A Model Context Protocol (MCP) server for interacting with the Clarity API
Project description
Clarity MCP Server
A Model Context Protocol (MCP) server for interacting with the Clarity API. This server enables Cursor and other MCP-compatible clients to access Clarity backend services.
Installation
Prerequisites
- Python 3.10 or higher (required for
fastmcp) uvpackage manager (recommended for this project)
Installing uv
On macOS (using Homebrew):
brew install uv
On Linux/macOS (using curl):
curl -LsSf https://astral.sh/uv/install.sh | sh
On Windows:
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
Setting up the project
Once uv is installed, it will automatically manage Python versions. You can install dependencies and run the server:
# Install dependencies (uv will automatically use Python 3.10+)
# IMPORTANT: Run this WITHOUT activating any venv - just run it directly
uv sync
# Install the package in editable mode so the 'clarity-mcp' command is available
# This makes the entrypoint script available
uv pip install -e .
# Verify the installation worked
uv run which clarity-mcp
# Run the server locally (for development)
uv run clarity-mcp
Important Notes:
- Never activate the venv manually - just run
uv syncanduv rundirectly in your shell uv synccreates a.venvdirectory automatically, but you never need to activate/deactivate ituv pip install -e .installs the package in editable mode, making theclarity-mcpcommand availableuv runautomatically uses the venv thatuvmanages - this is "no manual virtualenv management"uvx clarity-mcpwill only work after the package is published to PyPI. For local development, useuv run clarity-mcpafter runninguv syncanduv pip install -e .
The server will run over stdio and communicate with MCP clients.
Configuration
The server requires the following environment variables:
CLARITY_EMAIL(required): Your Clarity account email addressCLARITY_PASSWORD(required): Your Clarity account passwordCLARITY_BASE_URL(optional): Base URL for the Clarity API (defaults tohttps://clarity-backend.up.railway.app/)CLARITY_FRONTEND_URL(optional): Frontend URL for the Clarity Chat API (defaults tohttps://clarity-frontend.up.railway.app)
Setting Environment Variables
You can set environment variables in several ways:
Option 1: Export in your shell
export CLARITY_EMAIL=your_email@example.com
export CLARITY_PASSWORD=your_password
uv run clarity-mcp
Option 2: Use a .env file (with python-dotenv)
Create a .env file in your working directory:
CLARITY_EMAIL=your_email@example.com
CLARITY_PASSWORD=your_password
CLARITY_BASE_URL=https://clarity-backend.up.railway.app/
CLARITY_FRONTEND_URL=https://clarity-frontend.up.railway.app
Option 3: Inline with the command
CLARITY_EMAIL=your_email@example.com CLARITY_PASSWORD=your_password uv run clarity-mcp
Cursor MCP Configuration
Add the following entry to your Cursor mcp.json configuration file:
{
"mcpServers": {
"clarity": {
"command": "uvx",
"args": ["clarity-mcp"],
"env": {
"CLARITY_EMAIL": "your_email@example.com",
"CLARITY_PASSWORD": "your_password",
"CLARITY_BASE_URL": "https://clarity-backend.up.railway.app/",
"CLARITY_FRONTEND_URL": "https://clarity-frontend.up.railway.app"
}
}
}
}
Note:
- Replace
your_email@example.comandyour_passwordwith your actual Clarity credentials - The
CLARITY_BASE_URLandCLARITY_FRONTEND_URLare optional
After adding this configuration, restart Cursor to load the MCP server.
Available Tools
clarity_ping
Health check tool for the Clarity MCP server.
- Input: None
- Output:
{"status": "ok"}
get_company_info
Get company information from the Clarity API.
- Input: None
- Output: Dictionary containing company information
- Errors: Raises
ClarityAPIErrorif the API request fails
get_insights
Get insights from the Clarity API.
- Input:
status(optional): Status filter. Can be a single status (e.g.,"new") or comma-separated multiple statuses (e.g.,"new,ticket_created"). If not provided, returns all insights.
- Output: Dictionary containing insights data
- Errors: Raises
ClarityAPIErrorif the API request fails
Examples:
- Get all insights:
get_insights() - Get only new insights:
get_insights(status="new") - Get new and ticket_created insights:
get_insights(status="new,ticket_created")
chat
Ask questions about your users and their feedback using natural language.
- Input:
query(required): Natural language question about user feedback
- Output: Dictionary containing the chat response with a
responsefield - Errors: Raises
ClarityAPIErrorif the API request fails
Use this tool when you need to understand what users are saying about specific topics, find related feedback, or explore user sentiment.
Examples:
chat(query="What are users saying about onboarding?")chat(query="Where else are users reporting this problem?")chat(query="What are the main complaints about the mobile app?")chat(query="How do users feel about the new pricing?")
Authentication
Note: This server currently uses email/password authentication, which is a temporary MVP approach. The architecture is designed to allow swapping authentication methods (e.g., API keys or OAuth) in the future without changing the MCP tool interface.
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