api-canvas

A DuckDB-backed workspace for registering tabular data from APIs, querying multiple tables with SQL, and exporting results as CSV, Parquet, or JSON.

In plain words
What is it for?
Use it for aggregations, grouping, joins, time-based filters, and exporting analyzed table data.
Why use it?
It gives an agent a place to combine and analyze structured API results instead of handling each response separately. It is disabled by default and does not support Cloudflare Workers.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/cyanheads/reference-data-mcp-server/api-canvas
Any agent
npx skills add cyanheads/reference-data-mcp-server --skill api-canvas
Clone the repo
git clone --depth 1 https://github.com/cyanheads/reference-data-mcp-server

Made for: Claude Code, Codex.

Per session 85 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 7,799 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00085 $0.07799
Opus 5 $0.00043 $0.03900
Sonnet 5 $0.00017 $0.01560
Haiku 4.5 $0.00009 $0.00780

Measured 2d ago against content hash a15da8c76763, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

api-canvas scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

100% identical to api-canvas — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/api-canvas/SKILL.md · 556 lines

How it starts

The opening of the file, as written. The whole thing — 556 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Overview

DataCanvas is a primitive for storage stashes, canvas computes. The existing IStorageProvider is a key/value abstraction — it can stash blobs but exposes no analytical surface. DataCanvas is the analytical surface: register tabular data from upstream APIs, run SQL across multiple registered tables, and export results as CSV/Parquet/JSON.

Tier 3@duckdb/node-api is an optional peer dependency (bun add @duckdb/node-api). Servers that don't enable canvas pay zero install cost. Lazy-loaded on first use.

Disabled by default. Set CANVAS_PROVIDER_TYPE=duckdb to enable. Otherwise core.canvas is undefined.

Cloudflare Workers: unsupported. DuckDB has no V8-isolate build. Setting CANVAS_PROVIDER_TYPE=duckdb on a Worker fails closed with a ConfigurationError at init time.


When canvas earns its keep

Two gates before wiring canvas in — both must be yes. Canvas that fails either is a SQL surface nobody queries.

  1. Is the data analytical, not just large? Canvas is for tabular/numeric result sets an agent runs SQL over — aggregate, group, join, time-series filter. A discovery/search surface returning categorical metadata (titles, IDs, types, dates) where the workflow is find the record, then drill into it does not qualify, regardless of row count. A 5,000-row search result is still discovery. The gate is shape, not size: the right question is "would an agent write SELECT … GROUP BY against this?", not "does it have many rows?" For name→ID resolution over a bounded list, reach for MCP-side list filtering (see the design-mcp-server skill) instead.
  2. Is it too big to inline? A result that fits the response (≤ ~100 rows of compact data) just gets inlined — no canvas. Canvas is the third option only when shape and size both call for it.

If canvas earns its keep, it carries an obligation: a tool that emits a canvas_id MUST ship a dataframe_query tool in the same server's surface (see the simple-shape Tools row and the Checklist). A canvas_id with no query tool is dead output — the agent literally cannot reach the staged data.

Read the full file on GitHub · 556 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 556 lines · 85 tokens per session scan A a15da8c76763

Subscribe to this mod's changes

api-canvas is a skill published in the GitHub repository cyanheads/reference-data-mcp-server (1 stars, last pushed 8d ago), licensed Apache-2.0. It adds 85 tokens to every session and 7,799 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to api-canvas, differing in 0 lines, and is treated as a copy.

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