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MCP server · Automation

Gms MCP

GameMaker CLI + MCP server toolset

Unclaimed MIT last commit 6 months ago automation
55Fair

Scored 3 months ago · breakdown

About Gms MCP

Gms MCP is an MCP server published by Ampersand-Game-Studios in the Automation category: gameMaker CLI + MCP server toolset. It has been installed 0 times through Conduid.

Six months or more without a commit doesn't mean the server is broken, but check the open issues (0) before depending on it in production.

Install

Install
npx gms-mcp

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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Security checks

  • ·README presentNot checked yet.
  • ·License declaredNot checked yet.
  • ·Tests presentNot checked yet.
  • ·Dependencies pinnedNot checked yet.
  • ·No dynamic code executionNot checked yet.
  • !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.

README

GitHub Actions & Automation

This directory contains GitHub Actions workflows and automation scripts for gms-mcp.

Tweet Automation

The @gms_mcp Twitter account is automated using Claude API to generate tweets 3x daily.

How It Works

  1. Scheduled workflow (workflows/x-scheduled-post.yml) runs at 8am, 2pm, 8pm UTC
  2. Tweet generation (scripts/generate_tweet.py) calls Claude API with context
  3. Posting (scripts/post_tweet.py) posts to X via API
  4. History tracking persists across runs via GitHub Actions cache

History Persistence

Why we use cache instead of committing history:

The main branch is protected and cannot be pushed to from GitHub Actions workflows. We use actions/cache with a static key (tweet-history-v1) to persist tweet history between runs.

Key points:

  • Static cache key ensures the same entry is overwritten each run
  • Cache is accessed 3x/day, so it won't expire (7-day limit is for non-accessed caches)
  • History includes: posted tweets, topic/format/angle coverage tracking, hashtag metadata

If history resets unexpectedly:

  1. Check if the workflow has been paused for >7 days (cache may have expired)
  2. The system will reinitialize with empty coverage and rebuild naturally
  3. For manual intervention, you can seed a tweet_history.json file in the workflow

Content Diversity System

To prevent repetitive tweets, the system tracks and rotates:

  1. Topics (14 categories): Code Intelligence, Asset Creation, Maintenance, etc.
  2. Formats (6 styles): Problem/Solution, Scenario, Comparison, Tip, Q&A, Workflow Story
  3. Angles (6+ per topic): Different perspectives on each topic
  4. Opening patterns (7 types): Statement, Scenario, Discovery, Comparison, Question, Workflow, Tip
  5. Hashtag strategy: Freeform, contextual hashtags (0-2 max, optional when not useful)

Each dimension is tracked independently with timestamps, ensuring the least-recently-used option is selected.

Validation

Generated tweets are validated for:

  • Length (50-280 characters)
  • Hashtag count (max 2)
  • Bad patterns (corporate speak, emoji spam, negative GameMaker framing)
  • Exact duplicates (hash comparison)
  • Semantic duplicates (>60% word overlap with recent tweets)
  • Overused opening patterns

Files

  • workflows/x-scheduled-post.yml - Main workflow
  • workflows/x-evergreen-experiment.yml - Evergreen experiment workflow
  • scripts/generate_tweet.py - Tweet generation with Claude API
  • scripts/post_tweet.py - X API posting
  • scripts/post_evergreen.py - Evergreen queue posting (does not use next_tweet.txt)
  • scripts/report_evergreen_experiment.py - Experiment KPI report generation
  • scripts/tweet_context.py - Topic categories, formats, context building
  • x-personality.md - Voice/tone guidelines

Evergreen Experiment Controls

The evergreen experiment is controlled entirely through repository variables:

  • X_SCHEDULED_PAUSED - when set to true, x-scheduled-post.yml is paused.
  • X_EVERGREEN_EXPERIMENT_ACTIVE - when set to true, evergreen workflow can run.
  • X_EVERGREEN_EXPERIMENT_START_UTC - ISO UTC experiment start timestamp.
  • X_EVERGREEN_EXPERIMENT_END_UTC - ISO UTC experiment end timestamp (exclusive).
  • X_EVERGREEN_QUEUE_FILE - optional queue file path (defaults to .github/evergreen_queue.json).

The evergreen workflow posts from a versioned queue file and records metrics to job summary + artifacts without changing the release/main tweet staging flow.

Other Workflows

  • release.yml - Automated releases on version tags
  • test.yml - CI testing on pull requests

README mirrored from the source repository 3 months ago. The original is authoritative.

Questions

About Gms MCP

How do I install Gms MCP?

Run npx gms-mcp, then add the server to your MCP client's configuration. Conduid has recorded 0 installs, so the command is known to work with current clients.

Is Gms MCP safe to use with an AI agent?

Its trust score is 55 out of 100 (fair). It passes 0 of 1 static security checks; the failures are listed above. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Gms MCP still maintained?

The last commit was 6 months ago, with 0 open issues. That's long enough that you should check whether the maintainer is responding to issues before depending on it.