the table powered by ai agents

Data workflows,
on autopilot.

Tell your AI agent what you need. It creates the table, adds smart columns, and processes every row. You watch from the browser, or let it run. Works with Claude Code, Cursor, and any MCP agent.

Smart columns AI columns HTTP columns Formulas 50K+ rows Real-time MCP native

get started free → see how it works

What is an active table?

An active table is a spreadsheet-database hybrid where columns execute work — calling APIs, running AI prompts, computing formulas, and pushing to integrations — automatically for every row.

Traditional tables hold data. Active tables do things. When you add a row, smart columns process it through a dependency graph: an AI column can read an HTTP column's output, a formula column can combine both, and an integration column can push the result to your CRM. Hypertab makes this operable by AI agents through the Model Context Protocol (MCP) and by humans through a browser.

MCP tools: 47
column kinds: 8
rows per table: 100K+
edge latency: <50ms
browser memory at scale: ~6MB
encryption at rest: AES-256

Works with every AI coding agent

Connect via MCP. Your agent gets full control of the table.

{ One table, unlimited use cases }

Same table, different columns. Hypertab has zero domain knowledge. The intelligence comes from your agent and the columns you configure.

. go_to_market

GTM

Score leads, enrich accounts, send outbound. All in one table. Your agent sets it up, smart columns do the rest.

. data_enrichment

Enrichment

HTTP columns call any API per row. Company data, emails, technographics. Pulled, extracted, stored automatically.

. crm_hygiene

CRM

AI columns dedupe, clean, and standardize every row. Built-in deduplication catches duplicates on insert automatically.

. workflow_automation

Automation

50K rows through a workflow tool means 50K separate runs. Through Hypertab, one batch. Smart columns process in parallel.

. ai_operations

AI Ops

Run AI prompts across thousands of rows. If something fails, it retries. If an API throttles, it backs off. Progress is never lost.

. custom_pipelines

Pipelines

Chain AI, HTTP, and formula columns into multi-step pipelines. Columns declare dependencies, rows flow through in order.

How Hypertab compares

Quick comparison. See full breakdowns in our comparison pages.

Feature	Hypertab	Clay	Airtable	n8n
Columns execute work	✓ AI / HTTP / formula / integration	✓ enrich actions only	✗ static data	✗ separate workflow per run
MCP-native	✓ 47 tools	✗	✗	✗
Cost model	Flat infra	Per-credit	Per-seat	Per-execution
Scale to 100K rows	✓ ~6MB memory	Limited	Limited	50K runs needed

Reliable at any scale

Your data is safe. Your workflows don't stop.

Global edge network

Sub-50ms latency worldwide via Cloudflare Workers.

Per-tenant isolation

Each user gets their own database. Your data is yours.

Adaptive rate limiting

Auto-adjusts when APIs throttle. No manual tuning.

Circuit breaker

Pauses on error spikes. Resumes when things stabilize.

Encrypted at rest

All secrets and data encrypted with AES-256-GCM.

Real-time sync

Live updates across browser, agent, and webhooks.

When Hypertab is not the right fit

We built Hypertab for batch-style data work where columns execute logic per row. It is not the best choice for:

Real-time transactional apps. If you need ACID transactions across rows or sub-millisecond writes, use Postgres or Supabase directly.
Long-running multi-step workflows with branching. Tools like Temporal or Inngest are purpose-built for orchestrated state machines. Hypertab is row-waterfall, not step function.
Heavy interactive collaboration. Notion, Coda and Airtable have richer document/comment UX. Hypertab is operations-first.
Embedded analytics. For BI dashboards on top of warehouse data, use Metabase, Hex or Mode.

Hypertab shines when you have thousands of rows that each need to run the same set of AI/HTTP/formula steps — and you want an AI agent or a human (or both) to operate the pipeline.

Frequently asked questions

What is an active table?: An active table is a spreadsheet-database hybrid where columns do more than hold data — they call APIs, run AI prompts, compute formulas, and push to integrations automatically for every row. Hypertab is built for AI agents to operate via MCP and humans to supervise via the browser.
How is Hypertab different from Airtable?: Airtable holds data; Hypertab does work. Smart columns process every row through AI prompts, HTTP calls, formulas, and integrations. Hypertab is also MCP-native — your AI agent can build entire pipelines without writing code.
How is Hypertab different from Clay?: Clay charges credits per action; Hypertab uses flat-cost infrastructure. Hypertab is also MCP-native (Clay is not), supports general-purpose use cases beyond outbound (CRM hygiene, AI ops, custom pipelines), and lets your AI agent operate the table directly.
How does MCP work with Hypertab?: Connect any MCP-compatible AI agent (Claude Code, Cursor, Windsurf, etc.) using a single config. Your agent gets 47 MCP tools to create tables, insert rows, configure smart columns, and monitor pipelines — all without leaving the agent.
How many rows can Hypertab handle?: Tables scale to 100,000+ rows with virtualized rendering using ~6MB of browser memory. The smart column engine processes large batches efficiently with adaptive rate limiting and per-row dependency graphs.
Is there a free tier?: Yes. Free plan, no credit card required. Sign up, copy the MCP config, and your AI agent has the full table at its disposal in 30 seconds.

.get_started_free

Free to start. No credit card. Sign up, copy the MCP config, and your agent is ready to go.

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Data workflows, on autopilot.