Kagan - AI Orchestration Layer
Related Servers
Alternatives to Kagan - AI Orchestration Layer
- AlicenseBqualityDmaintenanceProvides capabilities for searching Jira issues using JQL and retrieving detailed issue information.2496 npm28MIT
- AlicenseBqualityDmaintenanceAnthropic's github MCP server, but better. Support for more endpoints. Including releases and tags, pull request reviews, statuses, rate limit, gists, projects, packages, and even pull request diffs. Indented to be used with MissionSquad's MCP API for secret management (aka your access token).452,514 npm10MIT
- FlicenseNot gradedqualityDmaintenanceA comprehensive project management system that provides a full-featured Kanban board and dashboard accessible to AI agents. It enables agents to programmatically manage projects, tasks, and workflows through a suite of 13 specialized tools and 4 resource types.45 npm4-
Related Servers
- FlicenseNot gradedqualityCmaintenanceMulti-model agent orchestration MCP server that enables plan-code-review-deliver pipelines with configurable providers and models.-
- AlicenseNot gradedqualityAmaintenanceSelf-hosted kanban board that dispatches AI agent fleets against tickets. The embedded Streamable HTTP /mcp endpoint exposes 7 tools to list projects, read boards and tickets, and create, move and comment tickets from any MCP client.27AGPL 3.0
- AlicenseNot gradedqualityBmaintenanceA local kanban board and docs tool that AI agents can drive over MCP. It enables project management without accounts or API keys.MIT

AgentTaskerofficial
AlicenseNot gradedqualityBmaintenanceEnables AI agents to create, query, update, claim, hand off, and complete tasks on a local SQLite-backed, project-namespaced kanban board through stdio MCP tools, including filtering for ready/blocked/stale work and exchanging task attachments. It also lets agents list projects and manage statuses, ownership, and evidence without any server or accounts.MIT- AlicenseNot gradedqualityDmaintenanceAn AI-native kanban board MCP server where agents pull tasks via the Model Context Protocol. It provides tools for task discovery, claiming, progress updates, and review workflows.4MIT
- FlicenseNot gradedqualityDmaintenanceMCP server for agent-first Kanban board management, enabling agents to create, move, comment, and claim pebbles (cards) across statuses like requested, code_creation, testing, validation, and complete, with support for blocking, context feedback, and HIL (human-in-the-loop) transitions.-
TDQS
Scored across 47 tools
Multiple tools cover near-identical ground: run_start, run_execute, run_status, task_run, and task_wait all relate to task execution with unclear boundaries. fs_read_file, fs_write_file, fs_edit_file, bash_exec, and terminal_exec overlap heavily in file/command operations, requiring deep reading to distinguish.
Naming mixes several conventions: verb_noun (task_get, insight_add, fs_read_file), verb-only (run, plan, analyze), and inconsistent grouping (run_status vs run_start vs run_execute). Some tools use nouns (terminal) while others use prefixes (fs_), creating no clear pattern.
47 tools is excessive for a focused orchestration layer, well beyond the 3-15 sweet spot. Many tools could be consolidated (multiple run_* variants, multiple analytics_* tools, multiple fs_* tools), suggesting the surface area was not thoughtfully pruned.
Core domain coverage is quite thorough: task lifecycle (create/get/update/delete), execution (run/stop/wait), files (read/write/list), and insights (list/search/remove) are all represented. Minor gaps exist (e.g., no explicit project delete, no user management), but nothing creates a dead end.