Agentic Backlog MCP Server
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Agentic Backlog MCP Server show my open tasks"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Agentic Backlog MCP Server
Local-first MCP server for AI backlog management.
This package runs over stdio (Node.js) and forwards MCP tool calls to a running backlog API.
Exposed tools
backlog.identify_projectbacklog.healthbacklog.versionbacklog.list_projectsbacklog.get_projectbacklog.get_kanban_urlbacklog.create_taskbacklog.list_tasksbacklog.get_taskbacklog.find_tasks_by_titlebacklog.update_taskbacklog.update_task_by_titlebacklog.delete_taskbacklog.update_task_statusbacklog.add_task_notebacklog.plan_from_contextbacklog.get_focusbacklog.claim_taskbacklog.release_taskbacklog.restore_taskbacklog.get_boardbacklog.get_console_table
Related MCP server: boardagent-mcp
Requirements
Node.js 18+
Environment
BACKLOG_API_BASE_URL=http://127.0.0.1:38117/api
BACKLOG_REQUEST_TIMEOUT_MS=1800
BACKLOG_API_FAIL_FAST_MS=15000
BACKLOG_API_FAILURE_THRESHOLD=1Run locally
npm install
npm run build
npm startFor development:
npm run devMCP config example
.mcp.json file:
{
"mcp": {
"agentic-backlog": {
"command": "npx",
"args": ["-y", "@hakenshi/agentic-backlog-mcp-server"],
"env": {
"BACKLOG_API_BASE_URL": "http://127.0.0.1:38117/api"
}
}
}
}Notes
This server uses
stdiotransport only.Do not use
console.login MCP stdio mode (stdout breaks JSON-RPC). Logs must go tostderr.backlog.delete_taskrequires explicitconfirm: "DELETE".backlog.plan_from_contextis preview-only by default. Setapply: trueto persist changes.API resilience is fail-fast: when repeated timeout/5xx errors happen, the server opens a short circuit window and returns immediate 503 errors so agent runs do not stall.
Available Tools
22 toolsbacklog.add_task_noteAdd task noteC
Adds a task note through the running backlog API.
Inputs: note (required), task_id (required), source, agent_id, +3 more.
backlog.claim_taskClaim taskB
Claims a task with TTL for an agent/session to avoid multi-agent collisions.
Inputs: task_id (required), agent_id (required), session_id (required), note, +3 more.
backlog.create_taskCreate taskC
Creates a task through the running backlog API.
Inputs: title (required), project_id (required), source, status, +6 more.
backlog.delete_taskDelete taskC
Deletes a task through the running backlog API.
Inputs: confirm (required), task_id (required), idempotency_key.
backlog.find_tasks_by_titleFind tasks by titleC
Finds tasks in a project by title keywords using backlog API task list.
Inputs: query (required), project_id (required), limit.
backlog.get_boardGet board snapshotC
Returns board grouped snapshot from the running backlog API.
Inputs: project_id (required).
backlog.get_console_tableGet board as console tableC
Returns a console-table style board snapshot from backlog API.
Inputs: project_id (required), limit.
backlog.get_focusGet focusB
Returns what matters now for a project: top priority, blocked, stale, and in progress tasks.
Inputs: project_id (required), stale_hours.
backlog.get_kanban_urlGet kanban URLC
Returns a browser URL for visual kanban from the running backlog API.
Inputs: project_id (required), base_url.
backlog.get_projectGet projectB
Returns project metadata and board summary from the running backlog API.
Inputs: project_id (required).
backlog.get_taskGet taskA
Returns a single task by id from the running backlog API.
Inputs: task_id (required).
backlog.healthBacklog healthA
Checks backlog API health and connectivity before mutations.
Inputs: no named parameters.
backlog.identify_projectIdentify or create projectB
Detects git context and resolves/creates a project in the running backlog API (Docker app source of truth).
Inputs: cwd, name, description.
backlog.list_projectsList projectsC
Lists projects from the running backlog API.
Inputs: limit.
backlog.list_tasksList tasksC
Lists project tasks from the running backlog API.
Inputs: project_id (required), limit, status.
backlog.plan_from_contextPlan tasks from contextC
Delegates planning to running backlog API planner endpoint.
Inputs: context (required), project_id (required), apply, source, +4 more.
backlog.release_taskRelease task claimC
Releases an active task claim for the given agent/session.
Inputs: task_id (required), agent_id (required), session_id (required), source, +1 more.
backlog.restore_taskRestore taskC
Restores a soft-deleted task within restore window.
Inputs: task_id (required), source, idempotency_key.
backlog.update_taskUpdate taskC
Updates task fields through the running backlog API.
Inputs: task_id (required), title, reason, source, +8 more.
backlog.update_task_by_titleUpdate task by titleC
Finds a task by title query and updates it through the backlog API.
Inputs: query (required), project_id (required), title, reason, +9 more.
backlog.update_task_statusUpdate task statusC
Moves a task between states through the running backlog API.
Inputs: status (required), task_id (required), reason, source, +4 more.
backlog.versionBacklog versionA
Returns API version and protocol compatibility information.
Inputs: no named parameters.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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TDQS
Scored across 22 tools
Many tools are distinct, but there are several overlapping boundaries: get_board and get_console_table both return board snapshots, update_task/update_task_by_title/update_task_status all mutate tasks, and get_focus/list_tasks overlap as list-like views. Descriptions help, but an agent could easily pick the wrong one for state changes or snapshot retrieval.
Names consistently use the backlog. prefix with snake_case verb_noun construction (list_tasks, create_task, update_task). Minor deviations are bare nouns health and version and the looser get_/list_ distinction, but the overall pattern is predictable and readable.
22 tools is on the heavy side and sits in the 16-25 borderline range. Many could be consolidated (board formats, update variants, health/version), though the broad project/task/planning/claim domain explains some of the volume.
The surface covers task CRUD well, including restore, status transitions, notes, claims, board snapshots, focus, and planning. Minor gaps exist such as no project update/delete and limited search beyond title keywords, but core agent workflows do not hit dead ends.
Maintenance
Related MCP Connectors
Task and sprint coordination for humans and AI agents, with scoped API keys and full audit trail.
Durable background job execution, async task scheduling, and state persistence for AI agents.
Task management for teams building with AI agents. Agents claim tasks and report progress.
Project management MCP for AI agents with safe task reads and writes.
Related MCP Servers
- AlicenseNot gradedqualityCmaintenanceA self-hosted backlog tracker with priority scoring and an MCP server, enabling AI agents to autonomously pull, work on, and update tasks via JSON-RPC tools.MIT
- AlicenseAqualityBmaintenanceEnables AI agents to manage tasks on a local-first board via MCP, exposing task creation, updates, and queries through a thin adapter over the REST service.7MIT
- FlicenseNot gradedqualityCmaintenanceEnables AI assistants to manage a local-first Kanban board with Azure DevOps-style workflow rules, including task creation, status updates, subtask breakdown, full-text search, daily summaries, and next-task suggestions.-
- FlicenseNot gradedqualityBmaintenanceEnables managing projects, features, tasks, dependencies, executions, and human review through a Streamable HTTP endpoint, along with persistent inter-agent cooperation via task messaging and event subscriptions. It also supports administrative actions such as approvals, cancellations, unblocking, and member management.-