Data Platform

How to Use These Docs

Redpanda’s documentation helps you stream data, build pipelines, and deploy AI agents whether you manage infrastructure yourself or run in the cloud. This page explains how our docs are organized, clarifies the relationship between deployment models and products, and shows you how to access documentation through AI-powered tools and programmatic interfaces.

Understand the documentation structure

Redpanda’s documentation is organized around the Data Platform, the streaming foundation for everything you build. You can deploy the Data Platform in two ways: as a fully managed Cloud service or as a Self-Managed installation where you control the infrastructure. Regardless of deployment model, you have access to multiple products including Streaming (the broker and Redpanda CLI) and Connect (data pipelines).

Documentation hierarchy
Redpanda Documentation
└── Data Platform
    ├── Cloud (managed by Redpanda)
    │   ├── Serverless
    │   ├── BYOC
    │   └── Dedicated
    └── Self-Managed (managed by you)
        ├── Streaming (broker, Redpanda CLI)
        └── Connect (data pipelines)

What changed: Previously, the software that deployed a Redpanda broker was called "Redpanda Self-Managed". In the new structure, "Self-Managed" refers to the deployment model (you manage the infrastructure), while "Streaming" is the product name for the broker itself.

  • Old: "Redpanda Self-Managed" is the broker product

  • New: "Self-Managed" is deployment model that includes Streaming and Connect products

Key components:

Choose your path

Find the documentation that matches your use case:

I want to deploy Redpanda myself → Self-Managed docs

I want Redpanda managed for me → Cloud docs

I want to integrate data sources/sinks → Connect docs

  • Available in both Cloud and Self-Managed deployments

  • Hundreds of prebuilt connectors including AI and change data capture (CDC)

  • Connect documentation

AI agent access

Redpanda’s documentation is optimized for AI agents and LLM consumption. Whether you’re building AI agents, IDE plugins, or automation tools, you can access documentation through interactive page features, a Model Context Protocol (MCP) server for real-time queries, and static markdown exports for offline processing.

Discovery files

Redpanda follows the llms.txt standard for AI agent discovery:

Page options

Every documentation page includes interactive features:

View as plain text: Click View as plain text in the page options dropdown to render the current page in GitHub-Flavored Markdown format. This option is useful for reading in markdown-aware editors, accessing content offline, or sharing documentation snippets.

Copy as Markdown: Click Copy as Markdown in the page options dropdown to copy the page markdown to your clipboard with YAML frontmatter preserved (includes title, description, git dates, categories, and more). This option is useful for pasting into notes, documentation systems, or issue trackers.

Ask AI: Click Ask AI in the page options dropdown or top-nav section to open an AI chat drawer with full access to Redpanda documentation. The AI can explain configurations in simpler terms, show examples, or highlight common pitfalls.

Install the MCP server

Redpanda provides a remote Model Context Protocol (MCP) server that lets you access authoritative Redpanda documentation directly from your IDE or AI tool, such as Claude Code, Cursor, VS Code, ChatGPT, or Claude Desktop.

The MCP server is hosted at: https://docs.redpanda.com/mcp. You can add this endpoint to any AI agent that supports MCP.

  • Claude Code

  • Cursor

  • VS Code

  • ChatGPT Desktop

  • Claude Desktop

Run the following command to add the Redpanda MCP server to Claude Code:

claude mcp add --scope user --transport http redpanda https://docs.redpanda.com/mcp

This command:

  • Adds the MCP server with the name redpanda.

  • Uses the native HTTP transport to connect directly to the endpoint.

  • Configures it for your user account (stores in ~/.claude.json).

  • Works on all platforms (macOS, Linux, Windows).

To verify the installation:

claude mcp list

You should see redpanda: https://docs.redpanda.com/mcp (HTTP): ✓ Connected in the output.

For more information about Claude Code, see the Claude Code documentation.

Add the following to your .cursor/mcp.json file:

{
  "mcpServers": {
    "redpanda": {
      "type": "http",
      "url": "https://docs.redpanda.com/mcp"
    }
  }
}

For more information about MCP in Cursor, see the Cursor documentation.

Prerequisites: VS Code 1.102+ with GitHub Copilot enabled.

Create an mcp.json file in your workspace .vscode folder:

.vscode/mcp.json
{
  "servers": {
    "redpanda": {
      "type": "http",
      "url": "https://docs.redpanda.com/mcp"
    }
  }
}

To configure globally for all workspaces:

  1. Open Command Palette (Cmd+Shift+P / Ctrl+Shift+P)

  2. Run MCP: Open User Configuration

  3. Add the same JSON configuration

Using MCP in VS Code:

  1. Open the Chat view (Ctrl+Cmd+I / Ctrl+Alt+I).

  2. Select Agent mode from the dropdown.

  3. Click the Tools button to see available MCP tools.

  4. Ask questions about Redpanda and the AI automatically uses the documentation.

For more details, see the VS Code MCP documentation.

ChatGPT Desktop supports MCP servers in developer mode. To enable:

  1. Open ChatGPT Desktop.

  2. Go to Settings > Features.

  3. Enable Developer mode.

  4. Navigate to Settings > MCP Servers.

  5. Click Add Server and enter:

For more information, see the ChatGPT Desktop MCP documentation.

