Planable MCP Server for OpenAI Agents SDK 10 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Planable through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MCPServerStreamableHttp(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
) as mcp_server:
agent = Agent(
name="Planable Assistant",
instructions=(
"You help users interact with Planable. "
"You have access to 10 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from Planable"
)
print(result.final_output)
asyncio.run(main())
* 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.
The OpenAI Agents SDK auto-discovers all 10 tools from Planable through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Planable, another analyzes results, and a third generates reports, all orchestrated through Vinkius.
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 OpenAI Agents SDK 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 OpenAI Agents SDK via MCP
Follow these steps to integrate the Planable MCP Server with OpenAI Agents SDK.
Install the SDK
Run pip install openai-agents in your Python environment
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
Run the script
Save the code above and run it: python agent.py
Explore tools
The agent will automatically discover 10 tools from Planable
Why Use OpenAI Agents SDK with the Planable MCP Server
OpenAI Agents SDK provides unique advantages when paired with Planable through the Model Context Protocol.
Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety
Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure
Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate
First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output
Planable + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the Planable MCP Server delivers measurable value.
Automated workflows: build agents that query Planable, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries Planable, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through Planable tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query Planable to resolve tickets, look up records, and update statuses without human intervention
Planable MCP Tools for OpenAI Agents SDK (10)
These 10 tools become available when you connect Planable to OpenAI Agents SDK 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 OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK 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 OpenAI Agents SDK
Common issues when connecting Planable to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
Planable + OpenAI Agents SDK FAQ
Common questions about integrating Planable MCP Server with OpenAI Agents SDK.
How does the OpenAI Agents SDK connect to MCP?
MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.Can I use multiple MCP servers in one agent?
MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.Does the SDK support streaming responses?
Connect Planable with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Planable to OpenAI Agents SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.