"Information about sandbox environments or games" matching MCP servers:

Enables AI tools to interact with the Fellow.ai API for managing action items, notes, recordings, webhooks, and user info with full CRUD operations.

MCP server integrating OBSS Timepiece Time in Status for Jira, enabling queries about issue durations, status histories, and aggregated metrics via natural language.

A read-only MCP server that gives LLM agents deterministic operational facts about Trello boards, including structural history, card movement, workflow flow, staleness, and due-date information.

Enables the creation of interactive schedule visualizations on rhylthyme.com featuring parallel tracks, dependencies, and resource constraints. Users can import recipes or protocols from external sources and define custom workspace environments to generate shareable timelines with live execution timers.

MCP server that gives LLMs full visibility into your ws-cli workspace tree, enabling queries about workspaces, git status, tasks, and saved browser tabs.

Enables defect management on the SEPP platform, allowing users to query defects, retrieve user project information, and set up automated monitoring with alerts for new or unresolved defects via webhook or email.

Enables AI assistants to manage Sciple platform content including environments, services, dashboards, runbooks, projects, and tickets through the Sciple REST API.

MCP server for reading ONES documents in intranet environments, supporting authentication via account/password or browser session reuse.

Bridges local development environments with the Engineering Intelligence Platform (EIP), enabling AI coding agents to manage SSOT, generate implementation/test/security plans, and synchronize architectural knowledge.

Enables AI assistants to manage Optimizely DXP deployments through natural language conversations. Supports code deployment, database operations, content synchronization, and environment management across Integration, Preproduction, and Production environments.

Provides capabilities for searching Jira issues using JQL and retrieving detailed issue information.

Read-only MCP bridge connecting Claude Desktop to Merlin Project on Mac, allowing natural-language queries about plans, activities, resources, and project data.

Connects your Ashby recruiting data to Claude, enabling natural language queries and management of candidates, applications, jobs, interviews, offers, and team information.

Enables AI assistants to retrieve Trello card information by ID or link, providing access to card details including labels, members, due dates, and attachments through a standardized interface.

Enables Claude to read and analyze project schedule files in OmniPlan (.oplx) and Microsoft Project (.mpp) formats, answering questions about tasks, milestones, resources, and progress.

Enables AI assistants to securely connect to OpenProject workspaces and browse, query, and reason about projects, work packages, saved queries, and related metadata via the OpenProject REST API v3.

Captures comprehensive context about development issues and facilitates human assistance through structured API-based help requests.

A Model Context Protocol server that enables seamless interaction between MCP clients (like Claude Desktop) and CODESYS V3 programming environments, allowing automation of project management, POU creation, code editing, and compilation tasks.

A Model Context Protocol server for intelligent task management in AI-powered development environments, providing file-based storage, dependency management with cycle detection, and an interactive CLI.

Enables read-only intelligence over a Linear workspace by serving snapshot and change-history data stored in Cloudflare D1, so clients can answer questions about current work, project and milestone progress, member activity, and weekly reports without modifying Linear or invoking an LLM.

Enables AI clients to locally store and share tasks, work activities, long-term memory, knowledge, and people information, while allowing users to review saved content and generate briefings or reports through a web UI.

A zero-dependency MCP server that answers common questions about Jira work, such as what is assigned to me, standup status, sprint health, and more, without returning raw issue JSON.

Enables AI assistants such as Claude Desktop to access and manage amoCRM data—including leads, contacts, companies, tasks, pipelines, users, notes, and account information—through stdio or Streamable HTTP transports.

Enables AI clients to query construction management companies, projects, and directory data, and to create safety-gated draft records without permitting terminal commitments. It also provides credential resolution, context compression, audit logging, mock/demo sandbox modes, and remote transports for enterprise deployments.

An MCP server that enables AI assistants to interact with Atlassian Jira and Confluence across Cloud and Server/Data Center environments. It supports tasks like searching and summarizing documentation, managing Jira issues, and creating content through natural language.

Enables AI agents and users to verify claims about Jira issues and issue counts against live Jira, retrieve verifiable facts for drafting updates, and re-check previously posted claims. It provides read-only tools and an issue panel so status updates can be evidence-based and mismatches corrected before or after posting.

Enables Claude to read and update the local job-search tracker, adding postings from screenshots, pasted text or links, drafting application emails, syncing Gmail to log sent applications and replies, and answering questions about what's due or which jobs match a criteria. Every change is validated and appears live on the dashboard with a timeline entry.

Connects Canvas LMS to Claude Desktop, enabling natural-language queries about courses, assignments, grades, and more.

Enables Claude to read Jira CSV/JSON backlog exports, audit tickets for test readiness, and generate validated Gherkin acceptance scenarios tied to ticket criteria. It also tracks acceptance-criteria coverage and flags ambiguities or missing information for Product Owner follow-up.

Enables MCP clients to interact with Jira for managing tasks, including fetching assigned issues and creating new tasks. It supports retrieving detailed task information and filtering by project or status using the Jira API.