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 |
Read the resource at orchata://docs/quickstart
Dynamic Space Resources
Access detailed information about any space:
| URI Pattern | Description |
|---|
orchata://spaces/{spaceId} | Detailed space information |
Read the resource at orchata://spaces/spc_abc123
When an MCP client requests the list of resources, all available spaces are automatically included in the response.
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:
Type of RAG application: chatbot, search, qa, or agent
Use the rag-workflow prompt with useCase="agent"
- Organizing knowledge into spaces
- Choosing query strategies
- Formatting context for LLMs
- Generating grounded responses
Sample output for agent use case:
# 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:
The topic or question you’re trying to find information about
Use the space-discovery prompt with topic="authentication best practices"
- How to use
smart_query for the topic
- How to search the recommended spaces
- Strategies for refining results
Sample output:
# 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:
Read Documentation
AI reads orchata://docs/introduction to understand core concepts.
Use Discovery Prompt
AI uses space-discovery prompt with the user’s topic.
Execute Smart Query
AI calls smart_query tool to find relevant spaces.
Search Spaces
AI calls query_spaces with discovered space IDs.
Generate Response
AI synthesizes an answer from the retrieved content.
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
