"Information about QlikView - Business Intelligence and Data Visualization Software" matching MCP servers:

An MCP server that facilitates interactive software development planning by breaking down projects into manageable tasks, tracking progress, and saving implementation plans.

Facilitates software development planning through interactive sessions that break down projects into manageable tasks with complexity scoring, code examples, and implementation plan management.

Facilitates interactive software development planning by managing tasks, tracking progress, and creating detailed implementation plans through the Model Context Protocol.

Provides software development planning tools to help users create implementation plans and manage todo items.

Enables the creation and management of business design artifacts including Business Model Canvases, SWOT analyses, and user personas. It features project organization and AI-powered research tools to automatically populate frameworks with market data.

Enables async-first working practices by providing tools to draft decision docs, convert meetings to async artifacts, score status updates, and triage sync vs async tasks. It also offers reference tools for the Open and Async book's principles and coaching prompts.

Enables delivery leads to query explainable programme health, prioritized risks, dependency impacts, change request effects, blocked decisions, and evidence-backed claims with refusal on unsupported assertions, all via deterministic tools and telemetry.

MCP server enabling AI agents to interact with OpenProject API v3 for project management, including creating and managing work packages, projects, comments, time entries, boards, and user dashboards.

Enables AI-powered competitor monitoring and daily schedule optimization by integrating news data with calendar and task management tools like Google Calendar, Jira, and Asana. It allows users to automate intelligence gathering and generate structured daily plans based on strategic priorities.

Enables AI agents to break down complex tasks into manageable pieces using a structured JSON format with task tracking, context preservation, and progress monitoring capabilities.

A Model Context Protocol (MCP) server that connects AI assistants to Jira Server/Data Center, enabling issue management, JQL search, sprint tracking, and natural language interaction with Jira.

Dynamically exposes over 100 Jira Software Cloud REST API operations as fully typed tools for LLMs to interact with, supporting SSE and Stdio transports.

An MCP server exposing internal business operations as tools — task management (create, list, update status) and RAG-style semantic search over an internal knowledge base (leave, expense, and onboarding policies) that any MCP-compatible AI agent can call directly for grounded, non-hallucinated answers.

Enables AI to read live weather data and manage a persistent to-do list through MCP tools, demonstrating both read and write capabilities without API keys.

A Python MCP server that retrieves requirements and bug data from TAPD platform to provide AI clients with project management information.

Enables AI clients such as Cursor to interact with GitHub repositories and perform issue listing, triage, health checks, prioritization, commenting, weekly digests, and release-note generation through purpose-built MCP tools.

Provides complete FreshBooks integration with 87 tools covering accounting, invoicing, time tracking, expense management, client/project management, and financial reporting through OAuth2 authentication.

Enables AI coding assistants to log billable hours into the Keeping time-tracking service via MCP tools, with dry-run protection for all write operations.

Exposes the WCC event, mentorship, and analytics pipeline tools as MCP endpoints with per-group authentication and dry-run support, enabling agents to manage events, mentors, and analytics.

MCP server that connects to Jira Data Center, enabling issue search, retrieval, creation, comments, workflow transitions, project listing, arbitrary JQL, and turning meeting notes into structured Jira stories, tasks, and bugs.