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., "@MeteoControl MCP Server how much energy did my solar array produce yesterday?"
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.
A Model Context Protocol (MCP) server for the MeteoControl VCOM API v2. This extension allows you to monitor solar arrays, retrieve energy production data, and perform system health checks using natural language via the Gemini CLI.
System Discovery: List all solar systems associated with your account.
Energy Monitoring: Retrieve historical energy production data (Wh/kWh/MWh).
Asset Information: Get technical details about panels, inverters, and site capacity.
Real-time Power: Check instantaneous AC power output.
Multi-Transport Support: Run locally via Stdio or host remotely via SSE.
Multi-Tenant (BYOC): Support for "Bring Your Own Credentials" in a shared environment.
Related MCP server: Tigo Energy MCP Server
To install the extension directly from GitHub:
gemini extensions add https://github.com/your-org/meteocontrol-mcpClone the repository:
git clone https://github.com/your-org/meteocontrol-mcp.git
cd meteocontrol-mcpInstall dependencies and build:
npm install
npm run buildOnce installed, you can ask Gemini about your solar systems:
"List my solar systems."
"What is the energy production for system [systemKey] for the last 24 hours?"
"Show me the technical details for INV1 in system [systemKey]."
If you are using a shared MCP server, you can provide your own credentials directly in your prompts or configure them locally. The tools accept optional apiKey, user, and password arguments.
/health [systemKey]: Perform a comprehensive site health check.
/yield [systemKey]: Retrieve and summarize energy production data.
The server supports multiple modes of operation:
This is the default mode used by the Gemini CLI.
Command: node dist/index.js
Setup: Defined in gemini-extension.json using command and args.
Use this mode to host the MCP server on a central server for multiple users.
Remote mode requires a mandatory MCP_SERVER_TOKEN for security. You can generate a secure token using:
openssl rand -base64 32Environment Variables:
MCP_TRANSPORT=sse
MCP_SERVER_TOKEN=your_generated_token (Required)
PORT=3000 (optional, defaults to 3000)
Run Command:
MCP_TRANSPORT=sse MCP_SERVER_TOKEN=your_token node dist/index.jsYou can run the server as a container for easy deployment.
docker run -i --rm \
-e METEOCONTROL_API_KEY=your_key \
-e METEOCONTROL_USER=your_user \
-e METEOCONTROL_PASSWORD=your_password \
ghcr.io/your-org/meteocontrol-mcp:latestdocker run -d \
-p 3000:3000 \
-e MCP_TRANSPORT=sse \
-e MCP_SERVER_TOKEN=your_token \
-e METEOCONTROL_API_KEY=your_key \
-e METEOCONTROL_USER=your_user \
-e METEOCONTROL_PASSWORD=your_password \
ghcr.io/your-org/meteocontrol-mcp:latestIn your local .gemini/settings.json, add the url and the Authorization header:
{
"mcpServers": {
"meteocontrol": {
"url": "https://your-mcp-server.com/sse",
"headers": {
"Authorization": "Bearer your_generated_token"
}
}
}
}The following environment variables are required for the server to talk to MeteoControl (unless credentials are provided per request):
METEOCONTROL_API_KEY: Your VCOM API key.
METEOCONTROL_USER: Your VCOM username (email).
METEOCONTROL_PASSWORD: Your VCOM password.
Apache License 2.0
| Name | Required | Description | Default |
|---|---|---|---|
| systemKey | Yes | The unique key/ID of the solar system. | |
| apiKey | No | Optional: MeteoControl API Key (if not set on server) | |
| user | No | Optional: MeteoControl Username (if not set on server) | |
| password | No | Optional: MeteoControl Password (if not set on server) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
| Name | Required | Description | Default |
|---|---|---|---|
| systemKey | Yes | The unique key/ID of the solar system. | |
| apiKey | No | Optional: MeteoControl API Key (if not set on server) | |
| user | No | Optional: MeteoControl Username (if not set on server) | |
| password | No | Optional: MeteoControl Password (if not set on server) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
| Name | Required | Description | Default |
|---|---|---|---|
| systemKey | Yes | The unique key/ID of the solar system. | |
| from | Yes | The start date and time (ISO 8601). | |
| to | Yes | The end date and time (ISO 8601). | |
| apiKey | No | Optional: MeteoControl API Key (if not set on server) | |
| user | No | Optional: MeteoControl Username (if not set on server) | |
| password | No | Optional: MeteoControl Password (if not set on server) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
| Name | Required | Description | Default |
|---|---|---|---|
| apiKey | No | Optional: MeteoControl API Key (if not set on server) | |
| user | No | Optional: MeteoControl Username (if not set on server) | |
| password | No | Optional: MeteoControl Password (if not set on server) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v1.0.0get_alertsget_asset_infoget_energy_datalist_systemsEach tool has a clearly distinct purpose: get_alerts retrieves alerts, get_asset_info provides asset details, get_energy_data handles energy data, and list_systems lists systems. There is no overlap or ambiguity between these functions, making it easy for an agent to select the correct tool.
All tool names follow a consistent verb_noun pattern with 'get_' or 'list_' prefixes, using snake_case uniformly. This predictable naming scheme enhances readability and reduces confusion for agents.
With 4 tools, the count is reasonable for a server focused on meteorological control, but it feels slightly thin for comprehensive coverage. It includes core functions like alerts, assets, energy data, and systems, but might benefit from additional tools for broader operations.
The tools cover key read operations (get and list), but there are notable gaps in CRUD coverage, such as missing create, update, or delete functions for alerts, assets, energy data, or systems. This could limit agents in performing full lifecycle management tasks.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
Hosted MCP server for Xweather weather data: conditions, forecasts, alerts, and more.
An MCP server that provides an API to LLMs to manage their JumpCloud resources.
Hosted MCP server for live public-data APIs and Skills for AI agents.
AI-powered incident management and server monitoring via MCP.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/nielsvbrecht/meteocontrol-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server
