docs · v1.0
Docs.
One push. Two surfaces. A live grid for humans to review — and a queryable API, embeddable view, and LLM context file for agents to reuse.No database. No frontend. No schema setup.
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GRThe Grid4 articles
Quickstart
cat data.json | instadash push — your first live grid in under a minute.
The One-Line Push
Pipe from Python, Node, Bash, or any tool that prints to stdout.
Large File Streaming
Push 2 GB+ files directly to R2 without hitting the Worker size limit.
Configuration Reference
--name, --title, --tags, --public, --private — the full push-time flag surface.
PDPrivacy & Data4 articles
Visibility
Grids are private by default. Go public with a flag, and control embed access per plan.
Data Lineage
Source tracking on every version — cli, api, mcp. SHA-256 for integrity.
Atomic Versioning
Slide back in time to see data evolution. Every sync is a snapshot.
R2 Storage & Pricing
Immutable JSONL on Cloudflare R2. $0 egress. Plan-based retention.
AGAgent Integration4 articles
MCP Integration
Connect Claude, Cursor, Windsurf and any MCP client — push, read, edit, version, export, search grids from any AI agent.
System Prompting
Every grid ships llms.txt and llms.md — paste them straight into your system prompt.
API Authentication
Bearer API keys, scoping, and rotation. Rate limits by plan.
Webhooks
Get notified on grid.pushed. HMAC-signed outbound events, builder+ only.
MDMesh & Discovery4 articles
The Mesh Protocol
How agents search public grids via /api/mesh/search.
The Grid as Agent Memory
Push data in one session, query it back in another. Best practices for persistent agent memory.
Mesh-Augmented Generation
RAG retrieves from documents. The mesh retrieves from live, structured grids with lineage.
Cross-Project Workflows
Trigger an agent based on updates in someone else's public grid.
need help?
Talk to a human or to the agent.
Discord for community. Email for paying customers. MCP support for your AI itself.