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cr7258

Elasticsearch MCP Server

by cr7258
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

get_cluster_stats

Retrieve high-level cluster statistics to monitor Elasticsearch cluster health, performance metrics, and resource utilization for operational insights.

Instructions

Returns high-level overview of cluster statistics.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • src/tools/cluster.py:14-17 (handler)
    The MCP tool handler function for 'get_cluster_stats', registered via @mcp.tool() decorator, which delegates the call to the search client's get_cluster_stats method.
    @mcp.tool()
def get_cluster_stats() -> Dict:
    """Returns high-level overview of cluster statistics."""
    return self.search_client.get_cluster_stats()
  • src/clients/common/cluster.py:10-12 (helper)
    The core helper method in ClusterClient that retrieves cluster statistics directly from the OpenSearch client.
    def get_cluster_stats(self) -> Dict:
    """Get cluster statistics from OpenSearch."""
    return self.client.cluster.stats()

Tool Definition Quality

B3.1/5.0
Behavior2/5

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

With no annotations, the description carries full burden but only states it 'returns' data without disclosing behavioral traits like rate limits, authentication needs, or what 'high-level' entails. It doesn't mention if it's safe, read-only, or has side effects.

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 with no wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly.

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 no annotations and no output schema, the description is insufficient. It lacks details on what statistics are returned, format, or any behavioral context, leaving gaps for an agent to use it effectively.

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 tool has 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description doesn't add param info, but that's appropriate here, meeting the baseline for zero-param tools.

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 ('Returns') and resource ('high-level overview of cluster statistics'), making the tool's function immediately understandable. It doesn't distinguish from siblings like 'get_cluster_health' or 'get_index', but the purpose is unambiguous.

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 like 'get_cluster_health' or 'get_index'. The description implies it's for high-level statistics, but doesn't specify scenarios, prerequisites, or exclusions.

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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