Kagan runs on your own machine — the client starts it, so there is no endpoint to ping. 563 installs a week from pypi. Last commit 27 Jul 2026.
AI-powered Kanban TUI for autonomous development workflows with agent orchestration
We read the source, 18 h ago · rules 3dff92dd89df
What this server is able to do. For an MCP server this is often the job itself — a terminal server runs commands because that is what it is for. Listed so you know what you are plugging in, not as an accusation.
proc = Bun.spawn(["sh", "-c", command], {
Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.
We found places where it runs commands, builds paths or queries from values it is given. None of that is a flaw by itself — it becomes one when the code changes, and code changes quietly between releases. We re-read it on every one.
This server runs on your own machine — install it with the package manager and the client starts it for you. Package name taken from the official registry entry.
claude mcp add kagan -- uvx kagan
{
"mcpServers": {
"kagan": {
"args": [
"kagan"
],
"command": "uvx"
}
}
}
[mcp_servers.kagan]
command = "uvx"
args = ["kagan"]
{
"mcpServers": {
"kagan": {
"args": [
"kagan"
],
"command": "uvx"
}
}
}
{
"mcpServers": {
"kagan": {
"args": [
"kagan"
],
"command": "uvx"
}
}
}
This one needs environment variables set before it will start:
KAGAN_OPENAI_API_KEY (OpenAI API key for agent execution (if using OpenAI backend)), KAGAN_ANTHROPIC_API_KEY (Anthropic API key for agent execution (if using Claude backend)), KAGAN_DB_PATH (Custom path for Kagan database file).
The author declared them in the registry entry; get the values from the project itself.
Integrates agents with Linear software development workflows.
A Jira-lite MCP server that guides planning-first workflows for AI-assisted development.
Shared memory + orchestration for your coding agents. Local-first MCP, vector RAG.
Task management for AI agents with hierarchical tasks, dependencies, sprints, and coordination.
Per-env roadmap board for WithVibe — an MCP server the orchestrator drives to plan and track work.
Kanban boards, sprints, tickets and a team wiki, with versioned writes for concurrent agents.
Task & board management for AI agents + humans. Kanban, comments, digests via MCP.
Tre — shared memory kanban for humans and agents (MCP Streamable HTTP).
Answers built from our own checks of this server.