diff --git a/.env.example b/.env.example
index c5bce0bb..d98a88f3 100644
--- a/.env.example
+++ b/.env.example
@@ -64,6 +64,12 @@ BEDROCK_API_KEY_1=""
 # --- Chutes ---
 CHUTES_API_KEY_1="YOUR_CHUTES_API_KEY"
 
+# --- Custom OpenAI-Compatible Providers (vLLM, Ollama, local LLM) ---
+# To add a custom provider, define its API base URL and at least one API key.
+# Replace 'CUSTOM' with your desired provider name.
+# CUSTOM_API_BASE="http://127.0.0.1:8001/v1"
+# CUSTOM_API_KEY_1="dummy"
+
 
 # ------------------------------------------------------------------------------
 # | [OAUTH] Provider OAuth 2.0 Credentials                                     |
diff --git a/DOCUMENTATION.md b/DOCUMENTATION.md
index ef1a2211..6e4835ff 100644
--- a/DOCUMENTATION.md
+++ b/DOCUMENTATION.md
@@ -1363,6 +1363,31 @@ TIMEOUT_POOL=120
 ---
 
 
+---
+
+### 2.19. Custom OpenAI-Compatible Upstreams
+
+The `rotator_library` includes a dynamic provider registration system that allows it to support any OpenAI-compatible API backend without requiring a specific plugin.
+
+#### Dynamic Registration Logic
+
+During initialization, the library scans environment variables for any key ending in `_API_BASE` (excluding built-in providers). For each match, it:
+1.  Registers a new provider name (derived from the prefix).
+2.  Creates a dynamic instance of `DynamicOpenAICompatibleProvider`.
+3.  Maps all requests for this provider to LiteLLM's standard `openai` implementation.
+
+#### Implementation Details
+
+- **`src/rotator_library/providers/__init__.py`**: Contains the logic that iterates over `os.environ` and populates `PROVIDER_PLUGINS` with dynamic classes.
+- **`src/rotator_library/client.py`**: In `_convert_model_params_for_litellm`, it detects these custom providers and re-writes the `model` parameter to `openai/{model_name}` while injecting the custom `api_base` and setting `custom_llm_provider="openai"`.
+- **Model Discovery**: Custom providers delegate model listing to `OpenAICompatibleProvider.get_models()`, which performs an authenticated `GET` request to the upstream's `/v1/models` endpoint.
+
+#### Usage Requirements
+
+For a custom provider to be active, it must have:
+- `{PROVIDER}_API_BASE`: The full URL to the OpenAI-compatible v1 endpoint.
+- `{PROVIDER}_API_KEY`: At least one API key configured (can be a dummy value if the upstream doesn't require authentication).
+
 ---
 
 ## 3. Provider Specific Implementations
diff --git a/README.md b/README.md
index c6206392..cbfb36f4 100644
--- a/README.md
+++ b/README.md
@@ -187,6 +187,21 @@ python -m rotator_library.credential_tool
 | **API Keys** | Gemini, OpenAI, Anthropic, OpenRouter, Groq, Mistral, NVIDIA, Cohere, Chutes | Enter key in TUI or add to `.env` |
 | **OAuth** | Gemini CLI, Antigravity, Qwen Code, iFlow | Interactive browser login via credential tool |
 
+### 🔌 Custom OpenAI-Compatible Providers (vLLM, Ollama, local LLM)
+
+The proxy supports dynamic registration of any OpenAI-compatible upstream. This allows you to integrate local instances of vLLM, Ollama, or other custom backends without modifying the code.
+
+#### Configuration
+Add the following to your `.env` file (replacing `CUSTOM` with your desired provider name):
+
+1.  **Base URL:** `CUSTOM_API_BASE="http://127.0.0.1:8001/v1"`
+2.  **API Key:** `CUSTOM_API_KEY="any-value"` (A non-empty value is required to mark the provider as active)
+
+#### Usage
+Access your custom models using the format: `custom/model-id`.
+*   **Example:** If using vLLM, set `VLLM_API_BASE` and call the proxy with model `vllm/llama-3-8b`.
+*   **Model Discovery:** The proxy's `/v1/models` endpoint will automatically attempt to fetch and list available models from your custom upstream's `/models` endpoint.
+
 ### The `.env` File
 
 Credentials are stored in a `.env` file. You can edit it directly or use the TUI:
diff --git a/src/proxy_app/settings_tool.py b/src/proxy_app/settings_tool.py
index 1194432b..194935d6 100644
--- a/src/proxy_app/settings_tool.py
+++ b/src/proxy_app/settings_tool.py
@@ -798,7 +798,16 @@ def manage_custom_providers(self):
                 )
             )
 
-            self.console.print()
+            self.console.print(
+                Panel(
+                    "Register any OpenAI-compatible upstream (vLLM, Ollama, etc.) by defining a base URL.\n"
+                    "Usage: Set [bold]PROVIDER_API_BASE[/bold] here and [bold]PROVIDER_API_KEY[/bold] in credentials.\n"
+                    "Models will be available as [bold]provider/model-id[/bold].",
+                    title="[dim]How it works[/dim]",
+                    border_style="dim",
+                )
+            )
+
             self.console.print("[bold]📋 Configured Custom Providers[/bold]")
             self.console.print("━" * 70)