Connect Claude Desktop to Redpanda’s MCP server using one of two methods:

Method 1: Using Connectors

This method is available for Pro, Max, Team, or Enterprise plans and works across all platforms (macOS, Windows, Linux):

  1. Open Claude Desktop.

  2. Navigate to Settings > Connectors.

  3. Click Add custom connector.

  4. Enter the URL: https://docs.redpanda.com/mcp

  5. Follow any authentication prompts if required.

When using Connectors, Claude connects to your remote MCP server from Anthropic’s cloud infrastructure.

Method 2: Using Configuration File

This method works for all plans, including Free plan.

Edit the Claude Desktop configuration file for your platform:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

  • Windows: %APPDATA%\Claude\claude_desktop_config.json

Add the following configuration to your claude_desktop_config.json file:

{
  "mcpServers": {
    "redpanda": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://docs.redpanda.com/mcp"]
    }
  }
}

This configuration uses the mcp-remote bridge to connect to Redpanda’s remote MCP server. Claude Desktop supports only stdio and sse transports, so mcp-remote converts the HTTP endpoint to a compatible format.

Restart Claude Desktop for changes to take effect.

On Linux, Claude Desktop cannot connect to remote servers configured using claude_desktop_config.json. If this method doesn’t work, use the Connectors interface instead (available with Pro, Max, Team, or Enterprise plans).

For more details, see the Claude Desktop documentation.

Other AI tools

Any tool that supports MCP servers can connect using the following URL:

https://docs.redpanda.com/mcp
MCP support varies by tool and version. Check the specific tool’s documentation for MCP setup instructions.

What you can do

Once connected, you can ask context-aware questions about Redpanda from within your editor:

  • "How do I configure Redpanda for production?"

  • "What are the instructions for running Redpanda in a local Kind cluster?"

  • "What are the best practices for topic partitioning in Redpanda?"

  • "What are Redpanda’s security features and authentication methods?"

  • "How do I monitor Redpanda cluster performance?"

  • "What’s the difference between Redpanda Cloud and self-hosted deployment?"

Usage limits

To ensure fair use and performance for all users, the public MCP endpoint enforces the following rate limits per user:

  • 60 requests per 15 minutes

As well as this global limit, the ask_redpanda_question tool proxies to an MCP server hosted by Kapa.ai, which enforces its own limits. See the Kapa documentation for details.

These limits are suitable for:

  • Individual developer IDE usage

  • Ad-hoc documentation queries

  • Evaluation and testing

If you exceed the limit, you receive an HTTP 429 response with rate limit headers. Wait until the reset time before retrying.

Rate limit exceeded response
HTTP 429 Too Many Requests
RateLimit-Limit: 40
RateLimit-Remaining: 0
RateLimit-Reset: <timestamp>

Troubleshooting

Server not connecting

  • Verify the URL is exactly: https://docs.redpanda.com/mcp.

  • Check your internet connection.

  • Ensure your AI tool supports HTTP-based MCP servers.

  • Restart your AI tool after adding the configuration.

VS Code specific issues

  • Ensure you have VS Code 1.102 or later.

  • Verify GitHub Copilot is installed and enabled.

  • Try running MCP: Reset Cached Tools from the Command Palette.

  • Check the Output panel (View > Output > MCP) for error messages.

Configuration issues

  • For Claude Code, Cursor, and VS Code, use the HTTP transport (--transport http or "type": "http").

  • For Claude Desktop, use the mcp-remote bridge shown in the setup section. Claude Desktop does not support direct HTTP transport.

  • If you previously configured Claude Code using mcp-remote and experience connection issues, remove the old configuration and use the HTTP transport method shown above.

  • Some MCP clients may have issues with SSE streaming. If you experience connection problems, verify that your client supports HTTP-based MCP servers with Server-Sent Events (SSE).

  • Check that your client’s Accept headers include both application/json and text/event-stream.

Rate limiting

If you’re building automation or high-volume integrations and hitting rate limits frequently:

  • The public endpoint’s rate limits are intentionally restrictive for fair use.

  • Consider implementing caching on your side to reduce duplicate queries.

Other issues

Check the MCP GitHub repository for additional troubleshooting guidance or report an issue with our documentation.

Static markdown exports

For agents without MCP support or for offline processing, use our static markdown exports:

Component-specific exports:

Use cases:

  • Offline AI training and model fine-tuning

  • Batch processing and analysis

  • Full-text search implementations

  • Custom documentation tools

Fetch individual pages

Every HTML page in our documentation has a markdown equivalent that you can access programmatically.

  1. Direct access: Replace .html with .md in any URL

    Example: https://docs.redpanda.com/streaming/home.html → https://docs.redpanda.com/streaming/home.md

  2. Content negotiation: Request any URL with Accept: text/markdown header

Markdown features:

  • YAML frontmatter with page metadata (title, description, categories, topic type, personas)

  • Git dates (accurate created/modified dates from commit history)

  • GitHub-Flavored Markdown format

Use cases:

  • API integrations

  • Automated documentation pipelines

  • Custom documentation workflows

  • Integration with internal knowledge bases

Contributing:

  • Want to contribute to the documentation? See the Contributing guide

  • Found a typo or have a suggestion? Open an issue or pull request on GitHub