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Plane mit Gemini verbinden — über MCP

Manage Plane (open-source project management) workspaces, projects, issues, cycles, modules from any AI agent. 10 tools, API key auth.

HCBy HelpCode teamUpdated 2 min read Open source on GitHub

No credit card · 7-day trial · Self-host alternative available

MCP connector

Plane

Manage Plane (open-source project management) workspaces, projects, issues, cycles, modules from any AI agent. 10 tools, API key auth.

Tools

10

Region

INTL

Category

project-management

Authentication

API Key

Required env vars

PLANE_API_KEY
Install in one click on Cloud

7-day free trial · No credit card

  • 7-day free trial
    No credit card required
  • GDPR & SOC 2 ready
    EU data residency, audit logs
  • Open-source on GitHub
    Source-available BSL-1.1
  • Works with ChatGPT, Claude, Gemini
    Any MCP-compatible client

No install? Use cloud.anythingmcp.com directly.

Sign in, install the Plane in one click, paste the credentials, mint an MCP API key — done. No Docker, no git clone, no local server to run.

Open Cloud

TL;DR

Manage Plane (open-source project management) workspaces, projects, issues, cycles, modules from any AI agent. 10 tools, API key auth.

💡 Keine Installation? Nutze cloud.anythingmcp.com direkt. Einloggen, Connectors → Plane klicken, Zugangsdaten einfügen, MCP-API-Key erzeugen — fertig. Kein Docker, kein git clone, kein lokaler Server.

Plane + Gemini

Manage Plane (open-source project management) workspaces, projects, issues, cycles, modules from any AI agent. 10 tools, API key auth.

Voraussetzungen

Die vollständige Setup-Anleitung ist in den Connector eingebaut (im Store sichtbar, wenn du den Connector auswählst). Benötigte Umgebungsvariablen für diesen Connector:

PLANE_API_KEY

Schritt 1 — Zugangsdaten holen

This connector wraps the Plane REST API v1 (api.plane.so/api/v1 — or your self-hosted host).

Setup:

  1. Log into your Plane instance → top-right avatar → API Tokens → Create new token.
  2. Note the workspace slug (the part of URLs like app.plane.so/<slug>/projects).
  3. Set PLANE_API_KEY. For self-hosted, also set PLANE_HOST (e.g. https://plane.yourdomain.com) — defaults to cloud (api.plane.so).

Authentication: X-API-Key: ${PLANE_API_KEY}.

Hierarchy: Workspace → Project → Issue → Sub-issue. Cycles + Modules are issue containers within a project for sprint planning / feature grouping.

…(continued in the in-app connector instructions)

Schritt 2 — Adapter installieren

git clone https://github.com/HelpCode-ai/anythingmcp.git
cd anythingmcp && docker compose up -d

Schritt 3 — Connector in Gemini hinzufügen

Gemini CLI liest MCP-Server aus ~/.gemini/settings.json (oder %APPDATA%\gemini\settings.json unter Windows). Hinzufügen:

{
  "mcpServers": {
    "anythingmcp": {
      "httpUrl": "https://cloud.anythingmcp.com/mcp",
      "headers": { "Authorization": "Bearer YOUR_MCP_API_KEY" }
    }
  }
}
  1. Hole deinen MCP API Key aus AnythingMCP → Profil → MCP API Keys → Neuer Key.
  2. Speichern und gemini neu starten.
  3. /mcp in Gemini CLI ausführen — Plane sollte als verfügbar gelistet sein.
  4. Vertex AI Studio: https://cloud.anythingmcp.com/mcp im tools-Array der Anfrage mit demselben Bearer-Header übergeben.

Verfügbare Tools

ToolWhat it does
plane_list_workspacesList all workspaces the API key can access
plane_list_projectsList projects in a workspace
plane_get_projectGet one project
plane_list_issuesList issues in a project
plane_get_issueGet one issue with full description + custom properties
plane_create_issueCreate an issue
plane_update_issueUpdate an issue (PATCH semantics)
plane_list_statesList states (issue statuses) defined in a project
plane_list_cyclesList cycles (sprints) in a project
plane_list_modulesList modules (feature groups) in a project

FAQ

Unterstützen Gemini 1.5 Pro oder 2.x MCP? Ja — Gemini CLI ≥ 0.4 und die Vertex AI Tools API akzeptieren MCP httpUrl-Connectors mit Bearer-Header.

Nächste Schritte

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