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Seq MCP Server

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    • A
      license
      B
      quality
      D
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      Enables LLMs to query and analyze logs from SEQ structured logging server with capabilities for searching events, retrieving event details, analyzing log patterns, and accessing saved searches.
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    • A
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      A Model Context Protocol server that provides AI agents with controlled read access to Datalust Seq instances for log analysis and monitoring. It enables agents to search events, execute data queries, and retrieve information about signals, dashboards, and alerts.
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    • A
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      Integrates AI assistants with Graylog to query and analyze log data using Elasticsearch syntax and stream-specific filtering. It enables users to perform advanced searches, retrieve log statistics, and manage Graylog streams through natural language.
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    • A
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      quality
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      Connects AI assistants to cloud and SaaS logs via Tailpipe, enabling natural language querying and analysis of log data.
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    • A
      license
      A
      quality
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      Enables querying OpenObserve logs—listing streams, inspecting schemas, and running SearchSQL time-windowed searches—so you can answer what actually happened in production. Optionally correlates those logs against a database through a verified read-only connection via DbSchema and DbQuery tools.
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    TDQS

    B3.4/5.0

    Scored across 6 tools

    Disambiguation4/5

    Most tools are clearly distinct: signals listing/retrieval, filter conversion, and live tailing each have unique purposes. However, seq_search for historical events and seq_query for analytical SQL-like queries could be confused by an agent deciding how to retrieve or analyze log data. Descriptions provide enough guidance to resolve most ambiguity.

    Naming Consistency5/5

    All tools use a consistent seq_ prefix followed by a verb_noun pattern in snake_case (seq_search, seq_list_signals, seq_get_signal, etc.). No mixed conventions or vague naming.

    Tool Count5/5

    Six tools is well-scoped for a Seq log querying server, covering search, analytical query, signal inspection, filter conversion, and live tailing without bloat. Each tool earns its place for the core workflows.

    Completeness4/5

    The server covers key read and query operations: historical search, SQL-like analytics, signal discovery, filter conversion, and live tailing. Minor gaps exist around managing signals (e.g., create/update/delete) and exporting results, but core agent workflows are supported.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues