Skip to main content
Glama
EasyDeploy-AI

easydeploy-ai-mcp

Official
by EasyDeploy-AI
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Related Servers

Alternatives to easydeploy-ai-mcp

No user-submitted related servers found.

    Related Servers

    • my-mcp-server

      15972289829
      F
      license
      Not graded
      quality
      D
      maintenance
      A Model Context Protocol server that allows integration with Claude Desktop by creating and managing custom tools that can be executed through the MCP framework.
      75 npm
      -

    • MCP API Server

      fikri2992
      A
      license
      A
      quality
      D
      maintenance
      A Model Context Protocol server that enables AI assistants to make HTTP requests (GET, POST, PUT, DELETE) to external APIs through standardized MCP tools.
      4
      2
      MIT

    • Coolify MCP Server

      wrediam
      A
      license
      A
      quality
      C
      maintenance
      A Model Context Protocol server that provides integration with the Coolify API, enabling DevOps teams to manage Coolify deployments, applications, services, and servers through MCP tools.
      32
      211 npm
      46
      MIT

    • routine-mcp

      rskmanz
      F
      license
      Not graded
      quality
      D
      maintenance
      A Model Context Protocol (MCP) server built with the mcp-framework for developing and managing custom tools. It provides a structured foundation for building and integrating modular components like data processors and API clients into Claude Desktop.
      11 npm
      -

    • mcp-connect

      myat-kyaw-thu
      A
      license
      Not graded
      quality
      B
      maintenance
      A dead simple MCP server for exposing your app functions to AI agents like Claude Desktop.
      16 npm
      6
      MIT

    • dify-mcp-server

      overpod
      A
      license
      Not graded
      quality
      C
      maintenance
      MCP server for Dify Console API that enables managing apps, workflows, knowledge bases, models, plugins, and MCP servers programmatically from Claude Code or any MCP client.
      5 npm
      7
      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

    A3.5/5.0

    Scored across 24 tools

    Disambiguation4/5

    Most tools target distinct resources or actions (e.g., projects, datasets, models, predictions). Some potential overlap exists between get_training_status and list_model_versions for checking training status, but detailed descriptions help disambiguate.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern (e.g., get_, list_, create_, run_) and use snake_case throughout, making the set predictable and easy to navigate.

    Tool Count3/5

    At 24 tools, the server is on the heavier side for the suggested range (16–25 is considered 'heavy'). While each tool serves a specific purpose, the count may feel overwhelming for an agent.

    Completeness2/5

    The tool set covers the core ML workflow but lacks delete operations for any resource (projects, datasets, models, predictions). This is a significant gap that will prevent agents from fully managing the lifecycle.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources