Max – Federated Data Query Layer for AI Agents

TL;DR

TL;DR: Max is an open-source federated data connectivity layer that syncs arbitrary data sources into local SQLite storage, letting AI agents query at full speed without rate limits, latency, or per-query costs.

Source and Accuracy Notes

⚠️ This section is MANDATORY. All links must be verified from actual source, not guessed.

• Project page: max.cloud
• Source repository: github.com/max-hq/max
• License: Apache-2.0 (verified via GitHub API license.spdx_id)
• HN launch thread: news.ycombinator.com/item?id=47278802
• Source last checked: 2026-08-02 (commit main branch)

What Is Max?

Max is a federated data connectivity layer developed by max-hq/max. It connects to arbitrary data sources — APIs, databases, SaaS tools — and synchronises that data into portable local storage. Once synced, queries run entirely offline against a local SQLite database rather than against live APIs.

The core benefits, quoted directly from the README:

• Queries are instant
• There are no API rate limits
• There is no incremental cost per query
• Data sources take a familiar shape

Max is designed primarily for AI agents. It provides a CLI that agents can call directly (max schema, max ls, max search), plus an llm-bootstrap command that outputs a context document teaching any agent how to use Max.

Setup Workflow

Prerequisites

• macOS, Linux, or WSL
• curl (for the install script)
• Git (for connector installation)

Step 1: Install

curl -fsSL https://max.cloud/install.sh | sh

The installer places the max binary on your PATH. Verify:

max --version

Step 2: Query a Public Node

Max hosts public demo nodes so you can try the tool without any setup:

# Most downloaded text-generation models on HuggingFace
max -t max://demo.max.cloud/max-demo/hf-popular search HfModel \
  --filter 'pipelineTag = "text-generation" AND downloads > 10000' \
  --order-by downloads:desc \
  --fields id,downloads,likes

# Open issues across a GitHub repo
max -t max://demo.max.cloud/max-demo/gh-pi-mono search GitHubIssue \
  --filter 'state = "open"' \
  --order-by createdAt:desc \
  --fields title,author,state

# Inspect a node schema
max -t max://demo.max.cloud/max-demo/gh-pi-mono schema

Step 3: Set Up a Private Workspace

Connect your own data sources:

# Clone the open-source connectors repo
max -g install --collection [email protected]:max-hq/max-connectors.git

# Initialize a project
max init my-project && cd my-project

# Connect a source (example: Linear)
max connect @max/connector-linear --name linear-1
max sync linear-1

# Query locally
max search linear-1 LinearIssue \
  --filter 'state = "In Progress" AND labels ~= "bug"' \
  --fields title,assignee,priority

Step 4: Give an AI Agent Access to Max

max -g llm-bootstrap

This prints a context document describing Max’s commands and schema. Paste it into your agent’s instructions, or have the agent run max -g llm-bootstrap directly. The agent can then explore data (max schema, max ls), run queries (max search), and pipe results into its own tools.

Deeper Analysis

Storage Model

Max uses SQLite as its storage backend by default. Queries run locally with high throughput and low latency — no network round-trips, no API rate limit concerns. This is particularly valuable for agents that need to iterate rapidly over large datasets (searching open issues, checking model availability, cross-referencing records).

Connector Ecosystem

The max-connectors repository is the community connector hub. Currently includes connectors for:

• GitHub (issues, PRs, repos)
• Linear (issues, projects)
• HuggingFace (models, datasets)
• Google Calendar
• Notion

Community connectors can be added by forking max-connectors and following the connector schema.

CLI-First Design

Max is CLI-first. Every operation — connect, sync, search, schema inspection — goes through the max command. This makes it trivially scriptable and agent-callable. There is no web UI for querying; the interface is the terminal.

Token Efficiency

For AI agents that bill per token on LLM calls, Max reduces cost in two ways: queries run locally (no API calls to external services during reasoning), and the llm-bootstrap context document is a one-time token cost per session rather than repeated API calls to remote endpoints.

Practical Evaluation Checklist

• Does it install cleanly on macOS? Yes — single curl | sh script
• Does it work without an API key on public nodes? Yes
• Are connectors open-source? Yes — github.com/max-hq/max-connectors
• Is the storage layer local and portable? Yes — SQLite on disk
• Is it agent-friendly? Yes — max -g llm-bootstrap generates instructions for any LLM
• Does it avoid per-query API costs? Yes — after initial sync, queries are free

Security Notes

• Max syncs data from external services into local SQLite files. Those files are stored on disk in your project directory — apply standard file system access controls.
• Connector credentials (API keys for Linear, GitHub, etc.) are stored locally in the project. Do not commit .max/ or *.db files to version control.
• The llm-bootstrap context document is read-only guidance — it does not execute arbitrary operations on its own.

FAQ

Q: Does Max replace a database? A: No. Max is a connectivity and caching layer. It pulls data from external APIs into a local SQLite cache. It does not host data itself.

Q: Can multiple agents share the same Max workspace? A: Yes — the SQLite database is a standard file that any process with read access can query. Agents running concurrently should use read-only connections to avoid lock contention.

Q: What happens when the source data changes? A: You run max sync [source] to re-fetch data from the live API. There is no automatic background sync by default; orchestration of re-syncs is up to the caller.

Q: Is there a hosted / managed version? A: No. Max is self-hosted only. You run it on your own infrastructure, and data stays on your machines.

Conclusion

Max solves a concrete problem: AI agents that need to query external data (GitHub issues, model registries, calendars) currently pay per-API-call costs and hit rate limits during reasoning. Max flips this by pulling data locally once and letting the agent query infinitely at SQLite speed.

The install is one line, public nodes require zero setup, and the llm-bootstrap command makes it usable by any LLM out of the box. For developers building agents that work with structured external data, Max is worth keeping in the toolbox.