Skip to main content
Glama
AIWerk

@aiwerk/mcp-server-elevenlabs

by AIWerk

get_documentation_chunks_from_knowledge_base

Read-onlyIdempotent

Retrieve all RAG chunks for a specific knowledge base document, filtered by embedding model, with cursor pagination to fetch every page.

Instructions

Get All Rag Chunks For A Document

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cursorNoUsed for fetching next page. Cursor is returned in the response.
page_sizeNoHow many documents to return at maximum. Can not exceed 100, defaults to 30.
embedding_modelYesThe embedding model used to retrieve the chunk.
documentation_idYesThe id of a document from the knowledge base. This is returned on document addition.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is covered. The description adds little beyond implying enumeration of all chunks, and it does not mention pagination behavior or any rate limits, so it only marginally exceeds the annotation baseline.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single short phrase with no padding, so it is concise, but the phrase is under-specified rather than front-loaded with useful information. It is not wasteful, just minimal.

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

Completeness2/5

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

With four parameters, pagination semantics and a large set of sibling chunk/knowledge-base tools, the description should clarify scope and relationship to alternatives. It does not, and with no output schema it also says nothing about the return shape or pagination, leaving important context missing.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents cursor, page_size, embedding_model and documentation_id in detail. The description adds no parameter meaning, which is the baseline 3 when the schema does all the work.

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

Purpose3/5

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

The description states a verb and resource (get chunks for a document), which is clearer than the name alone, but it does not distinguish this tool from close siblings like get_documentation_chunk_from_knowledge_base (singular) or query_agent_knowledge_base_rag_route. An agent cannot tell from the description alone which chunk-retrieval tool to pick.

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 when-to-use guidance is given and no alternatives are named. The description does not explain that this is for enumerating all chunks of a document versus performing a semantic query, nor does it mention prerequisites.

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

Deploy Server

Other Tools