TagoIO MCP Server
OfficialIntegrates with Codeium's Windsurf IDE, allowing developers to access TagoIO device management, data analysis, and platform resources directly within the Codeium development environment.
Enables GitHub Copilot to interact with TagoIO platform resources, providing AI-powered assistance for device management, data analysis, and TagoIO Analysis script generation within VS Code.
Provides integration with Google Gemini CLI, allowing users to access TagoIO device information, perform data analysis, and manage platform resources through Google's AI assistant.
Integrates with JetBrains IDEs through the AI Assistant feature, enabling developers to access TagoIO devices, perform statistical operations, and manage platform resources within JetBrains development environments.
Provides local server capabilities for TagoIO MCP integration, enabling offline development, air-gapped environment support, and custom setups through Node.js-based execution.
Enables integration with OpenAI Agents and ChatGPT, allowing AI assistants to access TagoIO device data, perform statistical analysis, and generate TagoIO Analysis scripts through the OpenAI platform.
Provides integration with Warp terminal through MCP bridge, enabling terminal-based access to TagoIO device management, data analysis, and platform resources.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@TagoIO MCP Servershow me the temperature data from my smart thermostat for the last 24 hours"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
TagoIO | MCP Server
Connect your AI assistant to your TagoIO devices, data, and platform resources — directly from your IDE or AI tool.
Features
Remote Server: Connect instantly via
https://mcp.ai.tago.io— no local setup requiredDevice Management: Access device information, configurations, and real-time data
Data Analysis: Perform statistical operations (sums, averages, reports) on stored data
Platform Integration: Retrieve users, actions, analysis scripts, and account statistics
Code Generation: AI-powered TagoIO Analysis script generation with proper context
Development Support: Debug assistance and tag relationship analysis
Dual Protocol Support: STDIO (default) and HTTP Streamable transport protocols
Quick Start
Get a token — Go to TagoIO Profile Settings and generate a Profile Token
Pick your setup — Remote Server (recommended) or Local Server
Configure your platform — Find your IDE or AI tool below and copy the config
Prerequisites
TagoIO account with a valid Profile Token (generate one here)
Node.js 22+ (download) — only required for the Local Server setup
Remote Server (Recommended)
Connect directly to the TagoIO hosted MCP server at https://mcp.ai.tago.io. No local installation or Node.js required.
Authentication is done via the Authorization header with your Profile Token.
Region: Requests default to US East (us-e1). To connect to a different region, add the x-tagoio-region header:
Header | Value |
|
|
|
|
VS Code
Add to .vscode/mcp.json in your project (or User Settings for global access):
{
"servers": {
"@tago-io/mcp": {
"type": "http",
"url": "https://mcp.ai.tago.io",
"headers": {
"Authorization": "Bearer ${input:tagoToken}"
}
}
},
"inputs": [
{
"type": "promptString",
"id": "tagoToken",
"description": "TagoIO Profile Token",
"password": true
}
]
}VS Code Insiders
Same configuration as VS Code. Add to .vscode/mcp.json or User Settings.
Claude Code
claude mcp add-json @tago-io/mcp '{"type":"http","url":"https://mcp.ai.tago.io","headers":{"Authorization":"Bearer YOUR-TAGOIO-TOKEN"}}'Claude Desktop
Claude Desktop does not natively support HTTP transport. Use the mcp-remote bridge:
Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):
{
"mcpServers": {
"@tago-io/mcp": {
"command": "npx",
"args": [
"-y",
"mcp-remote",
"https://mcp.ai.tago.io",
"--header",
"Authorization: Bearer YOUR-TAGOIO-TOKEN"
]
}
}
}Cursor
Add to ~/.cursor/mcp.json:
{
"mcpServers": {
"@tago-io/mcp": {
"url": "https://mcp.ai.tago.io",
"headers": {
"Authorization": "Bearer YOUR-TAGOIO-TOKEN"
}
}
}
}Windsurf
Add to ~/.codeium/windsurf/mcp_config.json:
{
"mcpServers": {
"@tago-io/mcp": {
"serverUrl": "https://mcp.ai.tago.io",
"headers": {
"Authorization": "Bearer YOUR-TAGOIO-TOKEN"
}
}
}
}JetBrains IDEs
Go to Settings > Tools > AI Assistant > Model Context Protocol (MCP) and add a new server with this JSON:
{
"servers": {
"@tago-io/mcp": {
"url": "https://mcp.ai.tago.io",
"requestInit": {
"headers": {
"Authorization": "Bearer YOUR-TAGOIO-TOKEN"
}
}
}
}
}GitHub Copilot
Add to .vscode/mcp.json (VS Code) or configure via CLI:
{
"servers": {
"@tago-io/mcp": {
"type": "http",
"url": "https://mcp.ai.tago.io",
"headers": {
"Authorization": "Bearer ${input:tagoToken}"
}
}
},
"inputs": [
{
"type": "promptString",
"id": "tagoToken",
"description": "TagoIO Profile Token",
"password": true
}
]
}Google Gemini CLI
Add to ~/.gemini/settings.json:
{
"mcpServers": {
"@tago-io/mcp": {
"httpUrl": "https://mcp.ai.tago.io",
"headers": {
"Authorization": "Bearer YOUR-TAGOIO-TOKEN"
}
}
}
}Amazon Q CLI
Add to ~/.aws/amazonq/mcp.json:
{
"mcpServers": {
"@tago-io/mcp": {
"url": "https://mcp.ai.tago.io",
"headers": {
"Authorization": "Bearer YOUR-TAGOIO-TOKEN"
}
}
}
}OpenAI Agents / ChatGPT
In the OpenAI Agent Builder or ChatGPT MCP settings:
Server URL:
https://mcp.ai.tago.ioProtocol: Streamable HTTP
Authentication: Add
Authorization: Bearer YOUR-TAGOIO-TOKENheader
Warp
Warp does not natively support HTTP transport. Use the mcp-remote bridge.
