HutchDB
com.hutchdb由 hutchdb.com 發布官方發布者v1.0.0更新於 Oct 24, 2026
Store, query, and update structured data from any AI agent
概覽
HutchDB 是給 AI 代理使用的可選結構記錄庫,讓助理跨工作階段儲存、查詢、更新並匯出共享的 JSON 記錄集合。
- 可以做什麼
- 建立與檢視集合,包含每個集合的統計資訊
- 儲存、查詢、搜尋、更新、刪除記錄並變更記錄狀態,支援篩選運算子、欄位投影以及 count/min/max/distinct/sum/avg 聚合
- 轉換記錄,並以 CSV 或 JSON 匯出、匯入集合
- 描述、推斷與更新可選結構,並在集合上定義檢視
- 適用情境
- 適合代理產生的結構化資料需要超越單次對話保存的情境:持續累積的調查、追蹤清單、帶狀態交接的多代理流程、長期專案狀態或可重複執行的流程。當需要篩選、聚合或多個代理同時更新時,可取代 markdown 筆記或試算表。
- 執行需求
- 需要遠端 MCP 端點(託管應用程式),或以 Docker 或 Node.js 搭配 npm 自行架設的執行個體,並具備 Postgres 資料庫(HUTCH_DATABASE_URL)。託管服務使用 OAuth 驗證;自行架設的 Core 執行個體使用透過 HUTCH_API_KEY 設定的靜態 bearer 權杖。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 HutchDB,將其新增到工作區。
- 連接 所需的 憑證。它們會被私密儲存,絕不會在公開頁面上展示。
- 為需要使用其工具的對話啟用該服務。
Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。
交給代理程式安裝
把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。
閱讀 https://sourceweft.com/mcp/com.hutchdb%2Fhutchdb/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。其他 MCP 客戶端
把它新增到你客戶端的 mcpServers 設定中。 客戶端會在首次連接時完成 OAuth 登入。
{
"mcpServers": {
"hutchdb": {
"type": "http",
"url": "https://app.hutchdb.com/api/mcp"
}
}
}README
HutchDB
A database for AI agents. No schema, SQL, or structure required.
A structured workspace that Claude Code, Codex, Cursor, Hermes, Claw, Grokbot, and other MCP clients can read and update together. Open source.
[Website] [HutchDB Cloud] [MCP] [License]
What is HutchDB?
HutchDB Core is a headless, single-user MCP server that gives every agent you run the same durable, structured data. Connect Claude Code, Codex, Cursor, VS Code, or another MCP client and they can store, query, and update shared collections of records across sessions.
Collections use schema-optional Postgres JSONB with full-text search, optional validation, and view definitions. There is no dashboard, no login screen, and no OAuth ceremony — just an MCP endpoint and a Postgres database you control.
This repo is the OSS engine. If you want people and agents working from the same visual workspace, HutchDB Cloud adds web views, published pages, social login, and organization sharing. See Core vs Cloud below.
What can you use it for?
The default home for agent working data is a markdown file: a TODO.md, a notes directory, a memory file full of prose. That works for one agent taking notes to itself. It breaks down the moment you want to filter ("open bugs above severity 2"), aggregate ("pipeline value by stage"), or have two agents update the same list without overwriting each other.
HutchDB holds the same information as real records: individually addressable, queryable, and safe for multiple agents to read and update at once. That makes it fit anywhere an agent produces or uses structured data that needs to outlast one chat. Some patterns people run on it:
Research that accumulates. Customer interviews, competitor teardowns, scraped listings, literature reviews. Each session adds records to a collection; any later session can query the whole set.
"Save these five competitor pricing pages to
competitor-pricing, then tell me who changed since last month."
Trackers you'd otherwise keep in a spreadsheet. Bug reports, content calendars, job applications, inventory, reading lists. The difference from a spreadsheet: your agents can query and update the records mid-task.
"Log this bug to
bug-reportswith severity high, then list everything still open."
