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Elasticsearch MCP Server

by cr7258
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Python
Remote

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    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    B3.3/5.0

    Scored across 20 tools

    Disambiguation5/5

    Each tool targets a clearly distinct resource and action (index, document, alias, data stream, cluster, analysis, or generic API). Overlaps like get_index vs list_indices and get_alias vs list_aliases are cleanly separated by specificity. The general_api_request fallback is explicitly scoped to APIs without dedicated tools, so it does not create real misselection risk.

    Naming Consistency5/5

    Tools follow a consistent snake_case verb_noun convention (create_index, delete_document, get_cluster_health, put_alias, etc.). The only minor exception is general_api_request, but it still fits the overall readable naming style. There is no mixing of camelCase or conflicting verb patterns.

    Tool Count4/5

    At 20 tools, the surface is slightly heavy by the usual 3–15 guideline, but Elasticsearch is a broad domain and each tool covers a meaningful resource area. The set avoids extreme bloat and does not include redundant operations.

    Completeness4/5

    Core CRUD and lifecycle coverage exists for indices, documents, aliases, data streams, and cluster inspection, with search and text analysis included. Notable gaps remain—such as dedicated index template management (required for data streams), bulk operations, and update-by-query—but the general_api_request tool provides a workaround for any missing API.

    Maintenance

    ActivityMaintained
    ResponsivenessWithin a week

    Resources