anythingllm-mcp

ask_workspace

Send an async chat query to an AnythingLLM workspace, returning a job ID immediately to avoid MCP timeouts on slow models; poll get_answer until done.

Instructions

Async chat query to an AnythingLLM workspace. Returns a job_id instantly so the call never hits the ~60s MCP timeout (use for slow models like Qwen 32B). Poll get_answer until status is 'done'.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "slug": "<slug>",
      "question": "<question>"
    },
    "name": "ask_workspace"
  }
}

Input Schema

Name	Required	Description
`mode`	No	query=only indexed docs (default); chat=allow model general knowledge
`slug`	Yes
`question`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.0.0Sep 27, 2026

TDQS

A4.1/5.0

Behavior4/5

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

With no annotations, the description carries the behavioral burden and does well: it discloses asynchrony, the instant job_id return, the ~60s MCP timeout it avoids, and the polling contract. It omits failure/error behavior and whether the slug must already exist, which keeps it from a 5.

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?

Three tight sentences, front-loaded with what the tool does and the return contract before the usage hint. No filler; every sentence carries distinct information.

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

Completeness4/5

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

For an async tool with no annotations and no output schema, the description covers the essential async contract, the immediate return value, and the polling loop. Residual gaps are the undocumented slug/question parameters and unstated error handling.

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?

Schema coverage is only 33% — only 'mode' is documented, and that documentation lives in the schema, not the description. 'slug' and 'question' are undocumented in both places; the description implies a workspace and a query but adds no format, constraints, or defaults, so it does not compensate for the coverage gap.

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?

States a specific verb+resource ('Async chat query to an AnythingLLM workspace') and immediately names the sibling it pairs with ('Poll get_answer'), so an agent can distinguish it from get_answer and the workspace CRUD tools without opening any schema.

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

Usage Guidelines4/5

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

Gives a concrete selection condition ('use for slow models like Qwen 32B') and names the required follow-up tool and its terminal state ('Poll get_answer until status is done'). It stops short of stating when a synchronous alternative should be preferred, but the routing guidance is otherwise explicit.

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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