.
    else if (name === "workspace_get") { result = await apiRequest("/workspace/" + args?.slug); }
Behavior2/5

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

With no annotations, the description must convey behavior. It states 'Get details' implying a read operation, but fails to disclose permissions, rate limits, or what exactly 'details' entails. Minimal transparency beyond the obvious.

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?

One sentence of 5 words with no filler. Front-loaded and efficient, earning its place.

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?

For a simple single-parameter get tool, the description minimally covers purpose but omits return details (no output schema) and behavioral context. Adequate but not thorough.

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

Parameters2/5

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

The only parameter 'slug' is mentioned in schema but not explained in description. Schema description coverage is 0%, yet the description adds no semantic context about slug format, examples, or how it identifies the workspace. Marginal value over 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 'Get details of a specific workspace' clearly indicates the verb (Get) and resource (workspace), differentiating it from sibling tools like list_workspaces, create_workspace, update_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 Guidelines2/5

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, such as list_workspaces for all workspaces or get_thread for threads. No when-not or prerequisite information is provided.

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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