@aiwerk/mcp-server-elevenlabs

get_documentation_chunk_from_knowledge_base

Read-onlyIdempotent

Retrieve a specific documentation chunk from a knowledge base by document ID and chunk ID, optionally specifying the embedding model used for retrieval.

Instructions

Get Documentation Chunk From Knowledge Base

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": {
      "documentation_id": "<documentation_id>",
      "chunk_id": "<chunk_id>"
    },
    "name": "get_documentation_chunk_from_knowledge_base"
  }
}

Input Schema

Name	Required	Description
`chunk_id`	Yes	The id of a document RAG chunk from the knowledge base.
`embedding_model`	No	The embedding model used to retrieve the chunk.
`documentation_id`	Yes	The id of a document from the knowledge base. This is returned on document addition.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 13, 2026

TDQS

C2.2/5.0

Behavior2/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered structurally. The description adds nothing on top of that — no note on retrieval scope, missing-chunk behavior, or how the embedding_model affects results.

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

Conciseness2/5

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

A single sentence that merely echoes the title; it is short but does not earn its place since it carries no information beyond the tool name.

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?

For a simple read tool with 100% schema coverage and full annotations, the description could still clarify the chunk-vs-document distinction and when to prefer this over sibling retrieval tools. That context is absent.

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%, with documentation_id, chunk_id, and embedding_model all documented in the schema, so the baseline is 3. The description contributes no additional meaning about how the required IDs relate to one another.

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

Purpose2/5

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

The description is a verbatim restatement of the tool name ('Get Documentation Chunk From Knowledge Base') and adds no distinguishing detail. It does not separate this single-chunk retrieval from siblings like get_documentation_chunks_from_knowledge_base or get_documentation_from_knowledge_base.

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?

There is no when-to-use guidance, no prerequisites, and no mention of the near-identical sibling tools. An agent cannot tell from the text why it would call this over the plural chunks route.

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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