Nifty's Model Context Protocol (MCP) server is the ideal way for AI assistants to interact with Nifty.
With Nifty's MCP server, you can empower all aspects of your workflow, such as:
Read the current state of a project and generate a stakeholder report
Convert AI assistant conversation into a task to capture actionable momentum
Message in Nifty from within your LLM to add context to the content populated via MCP
Display and track your agentic workflow progress within a task board
Identify abandoned tasks across projects that have no assignee, due date, or other indicators of progress
The Benefits of Nifty's MCP Server
Nifty's MCP server was built to maximize your AI experience in a variety of ways:
Token Efficient: We rearchitected Nifty's technology to be AI-native to minimize your token usage with every request.
Broad Scope: Our ever-expanding scope of what can be achieved via MCP allows you to touch the full breadth of your workflow.
Easy Install (coming soon): Click to install, no need to manage your config file or run scripts.
Nifty's MCP Scope Includes:
Members
Portfolios
Projects
Lists
Statuses
Tasks
Tags
Dates
Custom Fields (coming soon)
Messages
Docs (coming soon)
Setting Up Nifty's MCP
Nifty's MCP implementation varies based on the LLM you're using. Be sure to follow the guide to your LLM to correctly install Nifty's MCP.
For all installs, you'll want to start by accessing the Settings option in your dropdown menu and locating the MCP & AI Assistants tab in your sidebar.
App Scopes
When integrating with the MCP, you'll be prompted to select a scope based on your needs. The below will help you understand the different scope types.
Read only
Can only retrieve/view data (list, get, search)
Cannot create, update, or delete anything
Good for: dashboards, reporting, auditing, or giving your LLM visibility without risk of changes
Full Access
Can read and write — create, update, delete, and retrieve anything the MCP server supports
No restrictions on what actions can be taken
Good for: power users who want their LLM to take full action on their behalf
Custom
You select which specific permissions to grant
Best when you know exactly what the token will be used for
Good for: situations where you want your LLM to do some things but not others — e.g. create tasks but never delete projects
Claude Desktop via OAuth
Follow the below steps to add a custom connector for the Nifty MCP in Claude.
Start by opening your Claude desktop app and go to Settings within your Profile.
Next, navigate to Connectors in the settings sidebar and Add a new custom connector.
Copy the MCP Server and Client ID details from step one in Nifty as seen below.
Add these details into the Add custom connector pop up then Add the connector.
Following this step, you will be requested to log into Nifty and approve Claude's access. Restart the Claude desktop app and give the Claude a prompt such as "What's the latest task updated in Nifty".
Cursor / Custom
Cursor / Custom implementations will require you to add a small amount of code into the config file of your LLM, but first, you'll need to create a token.
Add Your Code to the Config
Copy the code snippet with the copy icon to the right of the text box.
Cursor Config
From inside of the Cursor desktop app, select Settings. In the Settings sidebar, select Tools & MCPs and Add Custom MCP.
A sidebar editor will open for you to paste the code snippet into the config file. Note that the {mcpServers:} code may already be there, meaning you can remove the duplicate of this code when pasting the code snippet from Nifty.
Save the added code and restart the Cursor desktop app.
Final Steps
Back in Nifty, select I pasted it.
Restart your LLM and send a prompt for the Nifty MCP, after which you can Test your connection to confirm that your token was properly added into the config.
The two most common errors faced in this step are either
Code added to the incorrect place of the config file
Failure to restart your AI client application following the code addition to the config file
In addition to this test, you can try prompting your LLM to interact with Nifty via the MCP, at which point your AI assistant will verify if it is able to reach the Nifty MCP server.
OpenAI Custom App via OAuth
For the MCP beta, you'll need to create an OAuth app in ChatGPT.
Creating a ChatGPT app in Nifty
Copy the URL in Step 1 of the ChatGPT connection steps, then go to the App Center in Nifty.
Navigate to the Integrate with API tab and Create app.
Name the app ChatGPT and add the Redirect URI copied from before. Select your scope and Create app.
Be sure to save your Client ID and Client Secret, as you will need them for the next step in creating the ChatGPT app.
Creating a Nifty App in ChatGPT Browser
Start by navigating to the Profile of ChatGPT in the browser app and go to Settings.
In the Apps section of Settings, go to Advanced settings.
Enable Developer mode, then select Create app.
In the New App screen, title the app Nifty and place the copied URI in the Connection field. Click the tickbox, and click on Advanced OAuth settings.
In advanced OAuth settings, input your Client ID and Client Secret below the Callback URL, then Create the app which will prompt you to sign into Nifty.
After the app is created, log into Nifty via the ChatGPT interface to complete the integration.