Add llms.txt file for AI tool documentation discovery

[Claude]

Implements llmstxt.org specification to improve how AI tools parse and reference FalkorDB documentation.

Changes

• Created /llms.txt at repository root with structured documentation map
  • H1 title, blockquote product description, H2 sections, markdown links with colon-separated descriptions
  • Product description includes key constraints: protocol support (RESP/Bolt), deployment requirements, client compatibility, OpenCypher with extensions
  • Organized into logical sections: Getting Started, Core Documentation, GenAI/GraphRAG, Operations, Advanced Features
  • Optional section for secondary content (migration guides, deployment platforms, edge computing variants)
• Updated /llms.txt to include latest documentation additions:
  • MCP Server integration for AI assistants (Model Context Protocol)
  • Mem0 agentic memory framework integration
  • GraphRAG Toolkit explicitly listed
  • Snowflake Native App integration
  • Enhanced descriptions for Integrations section (REST API, Kafka Connect, Apache Jena, BOLT protocol, Spring Data)

Format

# FalkorDB Documentation

> FalkorDB is an ultra-fast, low-latency, scalable graph database designed for accurate GraphRAG...

> **Key Requirements**: FalkorDB supports both RESP and Bolt protocols. Requires Docker or cloud instance...

## Getting Started

- [Home](https://docs.falkordb.com/): FalkorDB overview and quick start with Docker
- [Getting Started](https://docs.falkordb.com/getting-started/): Complete guide to setting up FalkorDB...

## GenAI and GraphRAG

- [MCP Server](https://docs.falkordb.com/genai-tools/mcpserver/): Enable AI assistants like Claude to interact with FalkorDB...
- [Agentic Memory](https://docs.falkordb.com/agentic-memory/): Memory systems for AI agents with Graphiti, Cognee, Mem0...

## Optional

- [Migration Guides](https://docs.falkordb.com/operations/migration/): Migrating from other graph databases...

File prioritizes essential documentation in main sections, relegates changelogs and platform-specific guides to Optional section per spec. Kept synchronized with latest documentation structure.

Original prompt

---

This section details on the original issue you should resolve

<issue_title>Add llms.txt file</issue_title>
<issue_description>- [ ] Add an llms.txt file
Create a /llms.txt file at your site root that summarizes your documentation structure for AI tools. This is the single most impactful thing you can do for AI readability.

• Fix your llms.txt format
  Your llms.txt should have an H1 title, a blockquote description, H2 sections, and list items with links. Follow the llmstxt.org specification.

• Add descriptions to your links
  Each link in your llms.txt should include a colon-separated description, e.g., '- Auth: How to authenticate with API keys'. This helps AI understand what each page covers without loading it.

• Add an Optional section
  Add a '## Optional' section to your llms.txt for secondary content like changelogs and migration guides. This helps AI prioritize what to read within its context window.

• Add a clear product description
  Your llms.txt blockquote should clearly describe what your product does in 10+ words. Don't make AI guess — be explicit.

• List key constraints and requirements
  Add notes about authentication requirements, rate limits, prerequisites, and version compatibility in the opening section of your llms.txt.</issue_description>

Comments on the Issue (you are @claude[agent] in this section)

• Fixes Add llms.txt file #360

[Copilot]

Pull request overview

This pull request adds an llms.txt file to the repository root, implementing the llmstxt.org specification to improve how AI tools discover, parse, and reference FalkorDB documentation. The file provides a structured map of documentation with clear descriptions, making it easier for AI tools to understand the documentation hierarchy within their context window constraints.

Changes:

• Added /llms.txt file with comprehensive documentation structure following llmstxt.org specification
• Includes H1 title, blockquote product description with key requirements, H2 sections, and markdown links with colon-separated descriptions
• Organizes documentation into logical sections: Getting Started, Core Documentation, GenAI/GraphRAG, Operations, Advanced Features, and Optional

---

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[gkorland]

@claude[agent] please review the project and update the llm.txt with the latest commits updates

[Claude]

@claude[agent] please review the project and update the llm.txt with the latest commits updates

Updated llms.txt with the latest documentation additions from recent commits:

Added entries:

• MCP Server integration for AI assistants (genai-tools/mcpserver/)
• Mem0 agentic memory integration
• GraphRAG Toolkit explicitly listed
• Snowflake Native App integration details

Enhanced descriptions:

• Agentic Memory now includes Graphiti, Cognee, Mem0, and MCP server integrations
• Integrations section now lists specific tools: REST API, Kafka Connect, Apache Jena, BOLT protocol, Spring Data, and Snowflake Native App

Commit: a3129c3