Beeminder MCP. Manage commitments and track progress via AI chat.
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…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
Beeminder connects your goal tracking directly to your AI agent. Use it to list active goals, log new datapoints, and check your 'road status' without leaving your workflow.
It lets you manage your commitments and track progress against self-defined metrics—all through natural conversation with your AI client.
What your AI agents can do
Add datapoint
Adds a new, specific metric measurement to a defined goal.
Delete datapoint
Removes an existing datapoint from a goal's history.
Get goal
Retrieves detailed information about a specific goal.
Checks a goal's progress and alerts you if you're nearing a derailment.
Adds, updates, or deletes specific metrics for a goal to keep your progress accurate.
Provides a full list of your active goals for quick reference.
Lists recent charges and pledges associated with your Beeminder account.
Forces the system to fetch the absolute latest data for a specific goal.
Ask AI about this MCP
Supported MCP Clients
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Beeminder MCP Server: 10 Tools for Goal Data Management
These tools let your AI client read, write, and manage every aspect of your goals and progress data within Beeminder.
019d755aadd datapoint
Adds a new, specific metric measurement to a defined goal.
019d755adelete datapoint
Removes an existing datapoint from a goal's history.
019d755aget goal
Retrieves detailed information about a specific goal.
019d755aget goal status
Checks the current progress and road status of a goal.
019d755aget user info
Retrieves your core Beeminder user profile details.
019d755alist charges
Shows a list of your recent financial pledges or charges.
019d755alist datapoints
Retrieves all historical data points logged for a specific goal.
019d755alist goals
Lists every active goal you have set up on the platform.
019d755arefresh goal
Forces the system to update the goal's data cache to ensure you have the latest status.
019d755aupdate datapoint
Modifies an existing datapoint with a corrected value.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Beeminder, then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,700+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
What you can do with this MCP connector
Beeminder lets your AI client manage your goals right where you are working. You'll use this server to check progress, log metrics, and review your financial commitments without leaving your workflow. You can use list_goals to see every active goal you've set up. You'll find out your core profile details with get_user_info.
You can check a specific goal's progress and see if you're getting close to a derailment using get_goal_status. If you need the absolute latest numbers, use refresh_goal to force the system to update a goal's cache. To keep your progress straight, you can add new metrics using add_datapoint, or change an existing one with update_datapoint.
If a datapoint is wrong, use delete_datapoint to take it out of a goal's history. You can pull all the historical data for a goal by running list_datapoints. To see what you owe or what you've pledged, run list_charges to get a list of your recent financial pledges. You can also look up detailed info on any goal using get_goal.
How Beeminder MCP Works
- 1 Subscribe to the server and enter your Beeminder Username and Auth Token.
- 2 Your AI client makes a request (e.g., 'Check my gym progress').
- 3 The server executes the necessary tool (e.g.,
get_goal_status) and returns the status and data to your AI client.
The bottom line is, your AI client talks to Beeminder, and Beeminder talks back.
Who Is Beeminder MCP For?
Anyone tracking self-improvement or complex metrics needs this. It's for the data-obsessed professional, the biohacker, or the developer who wants to enforce habits using code. If your personal metrics matter, this is for you.
Uses the agent to check if the team's key metrics (e.g., feature adoption rate) hit their goals, logging the data point right from a daily standup chat.
Automates logging metrics (like lines of code written or tests run) directly from the code editor or a script without switching contexts.
Logs daily metrics (like word count or hours spent researching) by simply asking the agent, 'Log 1,500 words to my book goal.'
What Changes When You Connect
- Check your progress instantly. Instead of going to the website and manually checking, you simply ask your agent to
get_goal_statusand get a real-time status update. - Log metrics without leaving your tool. When you write a session's worth of copy, you just tell the agent to
add_datapoint, and the data gets logged immediately. - Audit your commitments easily. Use
list_chargesto see all your recent pledges and financial activity in one chat session. - Maintain data integrity. If you log a number incorrectly, you can use
update_datapointto fix it, ordelete_datapointif it was never right. - Get a full picture of your setup. Use
list_goalsto see all your active goals at a glance, orlist_datapointsto review historical data for one goal.
Real-World Use Cases
Checking project health status
The PM needs to report on the 'Marketing' goal during a standup. They prompt the agent to run get_goal_status. The agent responds that the goal is yellow and they need to act fast, solving the problem before it gets out of hand.
Automating personal logging
A developer finishes a coding sprint. Instead of opening a spreadsheet, they ask the agent to add_datapoint for 'project-x'. The data logs automatically, keeping the progress record updated without context switching.
Reviewing data history
A user wants to see how many times they logged gym visits last month. They ask the agent to list_datapoints for the 'Gym' goal. The agent retrieves the full log, letting the user spot trends they missed.
Correcting an error
A user accidentally logged a datapoint that was wrong. Instead of manually deleting it on the site, they ask the agent to delete_datapoint, ensuring the data is clean and the status is accurate.
The Tradeoffs
Treating data points like random entries
Just logging a number without checking if the goal is active or what the current status is. This can lead to orphaned data or confusing status readings.
→
Always start by using list_goals to confirm the goal slug, then use get_goal_status before running add_datapoint or update_datapoint. This keeps your actions grounded.
Manually refreshing data status
Relying on stale data. If you run a report and it looks wrong, you might assume the underlying data is bad, wasting time troubleshooting the tool.
→
Run refresh_goal first. This forces the system to pull the latest data from Beeminder, ensuring any status you read is current.
Overwriting data without confirmation
Using update_datapoint when you actually meant to start a new metric. This overwrites history and loses the original data point.
→
If you are logging a new metric, use add_datapoint. Only use update_datapoint when you are certain you are correcting a specific, known historical entry.
When It Fits, When It Doesn't
Use this if you need to manage a personal commitment or metric that needs to be tracked over time. The server is ideal for 'quantified self' tracking—logging consistent, sequential data points. Don't use it if you just need to read static documents or manage simple contacts; those tools are better for general knowledge retrieval. If your primary need is auditing financial transactions, use list_charges first to verify the financial history before making any data changes.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Beeminder. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 10 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Tracking goals usually means jumping between dashboards and spreadsheets.
You usually have to log into Beeminder, find the specific goal, navigate to the data entry section, and manually input the number. If you want to see the overall status, you open a second tab, find the status gauge, and cross-reference the two. It's slow, and you're always dealing with context switching.
With the Beeminder MCP Server, you just ask your agent. You tell it, 'Log 500 words to my reading goal.' The agent handles the `add_datapoint` and reports back the updated road status. You stay right where you are.
Get Goal Status: Check your progress in a single chat.
Before, checking status meant logging into the platform, navigating to the goal, and waiting for the page to load the current calculation. If you needed to check multiple goals, you'd repeat that whole process for every single one.
Now, you ask the agent to `get_goal_status`. It runs the check and gives you the immediate status, including if you're yellow or green. It cuts the process down to a single, conversational prompt.
Common Questions About Beeminder MCP
How do I list all my active Beeminder goals using the Beeminder MCP Server? +
Use the list_goals tool. This immediately returns a list of every goal you have set up, so you know exactly what you can track.
What is the difference between `add_datapoint` and `update_datapoint`? +
Use add_datapoint when logging a brand new metric value. Use update_datapoint only when you need to change a specific, existing value that was entered incorrectly.
Can I check my goal status without refreshing the data first? +
It's best practice to run refresh_goal first. This guarantees the agent is reading the most current data before it reports the status via get_goal_status.
How do I see my recent pledges on Beeminder? +
You call the list_charges tool. This provides an easy-to-read list of your recent financial activity and pledges.
How do I use the `get_user_info` tool to check my Beeminder account details? +
This tool retrieves your core profile information. It shows details like your username and account creation date, which is helpful for verifying credentials or logging setup details.
What happens if I try to `add_datapoint` for a goal that doesn't exist? +
The server will return a specific error message indicating the goal slug is invalid. You must use list_goals first to confirm the correct goal slug before attempting to add data.
How can I list all the available datapoints using `list_datapoints`? +
The tool provides a full list of existing datapoints tied to a specific goal. You can review these records to confirm the data logged matches what you expected.
Is there a way to manually refresh a goal using `refresh_goal`? +
Yes, calling refresh_goal forces the server to pull the latest data from Beeminder. This ensures your AI agent sees the most current status, bypassing potential caching issues.
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.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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