Statey
Summary
Every agent session starts from scratch — the ticket it triaged, the customer it updated, the record it wrote all vanish the moment the conversation ends. Statey is a headless structured database built specifically so that work has somewhere to live between sessions.
Statey exposes collections, schemas, and validated records through MCP, so Claude, ChatGPT, Cursor, or any MCP-speaking client can read and write the same data without you wiring up a backend. There is no UI on purpose — the agent renders the view on demand, and the database keeps the record. Every write is attributed to a human or agent and event-logged in the same transaction, so you can trace exactly what changed and who caused it. Reactive triggers — where a data mutation dispatches an agent automatically — are listed as coming soon, not yet shipped. Teams that need that loop closed today are working around it manually.
Bottom line: Reach for Statey when your agents need a shared, persistent record store and you do not want to maintain a backend yourself — but plan a different approach when your workflow depends on trigger-driven automation, because that feature is not live yet.
Pricing Plans
Usage-BasedLast verified 1 week ago- Price
- $20/workspace/mo plus usage-based storage
- Free Tier
- 1 workspace, 1 GB storage included, Unlimited reads & writes, 3 agent keys, 30-day event history, Community support
Free
For solo builders and their agents
- 1 workspace
- 1 GB storage included
- Unlimited reads & writes
- 3 agent keys
- 30-day event history
- Community support
Pro
For builders going deeper. Per workspace per month plus usage-based storage
- 10 GB included storage, then usage-based
- 20 agent keys
- 1-year event history
- Triggers & reactive loop
- Hard spend caps
- Email support
Team
For teams of humans and agents. Per workspace per month plus usage-based storage
- 100 GB pooled storage
- Unlimited event history
- Roles & permissions (RBAC)
- SSO / SCIM
- Backups & point-in-time restore
- Priority support
Enterprise
For scale and compliance. Custom tailored to your footprint
- VPC or self-hosted storage
- SOC 2 & audit exports
- Custom rate limits
- 99.9% uptime SLA
- Dedicated support
View full pricing on statey.ai →
Pricing may have changed since last verified. Check the official site for current plans.
Community Performance Report Card
No community ratings yet. Be the first to rate this tool!
Community Benchmarks Community
Sign in to submit a benchmarkNo community benchmarks yet. Be the first to share a real-world data point.
Pros
Sign in to edit- Single MCP endpoint for every client, which means Claude, ChatGPT, Cursor, and Codex all read and write the same records without you managing separate integrations or syncing state between them.
- Schema evolves through plain-language requests with no migration step required, so the data model can change week to week as requirements shift without a developer touching schema files.
- Every write is attributed to a specific human or agent and logged in the same transaction, which means you can audit exactly what an agent changed and roll back a bad write without reconstructing events from chat logs.
- No fixed UI means the agent renders whatever view the task needs — a kanban board, a filtered table, a single answer — so you are not constrained by the screens a vendor decided to build.
- Optimistic concurrency is built in from the start, so multiple agents and humans writing the same collection at the same time do not silently overwrite each other's changes.
Cons
Sign in to edit- Reactive triggers — where a record mutation automatically dispatches an agent — are not yet live. Any workflow that depends on event-driven automation requires manual polling or an external scheduler, which means teams building agent pipelines that react to data changes cannot use Statey as the event backbone today.
- There is no self-hosted deployment option. Teams operating under data-residency requirements or internal security policies that prohibit third-party SaaS holding structured business data hit this wall immediately and have to evaluate a different backend entirely.
- Because there is no built-in UI, every read and write requires an MCP-capable client. Teams whose workflows include non-technical stakeholders who need to view or edit records directly — without routing through Claude or ChatGPT — have to build or bolt on a front end themselves, which erases much of the setup simplicity.
- The trigger and automation layer being absent means teams that need a full agent loop — ingest, store, react, dispatch — will eventually outgrow Statey as the sole infrastructure layer and add a separate orchestration system, at which point they are maintaining two backends instead of one.
Community Reviews
Sign in to write a reviewNo reviews yet. Be the first to share your experience.