Pipelines with handoffs between agents. One agent collects records, another processes them, a third reports on the results. A status field on each record marks where it is in the pipeline, so nothing gets copied between tools.
"Pull every
leadsrecord with statusnew, enrich each one, and set its status toready-for-outreach."
Working state for long-running projects. Decisions, open questions, and backlog items stay queryable after the context window closes. A new session starts by asking what came before instead of being re-briefed.
"What did we decide about the pricing page last week, and what's still unresolved?"
Repeatable playbooks. Store the instructions, inputs, and current status for recurring jobs (weekly reports, release checklists, content production) so any agent can pick one up and run it.
"Run the weekly-metrics playbook and store the results in
weekly-reports."
None of this needs schema design up front: collections auto-create on the first write and records are arbitrary JSON. Start with "save this to HutchDB," then query the same records from any connected agent.
Quick Start
Note: Full documentation lives at hutchdb.com.
-
Clone and boot (Docker):
Core migrates the database and boots on port 3000. The singleton user and personal org are inserted lazily on the first request — there is no seed step.
-
Lock it down (optional but recommended off-localhost) — require a bearer token on every MCP call by setting an API key before booting:
If unset, all requests are trusted — fine for localhost, not fine for a public host.
-
Connect your agent. For Claude Code, add to your MCP config:
Cursor, Codex, and VS Code accept the same HTTP MCP server shape — same
url, same bearer header. -
Use it. Collections auto-create on first write — there is no setup step. Just talk to your agent:
"Save these launch tasks to HutchDB." "What did we store about the pricing research last week?" "Query the bug-reports collection for anything mentioning timeouts."
-
Verify the endpoint (optional):
You should see the
hutch_*tool list (collections, records, schema, views).
Running without Docker
The dev MCP endpoint is http://localhost:3111/api/mcp (production/Docker: port 3000).
Example
A typical session with Claude Code connected to a local Core instance:
Records are arbitrary JSON in Postgres JSONB — queryable via containment filters, Mongo-style operators ($gt, $in, $exists, $contains, …), and full-text search, with optional schemas when you want structure enforced. Collections export and import as CSV or JSON when data needs to move.
HutchDB Core vs HutchDB Cloud
Core is intentionally small. If you want the product layer, run HutchDB Cloud — or fork Core and build your own.
claude.ai requires OAuth. Core ships no OAuth authorization server, so adding a Core instance to claude.ai (web) won't work out of the box. Claude Code, Cursor, Codex, and VS Code all accept a static bearer token and work fine.
Architecture
- Next.js App Router — one static landing page, one MCP route (
/api/mcp), one REST seed route (/api/v1/collections). Everything else is deleted. - Drizzle + Postgres — each collection is its own table of JSONB documents; hot fields become indexed columns automatically, everything else is queried via containment operators and full-text search. Upgrading a database from before per-collection storage: run
npm run storage:cutoveronce afterdb:migrate. - MCP server — collection tools (including per-collection stats), record tools (store/query/search/update/delete/status/transform plus CSV/JSON export and import), schema tools (describe/infer/update), and view tools. Queries support filter operators (
$gt/$gte/$lt/$lte/$ne/$in/$nin/$exists/$contains), field projection, and count/min/max/distinct/sum/avg aggregations. - Auth seam (
src/lib/auth/seam.ts) — the only place auth lives: bearer-key check whenHUTCH_API_KEYis set, singleton context otherwise. - Singleton bootstrap (
src/lib/auth/singleton.ts) — one user, one personal org, created lazily on first request.
Contributing
- Found a bug? Open an issue with repro steps.
- Want to improve Core? PRs welcome — contributors sign a CLA so the maintainer can dual-license into HutchDB Cloud. See CONTRIBUTING.md and CLA.md.
- Feedback or ideas? Issues are the front door; tell us what you're building.
Development
Status: stable enough for a single-user self-host. Breaking changes land on main; pin a commit if you need stability.
License
來源:README.md,提交 677fd23
工具
0版本歷史
1- v1.0.0最新Sep 23, 2026
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