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Kinetica MCP Server

Kinetica MCP Server

Official
by kineticadb
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_records

Fetch raw JSON records from a given table, with an optional limit on rows returned.

Instructions

Fetch raw JSON records from a given table.

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": {
      "table_name": "<table_name>"
    },
    "name": "get_records"
  }
}

Input Schema

NameRequiredDescriptionDefault
table_nameYes
limitNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.6/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure, but it only states 'Fetch raw JSON records'. It does not mention side effects (likely read-only), pagination, error handling, or any constraints beyond the input schema.

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?

The description is a single, front-loaded sentence of 6 words, avoiding any redundancy. While it is extremely short, it does not contain filler and conveys the core action efficiently.

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 tool with 2 parameters and an output schema, the description is too brief. It omits details about pagination, sorting, error behavior, or the meaning of 'raw'. The presence of an output schema does not fully compensate for missing usage context.

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

Parameters1/5

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

Schema description coverage is 0%, yet the description does not elaborate on the parameters. The phrase 'from a given table' only hints at 'table_name', while 'limit' and its default are completely ignored. The description adds essentially no value beyond the schema.

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 verb ('Fetch'), resource ('raw JSON records'), and context ('from a given table'), making the tool's purpose understandable. It is distinct from sibling tools like 'describe_table' or 'insert_records', though it does not explicitly contrast itself.

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 is provided on when to use this tool versus alternatives such as 'query_sql' or 'list_tables'. The description offers no context about preferred use cases or limitations.

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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