Tukey

The open-source Julius AI alternative — inside your coding agent.
Attach a CSV or a Postgres database. Tukey profiles it, answers in SQL, and draws real charts in the conversation.

_{Named for John Tukey, who invented exploratory data analysis, the box plot, and the 1.5×IQR outlier rule this profiler runs.}

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A real DeepSeek Harness session — the agent attached a CSV, profiled it, and drew these charts as conversation nodes (headless-Chrome capture of the live UI; see the verification record):

Status: M1 + M2 + M3 complete. The dsh plugin is live-verified inside dsh web 0.1.0-rc.8 — the full attach → profile → query → chart chain ran in a real session and both charts rendered as conversation nodes (verification record). The MCP server passes protocol-level tests plus a stdio smoke. See Known limitations.

What it does

data_attach     →  register a CSV / Parquet / JSON / XLSX file as a queryable table
data_attach_db  →  attach PostgreSQL / MySQL / SQLite read-only and list its tables
data_profile    →  types, missing values, exact distinct counts, outliers, quality issues, chart ideas
data_query      →  one read-only SQL statement, results as lossless JSON
data_chart      →  bar / line / scatter / histogram / area / heatmap / boxplot (Vega-Lite,
                   interactive) + sankey / sunburst / treemap / gauge (ECharts) — with color
                   series, stacked/grouped layout, facet small multiples; line & scatter pan/zoom
data_report     →  a self-contained HTML report (profile + charts as inline SVG); prints to PDF
data_sources    →  what is currently attached

The same five tools ship on two hosts from one engine:

Every tool is also reachable from Code Mode as await tools.data_*(args), so the agent can chain the whole analysis inside one program instead of spending a round trip per step.

The workbench — a session-header panel listing this session's data sources, a chart gallery with click-to-scroll, and generated reports:

Both engines in one conversation — heatmap and boxplot drawn live by Vega-Lite, sankey and treemap rendered on the host by ECharts:

More in-conversation chart kinds (same theme, exported from a live session):

Install

DeepSeek Harness:

dsh plugin --profile web add tukey

Claude Code (or any MCP client, via stdio):

claude mcp add tukey -- npx -y tukey-mcp-server

Architecture

Three decisions shape the codebase.

The engine knows nothing about the harness. @tukey/core takes paths and SQL and returns lossless JSON. It imports no dsh, MCP, or CLI type. That is what lets the same analysis ship to Claude Code, Codex, and Cursor through an MCP adapter later without a second implementation — the single largest factor in whether a plugin reaches an audience beyond one host.

DuckDB does the statistics. SUMMARIZE returns min/max/avg/std/quartiles/ approx_unique/null_percentage for every column in one pass, and reads CSV, Parquet and JSON directly with full-file type inference. Only IQR outliers, duplicate-row detection, and the judgement about what is worth flagging are written by hand.

Two chart engines, chosen per kind — and the client bundles one. Vega-Lite owns the exploratory kinds: its grammar keeps the spec short and the browser half renders it live and interactive. ECharts covers the shapes Vega-Lite has no grammar for at all — flow (sankey), hierarchy (sunburst, treemap), and a single-value KPI (gauge). Bundling ECharts in the browser too would add ~600 kB to a single-file plugin bundle every session downloads, chart or not, so those kinds are rendered to SVG on the host and travel as markup inside the event; the spec rides along, so a client that does speak ECharts can render it live. Measured cost to the browser bundle: 0 kB.

Charts are specs carried on session events. The harness tool-card kinds are a closed set — generic, terminal, diff, search, web — with no chart member, so a tool result can only ever degrade a chart to text. A real chart has to come from a conversation node, which the client half registers.

That constraint turned out to pick the chart format too. A conversation node must rebuild its view as a pure function of durable events — no clock, no random, no live state — and the engine prefers whole-value checkpoints over deltas. A Vega-Lite spec with its data inlined is exactly that: one plain JSON value that replays byte-for-byte. Vega-Lite was chosen because it satisfies the replay rule, not because it is a popular chart library.

@tukey/core            engine, profiling, DB connectors, chart specs  (host-agnostic)
  ├── @tukey/report    Vega-Lite -> SVG (pure JS) + self-contained HTML reports
  ├── tukey            dsh host half: 7 tools + chart event
  │     └── ./client         dsh browser half: conversation node + Vega canvas
  └── tukey-mcp-server stdio MCP server: same 7 tools, charts as SVG files

Development

pnpm install
pnpm -r run build
pnpm -r run test

89 tests: 58 over the core (SQL policy, JSON conversion, profiling with exact distinct counts, charts, and live PostgreSQL/MySQL connector tests that auto-skip without the Docker fixtures), 5 over the report builder, 14 driving the real dsh plugin tools end to end against DuckDB (including per-agent isolation), and 9 protocol-level MCP tests over the SDK's in-memory transport (plus a scripted stdio smoke). Live verification against a running dsh web is scripted in scripts/mock-llm-scripted.mjs + scripts/verify-live.patch.yml — see docs/VERIFICATION.md.

Known limitations

These are real and worth reading before building on this.

• PTC 模式 (Code Mode) presets reject direct tool calls — the model must wrap them in a run_code program there. Under the Standard preset the tools are called directly. Verified behavior, documented in docs/VERIFICATION.md.
• dsh per-agent engines are bounded, not lifecycle-tracked. Each dsh agent session gets its own engine (no alias collisions), but the harness does not notify plugins on agent disposal, so the plugin holds at most 32 engines and evicts the least-recently used — that session transparently re-attaches on its next call.
• The client bundle is ~860 kB. Vega is inlined because the harness serves exactly one file per plugin and has no route for sibling chunks, so a chart-free session still pays for it.
• data_attach takes any path the host process can read. There is no workspace fencing yet; it inherits whatever the harness sandbox allows.
• XLSX depends on DuckDB's read_xlsx, which may need an extension download on first use. CSV, Parquet and JSON are covered by tests; XLSX is not.

Notes on the dsh npm packages

Two things cost time here and are worth recording for anyone else building a harness plugin:

• latest points at a broken line. npm view @deepseek-ai/dsh-tools version reports 0.0.1-rc.1, but the current line is 0.1.0-rc.8. Several 0.0.1-rc.1 packages cannot be installed at all — @deepseek-ai/dsh-client-runtime@0.0.1-rc.1 depends on @deepseek-ai/dsh-compact and @deepseek-ai/dsh-session@0.0.1-rc.1 depends on @deepseek-ai/dsh-type-meta; neither is published. Pin 0.1.0-rc.8.
• pnpm's minimumReleaseAge policy blocks the rc line while it is fresh. This repo lifts it in pnpm-workspace.yaml, with a note to restore it once dsh has a stable release.

Roadmap

License

MIT