Skip to main content
Glama
CarmitHaas

Customer Service Data Analyst MCP Server

by CarmitHaas
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Related Servers

Alternatives to Customer Service Data Analyst MCP Server

No user-submitted related servers found.

    Related Servers

    • cheq-tickets

      GalDaich
      A
      license
      A
      quality
      C
      maintenance
      Enables semantic search and analysis of customer support tickets. Provides tools to search tickets, analyze the dataset, and retrieve individual tickets using natural language.
      3
      MIT

    • Customer Support Analyst MCP

      ZivSapir
      F
      license
      Not graded
      quality
      B
      maintenance
      Enables natural-language Q&A over customer support ticket data. Provides tools for schema inspection, SQL-based ticket counts and grouping, and full-text search for customer wording without requiring API keys.
      -

    • SQL MCP Server

      apoorva183
      F
      license
      Not graded
      quality
      D
      maintenance
      Exposes a SQLite database to AI assistants with structured, read-safe access. Includes five tools for schema exploration, querying, and sampling data.
      -

    • Zendesk MCP Server

      fitcloud
      F
      license
      Not graded
      quality
      D
      maintenance
      Enables AI agents to interact with Zendesk ticket data for customer support analysis and insights. It supports searching tickets by tags or keywords, retrieving ticket details, and analyzing agent performance and service trends.
      -

    • zendesk-mcp

      sophiabanda
      A
      license
      A
      quality
      B
      maintenance
      Enables Zendesk support workflows through tools for semantic ticket search, customer context retrieval, solution version assessment, and daily work summaries.
      4
      18 npm
      MIT
    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

    A4.3/5.0

    Scored across 5 tools

    Disambiguation5/5

    Each tool has a unique purpose: counting without rows, sampling with total count, listing categories, listing intents (optionally with distribution), and returning representative messages for summarization. No two tools perform the same function.

    Naming Consistency5/5

    All tool names follow the consistent verb_noun pattern using snake_case (e.g., count_records, filter_records). There are no deviations or mixed conventions.

    Tool Count5/5

    Five tools is well-scoped for the server's purpose of analyzing customer service data. Each tool serves a distinct, necessary function without redundancy or bloat.

    Completeness4/5

    The set covers discovery (categories, intents), counting, sampling, and summarization. A minor gap is lack of comparative or aggregate statistics across categories, but the core analytical workflow is supported.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues

    Resources