Skip to main content
Glama
Sign In
coreline-ai

Antigravity GLM MCP

by coreline-ai
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Related Servers

Alternatives to Antigravity GLM MCP

No user-submitted related servers found.

    Related Servers

    • cygnus-ssh-mcp by cygnussystems

      cygnus-ssh-mcpofficial

      cygnussystems
      A
      license
      A
      quality
      A
      maintenance
      Enables AI assistants to manage remote servers via SSH with 43 specialized tools for command execution, file editing, directory operations, and background tasks across Linux, macOS, and Windows.
      46
      54 PyPI
      8
      GPL 3.0

    • Desktop Commander MCP

      Viper-Empire
      A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI to run terminal commands with interactive process control, manage long-running processes, and perform filesystem operations including search and diff-based file editing. It also supports reading and editing Excel, PDF, and DOCX files, executing code in memory, and auditing tool-call history.
      699,740 npm
      MIT

    • Agentic MCP Server

      lucastl
      A
      license
      A
      quality
      D
      maintenance
      Acts as the 'Hands and Eyes' for an Autonomous AI Agent, bridging Large Language Models and your local development environment to enable safe file manipulation, context reading, command execution, and documentation verification.
      9
      2
      ISC
    Deploy Server
    Shareable, User-Owned Context BackendPeople, applications, and agents read, write, and coordinate together in one context lake. Reach it over MCP, a CLI, a Python SDK, or REST.fulcradynamics.comAd

    TDQS

    C2.7/5.0

    Scored across 25 tools

    Disambiguation4/5

    Most tools have distinct purposes, but 'glm_cmd' (delegating to GLM) and 'glm_bypass' (raw prompt) could confuse an agent. Also, multiple log-related tools (glm_action_log, glm_git_log) are separate but might be misinterpreted without careful reading.

    Naming Consistency5/5

    All tools follow a consistent 'glm_<domain>_<action>' pattern (e.g., glm_file_create, glm_git_commit). This makes the tool set predictable and easy to navigate.

    Tool Count3/5

    With 25 tools, the server is on the heavy side for a general-purpose assistant. While each tool serves a purpose, the count is borderline and could be streamlined by merging some functions (e.g., memory operations).

    Completeness4/5

    The tool surface covers a wide range: file operations, git, memory, code execution, web search, HTTP, image analysis, shell, scheduling, and DB queries. Minor gaps exist (e.g., no file rename or explicit memory update), but overall it's quite comprehensive for an AI assistant.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources