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

# Tools, Resources & Prompts

> The three types of capabilities your AI can access through MCP

## The Three Types of MCP Capabilities

When you connect to an MCP server (like GitHub or Slack), your AI gets access to three types of capabilities:

## Tools 🔧

**Tools are actions your AI can perform** - things that change or do something.

### Examples:

* **GitHub**: Create an issue, merge a pull request, comment on code
* **Slack**: Send a message, create a channel, react to posts
* **Dropbox**: Upload a document, share a file, organize files in folders
* **Email**: Send an email, mark as read, move to folder

### How your AI uses tools:

```
You: "Create a GitHub issue for the login bug"
AI: [Uses GitHub create_issue tool] "Issue #123 created: Fix login bug"

You: "Send a Slack message to the team"  
AI: [Uses Slack send_message tool] "Message sent to #general"
```

## Resources 📄

**Resources are information your AI can read** - things that provide data.

### Examples:

* **GitHub**: Repository contents, issue descriptions, commit history
* **Slack**: Message history, channel member lists, thread contents
* **Dropbox**: File contents, folder structures, file metadata
* **Databases**: Query results, table schemas, stored data

### How your AI uses resources:

```
You: "What's in our latest pull request?"
AI: [Reads GitHub PR resource] "The PR adds user authentication with OAuth..."

You: "Summarize yesterday's Slack messages"
AI: [Reads Slack message history resource] "Main topics discussed: deployment, bug fixes..."
```

## Prompts 💭

**Prompts are pre-written instructions** that help your AI use tools and resources effectively.

### Examples:

* **Code Review Prompt**: "Review this pull request for security issues, performance, and code style"
* **Bug Report Prompt**: "Create a detailed bug report with steps to reproduce, expected vs actual behavior"
* **Meeting Summary Prompt**: "Summarize key decisions, action items, and next steps from this conversation"

### How your AI uses prompts:

```
You: "Review this pull request"
AI: [Uses code review prompt] Systematically checks security, performance, style, and provides structured feedback

You: "Summarize today's standup"  
AI: [Uses meeting summary prompt] Creates organized summary with decisions, action items, blockers
```

## How They Work Together

A typical AI workflow combines all three:

<Steps>
  <Step title="Read Resources">
    AI reads current state (GitHub issues, Slack messages, file contents)
  </Step>

  <Step title="Use Prompts">
    AI applies pre-written instructions for how to analyze or process the information
  </Step>

  <Step title="Execute Tools">
    AI takes actions based on what it learned (create issues, send messages, update files)
  </Step>
</Steps>

### Example Workflow:

```
You: "Prepare for our team standup"

1. AI reads resources: Recent GitHub commits, Slack messages, project files
2. AI uses prompt: "Standup preparation checklist"
3. AI uses tools: Creates summary document, posts reminder in Slack
```

## Understanding MCP Server Capabilities

Each MCP server provides different combinations:

### GitHub Server

* **Tools**: Create issues, comment, merge PRs, create branches
* **Resources**: Repository files, issue lists, commit history, PR details
* **Prompts**: Code review templates, issue creation guidelines

### Slack Server

* **Tools**: Send messages, create channels, react to posts, set status
* **Resources**: Message history, channel lists, user profiles, thread contents
* **Prompts**: Message formatting, team communication guidelines

### Dropbox Server

* **Tools**: Upload documents, search files, organize folders
* **Resources**: File contents, folder structures, sharing permissions
* **Prompts**: Document creation templates, organization standards

## Why This Matters

Understanding these three types helps you:

* **Ask better questions**: "Read the latest GitHub issues" (resource) vs "Create a new issue" (tool)
* **Set expectations**: Know what your AI can read vs what it can change
* **Troubleshoot**: If something isn't working, understand whether it's a tool, resource, or prompt issue
* **Explore capabilities**: Ask "What tools are available?" to discover what actions your AI can take

## Discovering Available Capabilities

Try these prompts to explore what's available:

```
"What tools can you use?"
"What information can you access?"  
"What prompts are available for GitHub?"
"Show me all the Slack capabilities"
```

Your AI will list the tools, resources, and prompts available from your connected MCP servers, helping you understand what's possible.