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andreperez

AnythingLLM MCP Server

by andreperez

anythingllm_update_embeddings

Idempotent

Embed or un-embed documents in a workspace for RAG queries. Add document paths to vectorize content, or remove them from the workspace without deleting from storage.

Instructions

Embed or un-embed documents in a workspace (equivalent to "Save and Embed" in the UI).

This is the final step after uploading documents to AnythingLLM storage. Typical workflow:

  1. Upload a file -> upload_file / upload_file_to_folder / upload_link / upload_raw_text

  2. List documents -> list_documents / list_documents_in_folder (get the doc paths)

  3. Embed into workspace -> THIS TOOL with 'adds' containing the doc paths from step 2

Once embedded, the document's content is vectorized and available for RAG queries in the workspace. Removing (via 'deletes') un-embeds the document from the workspace but does NOT delete it from storage.

Args: slug: Workspace slug where documents will be embedded. adds: Document paths to embed, as returned by list_documents (e.g. ['custom-documents/Pine Script/file.pine-abc123.json']). deletes: Document paths to un-embed (remove from workspace only, the file remains in AnythingLLM storage).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
addsNo
slugYes
deletesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already convey the write, idempotent, and non-destructive nature. The description adds context about the vectorization effect and clarifies that un-embedding leaves the file in storage, which goes beyond what annotations state. However, it does not detail edge cases (e.g., duplicate embeddings, errors), so a 4 is more fitting than 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?

The description is well-organized with a workflow list and per-argument explanations. Every sentence contributes meaningful guidance without fluff, balancing detail and readability effectively.

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

Completeness5/5

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

The description covers prerequisites (upload first), the embedding process, and the distinction between un-embedding and deletion. It also includes example paths and the UI equivalent, providing a complete context for correct use. An output schema exists, so return values need not be described.

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?

With 0% schema description coverage, the description fully compensates by explaining each parameter: slug is the workspace, adds are document paths from list_documents, and deletes un-embed without deleting storage. It also provides a concrete example of a document path, making usage clear.

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 the tool's function: 'Embed or un-embed documents in a workspace' with the UI equivalent. It distinguishes itself from sibling tools by naming the specific action and referencing a workflow step, making its purpose unambiguous.

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

Usage Guidelines5/5

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

The description provides explicit when-to-use guidance via a step-by-step workflow ('Typical workflow...'), positioning this tool as the final step after upload and listing. It also implies when not to use it by noting that un-embedding does not delete from storage, steering users toward deletion tools if permanent removal is intended.

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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