"Information about 3D Game Studio (3DGS) software or related topics" matching MCP servers:

This server enables AI assistants to directly control the Unity Editor via MCP, supporting scene manipulation, script editing, level generation, monetization management, build pipelines, and more—all with zero external dependencies.

Enables Claude to function as a full-stack software engineer with comprehensive development capabilities including project creation, database management, frontend/backend development, testing, deployment, and DevOps operations across multiple frameworks and technologies.

A hosted remote MCP server for managing Android release gates, with tools to check release status, explain permission blockers, issue release receipts, summarize device matrices, and export release logs.

Enables coding agents to access approved user stories and acceptance criteria via MCP, with tools to list, retrieve, update, and check story requirements against the working tree.

Enables Codex users to inspect and publish local Vite games to the 1GP platform with automatic build detection, per-user browser authorization, and build status tracking.

Agent-loop coverage governance that provides coverage feedback to AI coding agents before commit, preventing regressions from reaching CI.

SSWP MCP — Deterministic software attestation for AI-augmented development. Witness any repo through a 5-gate pipeline, adversarially probe dependencies, and produce self-verifying .sswp.json attestations. Fleet registry across 131 nodes with tamper-proof audit ledger and FTS5 search. Agent-native — one tool call from Hermes, Claude, or Cline.

Enables AI coding tools to validate local projects and publish or update applications to Bedengan App Hub via API, with automated checks and live deployment without manual approval.

Enables AI coding agents to orchestrate the full software development lifecycle on GitHub, including planning, issue creation, code review, security triage, and release readiness checks.

Enables code-review gating by converting a git diff into a typed verdict with safety probabilities, severity, and recommended actions for auto-merge or human review.

Deploys and manages projects on Swigs Cloud from any MCP client, turning folders or git repositories into live HTTPS sites in about two minutes.

Enables coding agents to upload local .apk or .ipa builds and receive tester install links without leaving the editor.

Autonomous coding pipeline exposed as an MCP server: plan, dispatch, review, and merge software stories through worktree-isolated agents. A frontier model (Claude) handles judgment — planning, review, risk adjudication — while a local model does the implementation, gated by TDD and a merge-time test rerun on the rebased branch.

Enables Claude to run structured software development pipelines by directing it through sequential phases, validating evidence before advancing, and persisting state in SQLite for resumption across sessions.

Checks whether software dependencies (npm packages, GitHub Actions, MCP servers, Docker images) are alive, dormant, abandoned, archived, or deleted using dated observations from lastseen.dev.

Enables AI agents to enforce a software delivery standard by validating artifacts against declarative rules, providing templates, glossary terms, and pass/fail verdicts with actionable blockers.

Enables agents and CI pipelines to audit MCP servers and agent tool-chains by statically scanning repositories, local checkouts, tools/list exports, or live endpoints for risks such as destructive actions without confirmation, mismatched safety annotations, injection surfaces, credential or PII exposure, and unguarded command, path, or URL sinks. All checks are read-only and never execute the scanned code or call tools/call.

MCP server for DCI API enabling AI models to extract and analyze DCI jobs, components, and topics, with integrations for Google Drive, Jira, GitHub, and Red Hat support cases.

repo-release-tools mcp-server automates the software release process by managing version bumps, changelog generation, and releases. It streamlines repository maintenance by handling repetitive release tasks directly through your AI assistant.

Enables management of Railway.app infrastructure through natural language, including deploying services from GitHub repos or Docker images, managing environment variables, monitoring deployments, and configuring networking and volumes.