diff --git a/docs/source/contributing/index.md b/docs/source/contributing/index.md
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+++ b/docs/source/contributing/index.md
@@ -1,5 +1,69 @@
 # Contributing to Llama Stack
 
+If you are interested in contributing to Llama Stack, this guide will cover some of the key topics that might help you get started.
+
+Also, check out our [Contributing Guide](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md) for more details on how to contribute to Llama Stack.
+
+
+
+## Adding a New API Provider
+
+This guide will walk you through the process of adding a new API provider to Llama Stack.
+
+### Getting Started
+
+1. **Choose Your API Category**
+   - Determine which API category your provider belongs to (Inference, Safety, Agents, VectorIO)
+   - Review the core concepts of Llama Stack in the [concepts guide](../concepts/index.md)
+
+2. **Determine Provider Type**
+   - **Remote Provider**: Makes requests to external services
+   - **Inline Provider**: Executes implementation locally
+
+   Reference existing implementations:
+   - {repopath}`Remote Providers::llama_stack/providers/remote`
+   - {repopath}`Inline Providers::llama_stack/providers/inline`
+
+   Example PRs:
+   - [Grok Inference Implementation](https://github.com/meta-llama/llama-stack/pull/609)
+   - [Nvidia Inference Implementation](https://github.com/meta-llama/llama-stack/pull/355)
+   - [Model context protocol Tool Runtime](https://github.com/meta-llama/llama-stack/pull/665)
+
+3. **Register Your Provider**
+   - Add your provider to the appropriate {repopath}`Registry::llama_stack/providers/registry/`
+   - Specify any required pip dependencies
+
+4. **Integration**
+   - Update the run.yaml file to include your provider
+   - To make your provider a default option or create a new distribution, look at the teamplates in {repopath}`llama_stack/templates/` and run {repopath}`llama_stack/scripts/distro_codegen.py`
+   - Example PRs:
+     - [Adding Model Context Protocol Tool Runtime](https://github.com/meta-llama/llama-stack/pull/816)
+
+### Testing Guidelines
+
+#### 1. Integration Testing
+- Create integration tests that use real provider instances and configurations
+- For remote services, test actual API interactions
+- Avoid mocking at the provider level
+- Reference examples in {repopath}`tests/client-sdk`
+
+#### 2. Unit Testing (Optional)
+- Add unit tests for provider-specific functionality
+- See examples in {repopath}`llama_stack/providers/tests/inference/test_text_inference.py`
+
+#### 3. End-to-End Testing
+1. Start a Llama Stack server with your new provider
+2. Test using client requests
+3. Verify compatibility with existing client scripts in the [llama-stack-apps](https://github.com/meta-llama/llama-stack-apps/tree/main) repository
+4. Document which scripts are compatible with your provider
+
+### Submitting Your PR
+
+1. Ensure all tests pass
+2. Include a comprehensive test plan in your PR summary
+3. Document any known limitations or considerations
+4. Submit your pull request for review
+
 
 ```{toctree}
 :maxdepth: 1
diff --git a/docs/source/getting_started/index.md b/docs/source/getting_started/index.md
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--- a/docs/source/getting_started/index.md
+++ b/docs/source/getting_started/index.md
@@ -4,8 +4,6 @@ In this guide, we'll walk through how you can use the Llama Stack (server and cl
 
 A Llama Stack agent is a simple autonomous system that can perform tasks by combining a Llama model for reasoning with tools (e.g., RAG, web search, code execution, etc.) for taking actions.
 
-At minimum, an agent requires a Llama model for inference and at least one tool that it can use.
-
 In Llama Stack, we provide a server exposing multiple APIs. These APIs are backed by implementations from different providers. For this guide, we will use [Ollama](https://ollama.com/) as the inference provider.