Skip to main content
Glama
berriosb

powerbi-orchestrator-mcp

by berriosb
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Related Servers

Alternatives to powerbi-orchestrator-mcp

No user-submitted related servers found.

    Related Servers

    • superbi-mcp

      cyphonica
      A
      license
      B
      quality
      A
      maintenance
      Enables AI agents to author and edit Power BI files locally (.pbix/PBIP), covering semantic models, reports, and Power Query M with 490 tools.
      100
      23 npm
      3
      Cryptographic Autonomy 1.0 (Combined Work Exception)

    • powerbi-agent-mcp

      HamadYMarafi
      A
      license
      Not graded
      quality
      C
      maintenance
      Enables AI agents to securely connect to your own Power BI or Fabric tenant using your Azure identity, with tools to inspect workspaces and models, run read-only DAX, validate and deploy your own reports, take page screenshots, and enforce guardrails that protect shared resources.
      1
      MIT

    • Microsoft Fabric MCP Server

      snahrup
      A
      license
      B
      quality
      D
      maintenance
      Enables AI assistants to interact with Microsoft Fabric and Power BI services through the Model Context Protocol. Users can manage workspaces, execute DAX queries, refresh datasets, and create Fabric notebooks using natural language.
      6
      19 npm
      2
      MIT

    • Intellify Remote Power BI MCP

      Kkb113
      F
      license
      Not graded
      quality
      B
      maintenance
      Enables authorized AI agents to inspect, query, create, modify, validate, refresh, and manage eligible cloud semantic models in Microsoft Fabric and Power BI through stateless Streamable HTTP.
      -
    • Microsoft Fabric RTI MCP Server by microsoft

      Microsoft Fabric RTI MCPofficial

      microsoft
      A
      license
      B
      quality
      A
      maintenance
      Enables AI agents to interact with Microsoft Fabric Real-Time Intelligence services, allowing for seamless data querying, analysis, and streaming capabilities.
      39
      5,623 PyPI
      132
      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

    A3.8/5.0

    Scored across 28 tools

    Disambiguation4/5

    Most tools target distinct operations (plan vs apply, run_refresh vs execute_dax_query, diff_models vs audit), and detailed descriptions clarify boundaries. There is notable overlap among the report-generation tools (create_report_from_dataset vs design_report_page_from_requirements) and among the multiple audit tools (audit_model_and_report, audit_report_ux_and_storytelling, optimize_report_performance), which could cause occasional misselection.

    Naming Consistency4/5

    The set overwhelmingly follows a snake_case verb_noun pattern (plan_change, apply_plan, connect_target, deploy_to_workspace, promote_in_pipeline). A couple of tools break the pattern with noun-first/phrase names like pre_deploy_check and powerbi_health, but these are minor deviations and still readable.

    Tool Count3/5

    28 tools is on the heavy side and pushes toward the borderline-heavy band. However, the server spans many genuinely distinct domains (connection, planning, DAX, auditing, report design, accessibility, Git sync, RLS, deployment, security labels), so most tools earn their place rather than being redundant.

    Completeness4/5

    The surface covers an unusually full lifecycle: connect/plan/apply, DAX execution and regression, model/report creation, editing, auditing, deployment, Git bidirectional sync, RLS, and sensitivity labeling. The main gap is destructive/removal operations (no delete_measure, delete_visual, delete_role, disconnect), which agents may need alongside the abundant create/edit tools.

    Maintenance

    ActivityActive
    ResponsivenessNo issues

    Resources