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Akhilvis

Elastic MCP

by Akhilvis

search_index

Search an Elasticsearch index using a query string to retrieve data from Elasticsearch clusters through the Model Context Protocol.

Instructions

Search an Elasticsearch index with a simple query string.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
indexYes
queryYes

Implementation Reference

  • The handler function for the 'search_index' tool, decorated with @mcp.tool() for registration. It performs a search on an Elasticsearch index using the provided query string and returns the response or an error dictionary.
    @mcp.tool()
    def search_index(index: str, query: str) -> dict:
        """Search an Elasticsearch index with a simple query string."""
        try:
            resp = es.search(index=index, query={"query_string": {"query": query}})
            return resp
        except Exception as e:
            logger.error(f"Error searching index '{index}': {e}")
            return {"error": str(e)}
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. While 'search' implies a read operation, it doesn't specify whether this requires authentication, what happens with invalid queries or indices, rate limits, or what format the results will be in. The description mentions 'simple query string' but doesn't explain what that entails behaviorally.

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 states the core functionality without unnecessary words. It's appropriately sized for a basic search tool and gets straight to the point with zero wasted verbiage.

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 search tool with 2 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what the tool returns, error conditions, authentication requirements, or how it differs from sibling tools. The agent would need to guess about important operational aspects.

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

Parameters2/5

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

With 0% schema description coverage and 2 parameters, the description provides minimal parameter context. It mentions 'index' and 'query' but doesn't explain what constitutes a valid index name, what query syntax is supported ('simple query string' is vague), or provide examples. The description doesn't compensate for the complete lack of schema documentation.

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 ('search') and target resource ('an Elasticsearch index') with the method ('with a simple query string'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its siblings (get_index_mappings, list_indices), which would require mentioning that this is for content retrieval rather than metadata operations.

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 its siblings or alternative search methods. There's no mention of prerequisites, limitations, or comparative context that would help an agent choose between search_index, get_index_mappings, and list_indices.

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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