Hekkova provides a decentralized permanent memory layer for AI agents to mint moments to the blockchain via MCP.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install hekkova-openclaw-skill
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install hekkova-openclaw-skill using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
Hekkova is a specialized memory layer designed for AI agents, allowing them to record information, media, and context permanently. By leveraging the Polygon blockchain for ownership, IPFS for hot storage, and Filecoin for long-term archival, this Openclaw Skills integration ensures that an agent's history is immutable and independent of any single platform. The skill uses the Model Context Protocol (MCP) to bridge AI interactions with web3 technologies, providing a secure and encrypted way to store agent experiences.
Content stored through Hekkova is encrypted with Lit Protocol based on selected privacy phases, ensuring that sensitive agent data remains private while being stored on decentralized infrastructure. This architecture provides a robust alternative to traditional database storage, offering true data ownership and permanence for any AI-driven workflow.
To use this Hekkova integration with Openclaw Skills, follow these steps:
hk_live_.export HEKKOVA_API_KEY='your_api_key_here'
npx mcp-remote https://mcp.hekkova.com/mcp --header "Authorization: Bearer $HEKKOVA_API_KEY"
Hekkova organizes data across three distinct layers to balance accessibility and permanence:
| Layer | Technology | Data Stored |
|---|---|---|
| Ownership | Polygon Blockchain | Token ID, Timestamp, and IPFS Content CID |
| Hot Storage | IPFS (Pinata) | Encrypted HTML viewer and raw media files |
| Cold Archival | Filecoin (Lighthouse) | Long-term cryptographic storage deals |
| Indexing | Supabase | Metadata for fast searching, filtering, and pagination |
Provenance metadata can be attached to any moment, including fields for platform, author, original URL, and engagement metrics like like_count and view_count.
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