How to use RevoGrid MCP

RevoGrid MCP gives AI coding tools structured access to the unified RevoGrid knowledge catalog:

https://mcp.rv-grid.com

No MCP access token or authorization header is required. The same endpoint searches Core, Pro, and Enterprise knowledge. Results retain requiresPro metadata so agents can explain package and license requirements accurately.

Why this matters

RevoGrid has a wide API and plugin surface, with advanced features such as pivot, event manager, history, specialized renderers, and custom editors. MCP helps an AI tool retrieve the right implementation guidance before it writes code.

What you can use it for

Use RevoGrid MCP when you want an AI tool to:

• find the best Core or Pro example for a specific framework
• determine whether a feature requires a Pro package before suggesting code
• build around typed plugin APIs instead of guessing event names or option shapes
• gather migration notes before upgrading a RevoGrid implementation
• work from real examples for pivot, export, filters, history, validation, or custom renderers

Agent-readable documentation files

For public, text-only documentation sources—including the llms.txt index, full corpus, split skill references, and downloadable skill—see AI Agent Documentation Sources.

Use MCP when your tool supports structured retrieval and typed context. Use the public agent-readable files when it needs documentation it can fetch directly.

Recommended setup

1. Add https://mcp.rv-grid.com to your AI coding tool.
2. Ask the agent to search RevoGrid MCP before writing code.
3. Ask it to validate the final implementation against RevoGrid types and examples.
4. If your project must remain Core-only, say so explicitly in the prompt.

Install in AI coding tools

Claude Code

claude mcp add --transport http revogrid https://mcp.rv-grid.com

Codex

codex mcp add revogrid --url https://mcp.rv-grid.com

Cursor

{
  "mcpServers": {
    "RevoGrid": {
      "url": "https://mcp.rv-grid.com",
      "type": "http"
    }
  }
}

VS Code

Install the RevoGrid DataGrid MCP extension, or configure the server directly:

{
  "servers": {
    "RevoGrid MCP": {
      "url": "https://mcp.rv-grid.com",
      "type": "http"
    }
  },
  "inputs": []
}

How to prompt effectively

The best prompts tell the agent:

1. your framework
2. whether the solution may use Pro features
3. which RevoGrid behavior matters most

Good prompt examples

• Build a Vue RevoGrid Pro pivot table. Search MCP first, use the best matching example, and explain the required plugin configuration.
• Create a React grid with RevoGrid Pro history and validation. Use MCP docs and types before writing code.
• Find the best RevoGrid example for advanced filter headers in Angular and adapt it to server-side filtering.
• Check if this feature is available in Core or Pro, then recommend the best matching implementation path.
• Find a Core-only fallback for this Pro feature.

Best practices

Ask for retrieval first

Prompt the agent to inspect RevoGrid MCP before generating code. This reduces invented APIs and helps it start from real examples.

Use types as the source of truth

Ask the agent to verify plugin names, event payloads, config fields, and feature usage against RevoGrid types.

Be explicit about licensing

MCP knowledge is token-free, but using a Pro or Enterprise package still requires the appropriate product access. Ask for a Core-only fallback when needed.

Prefer examples over prose

Ask the agent to use the best matching demo or guide as the starting point, then adapt it to your app.

Example workflow

1. Add https://mcp.rv-grid.com to your MCP client.
2. Open your RevoGrid project.
3. Ask the agent to find the best matching examples and docs.
4. Ask it to adapt the result to your framework and data model.
5. Ask it to verify the result against RevoGrid types before finalizing.