> ## Documentation Index
> Fetch the complete documentation index at: https://docs.groundforge.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# Quick Start
> Choose the Weather MCP or LangChain Agent path and complete a first governed request.
The fastest way to learn GroundForge is to complete one small weather example and then follow the same request in the platform.
## Before you begin
You need:
* access to [platform.groundforge.ai](https://platform.groundforge.ai);
* an Organization and Workspace;
* the `gforge` CLI for command-line steps;
* Python 3.10 or newer;
* the `groundforge-langchain` wheel supplied with your GroundForge release for the Agent example.
## Path A: Weather MCP
Official Python MCP server with `get_alerts(state)` and `get_forecast(latitude, longitude)`.
```bash theme={null}
git clone https://github.com/modelcontextprotocol/quickstart-resources.git
cd quickstart-resources/weather-server-python
```
Follow [Weather MCP Example](/examples/weather-mcp) to discover the tools, create Gateway rules, test an allowed call, and review the resulting records.
## Path B: LangChain weather Agent
GroundForge external-Agent examples using automatic Channel input handling and explicit adapters.
```bash theme={null}
git clone https://github.com/groundforgeai/demo.git
cd demo
```
Choose one:
* [LangChain Agent Example](/examples/langchain-agent) — automatic Channel input handling;
* [LangChain Agent with Adapters](/examples/langchain-adapter) — explicit input and output conversion.
Then attach a Channel, send a weather question, apply a Gateway rule, and open the Trace.
| Twilio | Mailgun | Slack | Webhook |
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## What to check in GroundForge
After the first request, confirm:
1. the Agent or MCP provider is visible in the selected Workspace;
2. Discovery lists the expected weather capability;
3. the Gateway shows the action you selected;
4. an Operator Task appears when the action is Review;
5. the Trace shows the Channel input, decision, capability call, and response.
The next concept page explains how those resources relate: [Resource Model](/concepts/resource-model).
## Related topics
- [Platform Overview](/platform/overview.md)
- [Introduction](/index.md)
- [Start Langchain Agent Job](/api-reference/endpoints/integrations/start-langchain-agent-job.md)
- [External Agents](/platform/external-agents.md)