Can I add a new datapoint to a goal from the agent?

Yes! Use the `add_datapoint` action with the goal slug and the value. You can also add an optional comment. Your agent will log it to Beeminder instantly.

How do I check if I'm in danger of derailing on a goal?

Simply ask the agent to `get_goal_status` with the Goal Slug. It will return the road status color (e.g., green, yellow, orange, red) and a summary of how much time or value remains.

Does the integration allow me to create new goals?

Currently, the toolset focuses on managing existing goals (logging data, checking status). Creating new goals with complex 'Yellow Brick Road' configurations must be done on the Beeminder website.

Beeminder MCP Server for OpenAI Agents SDK 10 tools — connect in under 2 minutes

Name: Beeminder
Availability: InStock
Author: Vinkius

openai.github.io/openai-agents-python/mcp

Built by Vinkius GDPR 10 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Beeminder through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.

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

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="Beeminder Assistant",
            instructions=(
                "You help users interact with Beeminder. "
                "You have access to 10 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from Beeminder"
        )
        print(result.final_output)

asyncio.run(main())

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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 Beeminder MCP Server

Connect your Beeminder account to any AI agent and integrate goal tracking into your daily workflow through natural conversation.

The OpenAI Agents SDK auto-discovers all 10 tools from Beeminder through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Beeminder, another analyzes results, and a third generates reports, all orchestrated through Vinkius.

What you can do

Goal Oversight — List and inspect all active goals to keep your commitments front and center.
Data Management — Add, update, and delete datapoints for your goals to stay on your 'Yellow Brick Road'.
Status Monitoring — Check real-time road status colors and 'limsum' summaries to avoid derailment.
Goal Refresh — Trigger manual refreshes for your goals to ensure the latest data is reflected.
Charge Auditing — List recent charges and pledges associated with your account.

The Beeminder 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 Beeminder to OpenAI Agents SDK via MCP

Follow these steps to integrate the Beeminder 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 Beeminder

Why Use OpenAI Agents SDK with the Beeminder MCP Server

OpenAI Agents SDK provides unique advantages when paired with Beeminder 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

Beeminder + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the Beeminder MCP Server delivers measurable value.

Automated workflows: build agents that query Beeminder, process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents. one queries Beeminder, another analyzes results, a third generates reports

Data enrichment pipelines: stream data through Beeminder tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query Beeminder to resolve tickets, look up records, and update statuses without human intervention

Beeminder MCP Tools for OpenAI Agents SDK (10)

These 10 tools become available when you connect Beeminder to OpenAI Agents SDK via MCP:

add_datapoint

Add a new datapoint to a goal

delete_datapoint

Delete a datapoint

get_goal

Get specific goal details

get_goal_status

Check the current status of a goal

get_user_info

Get Beeminder user profile

list_charges

List recent charges/pledges

list_datapoints

List datapoints for a goal

list_goals

List all active Beeminder goals

refresh_goal

Trigger a refresh for a goal

update_datapoint

Update an existing datapoint

Example Prompts for Beeminder in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Beeminder immediately.

"List all my active Beeminder goals."

"Log 500 words to my 'Reading' goal."

"Check status for goal 'gym'."

Troubleshooting Beeminder MCP Server with OpenAI Agents SDK

Common issues when connecting Beeminder to OpenAI Agents SDK through the Vinkius, and how to resolve them.

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

Beeminder + OpenAI Agents SDK FAQ

Common questions about integrating Beeminder MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.