> ## Documentation Index
> Fetch the complete documentation index at: https://orchata.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Resources & Prompts

> MCP resources and prompts for guided workflows

In addition to tools, the Orchata MCP server provides **resources** for documentation access and **prompts** for guided RAG workflows.

## Resources

MCP resources provide read-only access to documentation and dynamic data. AI assistants can read these to understand how to use Orchata.

### Documentation Resources

| URI                            | Description                             |
| ------------------------------ | --------------------------------------- |
| `orchata://docs/introduction`  | Platform introduction and core concepts |
| `orchata://docs/quickstart`    | Getting started guide for AI agents     |
| `orchata://docs/api-reference` | API and MCP tool reference              |

**Example usage:**

```
Read the resource at orchata://docs/quickstart
```

This returns a Markdown document explaining how to use Orchata step-by-step.

### Dynamic Space Resources

Access detailed information about any space:

| URI Pattern                  | Description                |
| ---------------------------- | -------------------------- |
| `orchata://spaces/{spaceId}` | Detailed space information |

**Example:**

```
Read the resource at orchata://spaces/spc_abc123
```

Returns JSON with the space's full details including document count, description, and metadata.

<Tip>
  When an MCP client requests the list of resources, all available spaces are automatically included in the response.
</Tip>

***

## Prompts

MCP prompts provide guided workflows for common RAG tasks. They help AI assistants understand best practices and follow optimal patterns.

### rag-workflow

Step-by-step guide for implementing a RAG workflow with Orchata.

**Parameters:**

<ParamField body="useCase" type="string">
  Type of RAG application: `chatbot`, `search`, `qa`, or `agent`
</ParamField>

**Example:**

```
Use the rag-workflow prompt with useCase="agent"
```

**Returns guidance on:**

1. Organizing knowledge into spaces
2. Choosing query strategies
3. Formatting context for LLMs
4. Generating grounded responses

**Sample output for `agent` use case:**

```markdown theme={null}
# Orchata RAG Workflow Guide

## Basic RAG Flow

1. **Organize Knowledge**: Create focused spaces for different topics
2. **Query Strategy**: Use smart_query when unsure, query_spaces when you know the space
3. **Context Formatting**: Include retrieved content in your LLM prompt
4. **Response Generation**: Generate responses grounded in retrieved content

## AI Agent Tips
- Always start with smart_query to find relevant spaces
- Search multiple spaces for comprehensive answers
```

***

### space-discovery

Help discover which spaces contain the information you need.

**Parameters:**

<ParamField body="topic" type="string">
  The topic or question you're trying to find information about
</ParamField>

**Example:**

```
Use the space-discovery prompt with topic="authentication best practices"
```

**Returns guidance on:**

1. How to use `smart_query` for the topic
2. How to search the recommended spaces
3. Strategies for refining results

**Sample output:**

```markdown theme={null}
# Space Discovery Guide

Looking for: **authentication best practices**

1. Use smart_query("authentication best practices")
2. Then query_spaces with returned IDs
```

***

## Using Resources and Prompts

### When to Use Resources

* **Learning**: AI needs to understand how Orchata works
* **Reference**: AI needs to look up API details or concepts
* **Context**: AI needs information about a specific space

### When to Use Prompts

* **Guidance**: AI needs help with the right approach
* **Best Practices**: AI needs to follow recommended patterns
* **Discovery**: AI needs to find relevant information

### Example Workflow

Here's how an AI assistant might use resources and prompts together:

<Steps>
  <Step title="Read Documentation">
    AI reads `orchata://docs/introduction` to understand core concepts.
  </Step>

  <Step title="Use Discovery Prompt">
    AI uses `space-discovery` prompt with the user's topic.
  </Step>

  <Step title="Execute Smart Query">
    AI calls `smart_query` tool to find relevant spaces.
  </Step>

  <Step title="Search Spaces">
    AI calls `query_spaces` with discovered space IDs.
  </Step>

  <Step title="Generate Response">
    AI synthesizes an answer from the retrieved content.
  </Step>
</Steps>

***

## Resource and Prompt Reference

### All Resources

| URI                            | Type    | Description           |
| ------------------------------ | ------- | --------------------- |
| `orchata://docs/introduction`  | Static  | Platform overview     |
| `orchata://docs/quickstart`    | Static  | Getting started guide |
| `orchata://docs/api-reference` | Static  | API reference         |
| `orchata://spaces/{id}`        | Dynamic | Space details         |

### All Prompts

| Name              | Arguments  | Description              |
| ----------------- | ---------- | ------------------------ |
| `rag-workflow`    | `useCase?` | RAG implementation guide |
| `space-discovery` | `topic?`   | Space discovery guide    |

***

## Next Steps

<CardGroup cols={2}>
  <Card title="MCP Tools" icon="wrench" href="/mcp/tools">
    Explore all 12 MCP tools.
  </Card>

  <Card title="Setup Guides" icon="gear" href="/mcp/setup/cursor">
    Configure your AI tool for Orchata.
  </Card>
</CardGroup>