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Plane MCP Server

Name: Plane
Availability: InStock
Author: Vinkius

plane.so

Built by Vinkius GDPR ToolsFree for Subscribers

Manage Plane.so projects, track issues, review sprint cycles, and audit agile modules completely autonomously.

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What is the Plane MCP Server?

The Plane MCP Server gives AI agents like Claude, ChatGPT, and Cursor direct access to Plane via 6 tools. Manage Plane.so projects, track issues, review sprint cycles, and audit agile modules completely autonomously. Powered by the Vinkius - no API keys, no infrastructure, connect in under 2 minutes.

Built-in capabilities (6)

get_projectlist_cycleslist_labelslist_moduleslist_projectslist_work_items

Tools for your AI Agents to operate Plane

Ask your AI agent "List all cross-functional modules targeting project `project-x`." and get the answer without opening a single dashboard. With 6 tools connected to real Plane data, your agents reason over live information, cross-reference it with other MCP servers, and deliver insights you would spend hours assembling manually.

Works with Claude, ChatGPT, Cursor, and any MCP-compatible client. Powered by the Vinkius - your credentials never touch the AI model, every request is auditable. Connect in under two minutes.

Why teams choose Vinkius

One subscription gives you access to thousands of MCP servers - and you can deploy your own to the Vinkius Edge. Your AI agents only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure and security, zero maintenance.

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…and any MCP-compatible client

Plane MCP Server capabilities

6 tools

get_project

Get specific details of a Plane project

list_cycles

List cycles inside a Plane project

list_labels

List project labels in Plane

list_modules

List modules inside a Plane project

list_projects

List projects in a Plane workspace

list_work_items

List work items (issues) inside a Plane project

What the Plane MCP Server unlocks

Equip any AI agent with direct access to your Plane workspace. Whether you're using Plane Cloud or self-hosting, your AI assistant can seamlessly retrieve projects, analyze agile cycles, and parse the active issues pipeline without forcing you to click through kanban boards manually.

What you can do

Projects & Core Entities — Extract isolated project architectures spanning across your Workspace, pulling high-fidelity descriptions and status parameters.
Agile Cycles (Sprints) — Command the agent to list and structure your active development cycles, evaluating timelines and completion statuses.
Work Items (Issues) — Perform deep sweeps over tasks and explicit tickets inside boundary states, analyzing what your engineering team is actually building.
Modules & Taxonomy — Read epics (modules) and static categorization labels dictating your issue pipelines.

How it works

1. Install this integration onto your agent layer
2. Provide your Plane Personal API Key (and optionally, your self-hosted API URL)
3. Start fetching sprints and active cycles immediately from Cursor, Claude, or any MCP client

Who is this for?

Project Managers — instantly retrieve all pending tasks in the current cycle (list_cycles & list_work_items) and summarize progress dynamically.
Lead Engineers — inspect the ticket backlog without leaving your IDE; write code and verify module requirements consecutively.
Product Teams — cross-reference structured modules versus labels without dealing with the visual planner interface.

Frequently asked questions about the Plane MCP Server

Can my AI automatically aggregate all open issues inside our active sprint?

Yes. First, request the active iteration window by calling list_cycles. The agent will isolate today's active cycle bounds. Following that, it will invoke list_work_items directly constrained by that cycle object, outputting an exhaustive summary of untouched or blocking tickets.

How does the agent handle custom workspace slugs or self-hosted URLs?

The system dynamically accepts a PLANE_BASE_URL credential. If you are doing an on-premise installation running inside your homelab or company AWS cloud, you merely inject your private domain (e.g., https://plane.internal.acme.com). The workspace slug is seamlessly accepted as a contextual execution parameter during standard query prompts.

Can I request specific details of a long-term module (epic)?

You can instruct the agent to execute list_modules. It extracts the cross-functional epics spanning your workspace project. Your AI can read these top-level module architectures to contextually understand what the core functionality of the project repository aims to achieve.