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cr7258

Elasticsearch MCP Server

by cr7258
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Python
Remote

get_data_stream

Retrieve configuration, mappings, and settings for one or more data streams. Specify names, patterns, or omit to get all data streams.

Instructions

Get information about one or more data streams.

Retrieves configuration, mappings, settings, and other information about the specified data streams.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoName of the data stream(s) to retrieve. Can be a comma-separated list or wildcard pattern. If not provided, retrieves all data streams.
clusterNoOptional cluster name. Uses the default cluster if omitted.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv2.1.4
    • addedInput schema / additionalProperties
      Added value: +false
    • addedInput schema / properties / cluster / description
      Added value: +"Optional cluster name. Uses the default cluster if omitted."
    • addedInput schema / properties / name / description
      Added value: +"Name of the data stream(s) to retrieve.\n  Can be a comma-separated list or wildcard pattern.\n  If not provided, retrieves all data streams."
  2. Addedv2.1.2
  3. Removedv2.1.1
  4. Addedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full disclosure burden. 'Retrieves' implies a read-only operation but never states it, and there is nothing about permissions, error behavior for missing streams, or result size. The list of returned fields ('configuration, mappings, settings') is the only added behavioral content.

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 brief and front-loaded, but the second sentence largely restates the first with a field list rather than adding new information. No wasted words beyond that redundancy.

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

Completeness3/5

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

An output schema exists, so return values need not be explained, and the input schema is complete. However, with zero annotations the description should carry basic safety/usage context for the read operation and does not, leaving an agent to infer read-only semantics and when to prefer this over sibling lookup tools.

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 both 'name' (comma-separated list or wildcard, all if omitted) and 'cluster' are already fully documented in the schema. The description adds nothing about parameter semantics, which is acceptable at the 100% coverage baseline.

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?

States a specific verb ('Get') and resource ('data streams') plus the cardinality ('one or more'), so an agent immediately knows this is a read of data-stream metadata. It does not explicitly differentiate itself from siblings like get_index or create_data_stream, relying on the verb to carry that distinction.

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 mention of prerequisites, and no named alternative (e.g., get_index for indices, delete_data_stream for removal). The only usage signal is the implicit 'retrieve info' framing, which the agent must infer.

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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