Enables persistent, auditable business operations state by storing knowledge, evidence, decisions, tasks, execution receipts, and review results in a local SQLite database, so different sessions can continue the same project.
A simple, beginner-friendly Model Context Protocol (MCP) server written in Python. It lets any MCP-compatible AI client (like Claude Desktop) manage a to-do list on your computer through five tools: add, view, get by ID, complete, and delete.
Enables coding agents to query the dependency graph of a GitHub backlog, retrieve ordered ready work and prerequisite chains, atomically claim issues, and report blockers—so agents work in the correct order and safely in parallel.
MCP server that exposes a TODO list API to AI assistants, enabling natural language management of tasks with create, read, update, and delete operations.
Exposes task-management tools over the Model Context Protocol, letting any MCP client discover and call operations to add, list, and complete tasks persisted to a local JSON file. It serves as the plug layer for a separate task kitchen module, with permissions enforced in the client.
Enables AI assistants to interact with an on-premise Azure DevOps Server 2022, allowing users to list, view, create, and update work items through natural language.
Wraps UOF (U-Office Force) SOAP/ASMX WebServices as MCP tools, enabling AI agents to perform enterprise workflow tasks like form query, application, approval, and case closure via Model Context Protocol.
Allows Claude Code agents to pull tasks from an EasyTopic Kanban board, automate planning, commenting, approval, implementation, and closing of topics.
MCP server that acts as a shim between Claude and the PostGrowth API, exposing seven tools to list clients, manage posts, and handle ClickUp tasks and media uploads. It translates MCP calls into authenticated HTTP requests, keeping business rules and credentials on the server side.
A read-only Model Context Protocol server that connects MCP clients such as Claude Desktop, Claude Code, Cursor or VS Code to KanbanFlow, exposing the configured boards and the tasks assigned to a chosen person across all of them. It resolves board, column, swimlane, color, label and people ids to readable names, reports which boards or columns could not be fully loaded, and never modifies any board.
Lets any MCP client drive the recruiting workflow in natural language: create roles, screen CVs, schedule and manage candidate interviews, and read back scored reports with transcripts.
Enables an AI agent to manage Jira Stories in a self-hosted Jira instance via the Jira REST API v2, including CRUD operations, workflow transitions, and burndown data retrieval.