Can my AI automatically review and bulk-approve pending posts?

Yes. Instruct the agent to run `list_posts` filtered by 'pending_approval'. Tell your LLM to ensure they lack profanities or adhere strictly to brand tone. If they pass, you can command the AI to loop over their unique IDs mapping the `approve_post` mutation simultaneously, scheduling the calendar effortlessly.

Can I leave comments for the rest of my design team through this?

Absolutely. Using the `reject_post` functionality or directly targeting `add_comment` on a specific Post ID, the agent injects your exact critique ("Make the background logo larger") back into the underlying Planable portal in real-time. Your team sees your notes just as if you were logged onto their board.

Will the API tell me exactly which social channel the post is meant for?

Yes! Running `list_pages` maps the organizational identifiers. The API correlates structural pages inside your workspace to logical federated networks (Facebook, LinkedIn, TikTok), telling your agent explicitly what bounds to consider regarding content formatting constraints.

Planable MCP Server for Google ADK 10 tools — connect in under 2 minutes

Name: Planable
Availability: InStock
Author: Vinkius

google.github.io/adk-docs/tools/mcp-tools

Built by Vinkius GDPR 10 Tools SDK

Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add Planable as an MCP tool provider through Vinkius and your ADK agents can call every tool with full schema introspection.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from google.adk.agents import Agent
from google.adk.tools.mcp_tool import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import (
    StreamableHTTPConnectionParams,
)

# Your Vinkius token. get it at cloud.vinkius.com
mcp_tools = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    )
)

agent = Agent(
    model="gemini-2.5-pro",
    name="planable_agent",
    instruction=(
        "You help users interact with Planable "
        "using 10 available tools."
    ),
    tools=[mcp_tools],
)

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Planable MCP Server

Connect your Planable workspaces directly to your AI agent to radically streamline your social media collaboration loops. You can review scheduled posts, approve mockups, respond to team comments, and oversee the content pipeline directly from your primary interface.

Google ADK natively supports Planable as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 10 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.

What you can do

Workspace & Pages — View active workspaces, team members, and all connected social accounts isolated in their respective boundaries.
Content Pipeline — Retrieve post drafts, schedule future publications, and query statuses (draft, pending_approval, scheduled, published).
Approval Workflow — Radically speed up content sign-off. Instruct your AI to transition posts from pending directly to approved, or formally reject them with custom revision notes.
Collaboration — Add, fetch, and monitor chronological threaded comments on any isolated post.

The Planable MCP Server exposes 10 tools through the Vinkius. Connect it to Google ADK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Planable to Google ADK via MCP

Follow these steps to integrate the Planable MCP Server with Google ADK.

Install Google ADK

Run pip install google-adk

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Create the agent

Save the code above and integrate into your ADK workflow

Explore tools

The agent will discover 10 tools from Planable via MCP

Why Use Google ADK with the Planable MCP Server

Google ADK provides unique advantages when paired with Planable through the Model Context Protocol.

Google ADK natively supports MCP tool servers. declare a tool provider and the framework handles discovery, validation, and execution

Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with Planable

Production-ready features like session management, evaluation, and deployment come built-in. not bolted on

Seamless integration with Google Cloud services means you can combine Planable tools with BigQuery, Vertex AI, and Cloud Functions

Planable + Google ADK Use Cases

Practical scenarios where Google ADK combined with the Planable MCP Server delivers measurable value.

Enterprise data agents: ADK agents query Planable and cross-reference results with internal databases for comprehensive analysis

Multi-modal workflows: combine Planable tool responses with Gemini's vision and language capabilities in a single agent

Automated compliance checks: schedule ADK agents to query Planable regularly and flag policy violations or configuration drift

Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including Planable

Planable MCP Tools for Google ADK (10)

These 10 tools become available when you connect Planable to Google ADK via MCP:

add_comment

Add a comment to a Planable post for team collaboration

approve_post

Approve a Planable post in the approval workflow. Moves it to scheduled status

create_post

Create a Planable post. Instructions: Pass workspace_id, page_id, content text, and scheduled_at (ISO 8601). Post enters approval workflow

get_post

Get a Planable post by ID. Returns full content, media, schedule, approval history, and comments

list_comments

List comments on a Planable post. Returns comment IDs, authors, and text

list_pages

List social pages (connected accounts) in a Planable workspace. Returns page IDs, platform types, and display names

list_posts

List posts in a Planable workspace by status. Returns post IDs, content previews, scheduled times, and approval status. Instructions: status = draft|pending_approval|approved|scheduled|published

list_workspace_members

List members of a Planable workspace. Returns member IDs, names, emails, and roles

list_workspaces

List Planable workspaces. Returns workspace IDs, names, and member counts. Planable is a social collaboration platform for content planning and approval

reject_post

Reject a Planable post with feedback. Returns it to draft for revisions

Example Prompts for Planable in Google ADK

Ready-to-use prompts you can give your Google ADK agent to start working with Planable immediately.

"List all posts in the 'Acme Marketing' workspace that are currently awaiting approval."

"Draft a new Twitter post in our workspace announcing our new AI feature."

"Reject post `98341x` and tell the team to rewrite the hook, it's too salesy."

Troubleshooting Planable MCP Server with Google ADK

Common issues when connecting Planable to Google ADK through the Vinkius, and how to resolve them.

McpToolset not found

Update: pip install --upgrade google-adk

Planable + Google ADK FAQ

Common questions about integrating Planable MCP Server with Google ADK.

How does Google ADK connect to MCP servers?

Import the MCP toolset class and pass the server URL. ADK discovers and registers all tools automatically, making them available to your agent's tool-use loop.

Can ADK agents use multiple MCP servers?

Yes. Declare multiple MCP tool providers in your agent configuration. ADK merges all tool schemas and the agent can call tools from any server in a single turn.

Which Gemini models work best with MCP tools?

Gemini 2.0 Flash and Pro models both support function calling required for MCP tools. Flash is recommended for latency-sensitive use cases, Pro for complex reasoning.