About
- Platforms
- MCP clients (Claude, ChatGPT, Cursor, Claude Code, Codex)
- API Available
- Yes
- Self-Hosted
- No
- Last Updated
- 2026-06-27T20:35:57.331Z
Best For
Who it's for
- Agent-driven workflows needing persistent structured data
- Teams using multiple MCP clients like Claude and ChatGPT
- Building custom trackers and pipelines without fixed UIs
What it does well
- Bug triage and task tracking
- Customer records and CRM
- Structured documents and research vaults
- Inventory and operations tracking
- Marketing archives and applicant pipelines
Integrations
Discussion Community
Sign in to commentNo discussion yet. Sign in to start the conversation.
Compare Statey
Spotted incorrect or missing data? Join our community of contributors.
Sign Up to ContributeCommunity Notes & Tips Community
Sign in to contributeBe the first to contribute. General notes, observations, gotchas, and tips from people who use this tool day-to-day.
Recommended skills for this tool
Auto-curated by the AIDiveForge recommendation matrix. These skills are predicted to enhance this tool based on category, capability, and domain signals.
-
Meeting Summary Template transform 32%
Turn a raw transcript into a decision-focused recap: outcomes, owners, deadlines, open threads.
Why: category partial · caps 0/0 · domain ops
-
Standup Note Synthesizer transform 32%
Merge individual standup bullets from multiple people into a single team digest with blockers surfaced to the top.
Why: category partial · caps 0/0 · domain ops
-
Runbook Skeleton post 32%
Produce a first-draft runbook from a postmortem — detection, diagnosis, mitigation, rollback — so the next incident has a template to follow.
Why: category partial · caps 0/0 · domain ops
-
OKR Draft Critiquer post 32%
Score draft OKRs against SMART criteria and the outcome-not-output rule, with suggested rewrites for each failing key result.
Why: category partial · caps 0/0 · domain ops
Frequently Asked Questions
- Is Statey free?
- Statey has a permanent free tier alongside paid upgrades (paid plans from $20/workspace/mo plus usage-based storage). You can keep using a baseline version indefinitely without paying.
- Is Statey open source?
- No — Statey is a closed-source tool. Source code is not publicly available.
- Does Statey have an API?
- Yes. Statey exposes a developer API. See the official documentation at https://statey.ai for details.
- What platforms does Statey support?
- Statey is available on: MCP clients (Claude, ChatGPT, Cursor, Claude Code, Codex).
Hours Saved & ROI Stories Community
Sign in to contributeBe the first to contribute. Concrete time/cost savings, with context. e.g. "Cut my code review backlog from 4h to 45m per week."
Curated lists that include this category
Chat memory evaporates. Agents can create a ticket in one session and have no idea it exists in the next. Statey solves this by acting as a persistent, schema-flexible structured database that any MCP client can read and write. The core workflow is conversational: an agent describes what it wants to track, Statey builds the collection and schema, and from that point every create, update, or query travels through MCP tool calls. Collections, fields, and statuses can be reshaped at any time — the vendor states no migrations or schema files are required.
The defining design choice is that Statey ships no interface at all. Where other MCP-connected tools are constrained by the screens their app exposes, Statey treats the LLM as the rendering layer. The agent draws a board, a table, or a single answer from the tool result on demand, while the underlying record stays versioned and attributed. Every mutation carries full provenance — which human or agent wrote it, and in which transaction — so multi-actor workspaces where agents and people write concurrently do not produce silent conflicts.
Statey fits best when you are connecting multiple MCP clients — Claude Desktop, Claude Code, ChatGPT, Cursor, Codex — to a single source of truth, and you want agents to operate on that data without you building or hosting a backend. The ceiling appears at automation: reactive triggers that fire an agent the moment a record changes are described on the vendor page as coming soon. Teams whose workflows depend on event-driven agent dispatch cannot rely on that loop being closed and are either polling manually or holding off on those use cases entirely. Self-hosting is not available, so teams with data-residency requirements face an immediate blocker.