Add to ~/.warp/mcp.json:
{
"mcpServers": {
"@tago-io/mcp": {
"command": "npx",
"args": [
"-y",
"mcp-remote",
"https://mcp.ai.tago.io",
"--header",
"Authorization: Bearer YOUR-TAGOIO-TOKEN"
]
}
}
}Kiro
Kiro does not natively support HTTP transport. Use the mcp-remote bridge.
Add to .kiro/mcp.json in your project root:
{
"mcpServers": {
"@tago-io/mcp": {
"command": "npx",
"args": [
"-y",
"mcp-remote",
"https://mcp.ai.tago.io",
"--header",
"Authorization: Bearer YOUR-TAGOIO-TOKEN"
]
}
}
}Local Server
Run the MCP server locally via npx. Useful for offline development, air-gapped environments, or custom setups.
Requires Node.js 22+ installed (download).
STDIO Transport (Default)
Best for desktop AI assistants and IDEs. Add this configuration to your platform's config file (see Configuration Paths):
{
"mcpServers": {
"@tago-io/mcp": {
"command": "npx",
"args": ["-y", "@tago-io/mcp-server"],
"env": {
"TAGOIO_TOKEN": "YOUR-TAGOIO-TOKEN"
}
}
}
}For Claude Code, use the CLI:
claude mcp add @tago-io/mcp-server -e TAGOIO_TOKEN=YOUR-TAGOIO-TOKEN -- npx -y @tago-io/mcp-serverFor VS Code / GitHub Copilot, use the inputs pattern for secure token prompting:
{
"servers": {
"@tago-io/mcp": {
"command": "npx",
"args": ["-y", "@tago-io/mcp-server"],
"env": {
"TAGOIO_TOKEN": "${input:tagoToken}"
}
}
},
"inputs": [
{
"type": "promptString",
"id": "tagoToken",
"description": "TagoIO Profile Token",
"password": true
}
]
}HTTP Streamable Transport
For web-based AI platforms or when you need multiple clients connecting simultaneously:
# Start on default port 3000
npx -y @tago-io/mcp-server http
# Or pick a custom port
MCP_PORT=8080 npx -y @tago-io/mcp-server httpYour server will be available at http://localhost:3000.
Authentication: Pass your TagoIO token in the Authorization header:
Authorization: Bearer YOUR-TAGOIO-TOKENIn HTTP mode, each request carries its own token — no TAGOIO_TOKEN environment variable needed. Multiple clients with different credentials can connect at the same time.
Health check: GET /health returns the server name, version, and status.
Configuration Paths
Platform | Config File Path |
VS Code / GitHub Copilot |
|
Claude Desktop |
|
Claude Code | Managed via |
Cursor |
|
Windsurf |
|
JetBrains IDEs | Settings > Tools > AI Assistant > MCP |
Google Gemini CLI |
|
Warp |
|
Amazon Q CLI |
|
Kiro |
|
Authentication
The MCP server accepts two types of TagoIO tokens:
Profile Token (recommended for getting started): Go to TagoIO Profile Settings and generate a new token. This grants full access to your profile.
Analysis Token (for restricted access): Go to Analysis > select your analysis > copy the token. Your analysis must be set to run "External". This limits the MCP server to only the resources the analysis can reach — ideal for production or shared environments where you want to control access via IAM.
Replace YOUR-TAGOIO-TOKEN in any configuration above with your chosen token.
API Endpoints
The server connects to these TagoIO regions:
US East:
https://api.us-e1.tago.io(default)EU West:
https://api.eu-w1.tago.io
Dedicated TagoIO instances are also supported — pass your full API URL as the region value.
How to set the region:
Setup | Method |
Remote Server |
|
Local STDIO |
|
Local HTTP |
|
Troubleshooting
Connection Failed
Check your Profile Token is valid at TagoIO Profile Settings
Ensure correct API endpoint for your region
For the remote server, verify
https://mcp.ai.tago.iois reachable
Authentication Error
Confirm your token has the necessary permissions
Verify the token format — use
Bearer YOUR-TOKENin theAuthorizationheader (HTTP) or theTAGOIO_TOKENenv var (STDIO)
Data Access Issues
Check device permissions in your TagoIO account
Ensure devices have recent data available
mcp-remote Bridge Issues
If using mcp-remote for Claude Desktop, Warp, or Kiro:
Ensure Node.js 22+ is installed (required for
npx)Check that
mcp-remotecan reachhttps://mcp.ai.tago.ioTry running
npx -y mcp-remote https://mcp.ai.tago.io --header "Authorization: Bearer YOUR-TOKEN"manually to verify connectivity
License
This project is licensed under the MIT License - see the LICENSE file for details.
Need Help? Visit the TagoIO Documentation or contact our support team.
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