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astra-knowledge-base-mcp

astra-knowledge-base-mcp

by alrcatraz
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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kb_extract

Extract events and entities from unprocessed chunks for structured knowledge base indexing.

Instructions

Extract events and entities from unprocessed chunks (SAG indexing). Reference: arXiv 2606.15971

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>"
    },
    "name": "kb_extract"
  }
}

Input Schema

NameRequiredDescriptionDefault
kbYesKnowledge base name

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?

No annotations provided. The description mentions 'from unprocessed chunks' implying a state assumption but fails to disclose side effects (e.g., whether chunks become processed), required permissions, or output behavior. For a tool that likely mutates state, this is insufficient.

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

Conciseness4/5

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

Two concise sentences, front-loaded with action. The reference is tertiary but not harmful. No waste, though slightly more context could improve without losing conciseness.

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?

Lacks essential context: no output schema, no explanation of what the extracted data looks like, whether the tool modifies state, or prerequisites (e.g., chunks must be unprocessed). Given the complexity of extraction, this is incomplete.

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?

Only one parameter (kb) with a schema description. The tool description adds no extra meaning beyond 'Knowledge base name' in the schema. With 100% schema coverage, baseline score of 3 is appropriate.

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 it extracts events and entities from unprocessed chunks, with a reference. This distinguishes it from search, list, and other kb tools, though it doesn't explicitly name alternatives.

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 guidance on when to use this tool versus siblings like kb_search or mgmt_query. The description assumes the agent knows the context, providing no when-to-use or when-not-to-use advice.

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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