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itshare4u

Agent Knowledge MCP

by itshare4u
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Python
Hybrid

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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

    A3.5/5.0

    Scored across 27 tools

    Disambiguation4/5

    Most tools have distinct purposes, but some overlap exists. For example, 'ask_mcp_advice' and 'ask_user_advice' both involve seeking guidance, which could cause confusion. However, their descriptions clarify that one uses AI-filtered knowledge and the other involves human input, helping to differentiate them. Overall, the tools are well-defined with minimal ambiguity.

    Naming Consistency5/5

    Tool names follow a consistent snake_case pattern with clear verb_noun structures, such as 'create_document_template', 'delete_index', and 'validate_config'. There are no deviations in naming conventions, making the set predictable and easy to understand. This consistency aids in agent selection and reduces confusion.

    Tool Count3/5

    With 27 tools, the count is borderline high for an MCP server focused on Elasticsearch and knowledge management. While it covers many operations, it may feel heavy and could overwhelm agents. A more streamlined set of 15-20 tools might be more appropriate, but the current scope is still manageable given the domain's complexity.

    Completeness5/5

    The tool surface provides comprehensive coverage for Elasticsearch operations and knowledge base management, including CRUD for documents and indices, configuration handling, backup/restore, and validation. There are no obvious gaps; agents can perform full lifecycle management, from setup to maintenance, without encountering dead ends.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources