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astra-knowledge-base-mcp

astra-knowledge-base-mcp

by alrcatraz
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

kb_add

Add text content to a knowledge base with automatic chunking. Optionally tag, title, or link to a source.

Instructions

Add text content to a knowledge base (auto-chunked)

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": {
      "kb": "<kb>",
      "content": "<content>"
    },
    "name": "kb_add"
  }
}

Input Schema

NameRequiredDescriptionDefault
kbYesTarget knowledge base name
tagsNoOptional tags
titleNoOptional title for the content
sourceNoOptional source URL or path
contentYesText content to add

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description bears full responsibility for behavioral disclosure. It only mentions 'auto-chunked', but fails to explain whether additions are append-only, if chunks are stored separately, or what happens on duplicate content or missing knowledge base.

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 a single sentence of 10 words, conveying the core action and a key behavioral trait (auto-chunked). Every word earns its place; no extraneous content.

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?

Given the absence of annotations, output schema, and the presence of 5 parameters, the description lacks essential context such as return value (e.g., success confirmation or chunk identifiers), error handling, and prerequisites (e.g., the knowledge base must exist and be enabled).

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?

The input schema already provides descriptions for all 5 parameters, achieving 100% coverage. The brief description does not add any additional parameter-level insight beyond the schema, which is the baseline expectation.

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

Purpose4/5

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

The description clearly states the action (Add) and resource (text content to a knowledge base), and includes 'auto-chunked' as additional behavioral context. It does not explicitly differentiate from sibling tools like kb_create or kb_update, but the verb 'add' and resource 'content' distinguish it adequately.

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?

The description provides no guidance on when to use kb_add versus alternatives, nor any prerequisites or constraints. There is no mention of required existing knowledge base or restrictions (e.g., file size).

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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