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cr7258

Elasticsearch MCP Server

list_aliases

Retrieve all Elasticsearch index aliases to manage data organization and simplify query routing across clusters.

Instructions

List all aliases.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • MCP tool handler for list_aliases: decorated with @mcp.tool(), lists all aliases by calling search_client.list_aliases()
    @mcp.tool()
    def list_aliases() -> List[Dict]:
        """List all aliases."""
        return self.search_client.list_aliases()
  • Supporting method in AliasClient that implements the core logic to list aliases using the client's cat.aliases() API
    def list_aliases(self) -> Dict:
        """Get all aliases."""
        return self.client.cat.aliases()
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. 'List all aliases' implies a read-only operation, but it doesn't specify whether this is paginated, sorted, or includes metadata. It lacks details on permissions, rate limits, or error conditions, which are critical for a tool with zero parameters and no output schema.

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 ('List all aliases.') with zero wasted words. It's front-loaded and directly conveys the core action, making it easy for an agent 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?

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'aliases' are in this context (e.g., Elasticsearch aliases), the format of the returned list, or any behavioral traits like pagination. For a tool with no structured output documentation, more context is needed.

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 schema fully documents the absence of inputs. The description adds no parameter information, which is appropriate here. A baseline of 4 is given since no parameters exist, and the description doesn't need to compensate for gaps.

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 'List all aliases' clearly states the verb ('List') and resource ('aliases'), making the purpose immediately understandable. It distinguishes from siblings like 'get_alias' (singular) and 'put_alias' (create/update). However, it doesn't specify scope (e.g., all aliases in the system vs. filtered) 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 provides no guidance on when to use this tool versus alternatives like 'get_alias' (for a specific alias) or 'put_alias' (for creation). There's no mention of prerequisites, context, 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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