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Akhilvis

Elastic MCP

by Akhilvis

list_indices

Retrieve all indices from an Elasticsearch cluster to view available data collections for querying and management.

Instructions

List all indices in the Elasticsearch cluster.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler function for the 'list_indices' tool. It lists all non-hidden indices in the Elasticsearch cluster by fetching aliases and filtering out those starting with '.'.
    @mcp.tool()
    def list_indices() -> list:
        """List all indices in the Elasticsearch cluster."""
        try:
            indices = es.indices.get_alias()
            filtered = [name for name in indices.keys() if not name.startswith('.')]
            return filtered
        except Exception as e:
            logger.error(f"Error listing indices: {e}")
            return []
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool lists indices but doesn't mention any behavioral traits such as pagination, rate limits, permissions required, or what the output format looks like. This leaves significant gaps for a tool that interacts with a cluster.

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, efficient sentence that directly states the tool's purpose without any unnecessary words. It's front-loaded and wastes no space, making it highly concise and well-structured.

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?

Given the tool's simplicity (0 parameters, no output schema), the description is adequate as a minimum viable explanation. However, it lacks details about behavioral aspects like output format or cluster interaction nuances, which could be helpful despite the low complexity.

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

Parameters4/5

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

The input schema has 0 parameters with 100% coverage, so the baseline is 4. The description doesn't need to add parameter details, and it correctly doesn't mention any parameters, which is appropriate for this 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 action ('List') and target resource ('all indices in the Elasticsearch cluster'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'get_index_mappings' or 'search_index', which prevents a perfect score.

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 offers no guidance on when to use this tool versus alternatives like 'get_index_mappings' or 'search_index'. It lacks context about use cases, prerequisites, or exclusions, leaving the agent to infer usage from the tool name alone.

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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