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.
npx agentmods add skills/cyanheads/reference-data-mcp-server/api-mirrornpx skills add cyanheads/reference-data-mcp-server --skill api-mirrorgit clone --depth 1 https://github.com/cyanheads/reference-data-mcp-serverWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00068 | $0.02142 |
| Opus 5 | $0.00034 | $0.01071 |
| Sonnet 5 | $0.00014 | $0.00428 |
| Haiku 4.5 | $0.00007 | $0.00214 |
Grade A, and why
api-mirror 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.
This is a copy
100% identical to api-mirror — 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.
How it starts
The opening of the file, as written. The whole thing — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context
The MirrorService owns the source-agnostic half of a local mirror — the embedded store, the sync-state machine, the runner — so a server supplies only the two parts that are irreducibly per-source: the ingester (a sync generator) and the schema. It targets the embedded-SQLite tier (~10⁴–10⁷ rows). Node/Bun only: bun:sqlite is built-in on Bun, better-sqlite3 is an optional peer dependency on Node; the store is unavailable on Workers (no SQLite, no persistent filesystem).
Import from @cyanheads/mcp-ts-core/mirror.
The shape
import { defineMirror, sqliteMirrorStore } from '@cyanheads/mcp-ts-core/mirror';
const papers = defineMirror({
name: 'arxiv-papers',
store: sqliteMirrorStore({
path: config.mirrorPath,
primaryKey: 'id',
columns: { id: 'TEXT', title: 'TEXT', authors: 'TEXT', abstract: 'TEXT', updated: 'TEXT' },
fts: ['title', 'authors', 'abstract'], // opt-in FTS5 external-content index
indexes: [{ columns: ['updated'] }],
}),
// The ingester — the one part that is always server-specific.
async *sync({ mode, cursor, checkpoint, signal }) {
for await (const page of harvestPages({ resumeFrom: cursor, since: checkpoint, signal })) {
yield {
records: page.rows, // objects keyed by declared column
tombstones: page.deletedIds, // primary-key values to delete
cursor: page.token, // volatile resume position (see below)
checkpoint: page.maxStamp, // durable high-water mark (see below)
};
}
},
});
await papers.runSync({ mode: 'init', signal: AbortSignal.timeout(3_600_000) }); // full; resumes on interrupt
await papers.runSync({ mode: 'refresh' }); // incremental
const { rows, total } = await papers.query({ match: 'transformers', limit: 10, offset: 0 });
const status = await papers.status(); // { status, ready, checkpoint, total, ... }
cursor vs. checkpoint — the core distinction
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.
- 2d ago First seen · 133 lines · 68 tokens per session scan A 89b98aefc722
api-mirror 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 68 tokens to every session and 2,142 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to api-mirror, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
re-extract
Re-extract the legacy Confluence RouterOS documentation export into SQLite. Use for rebuilding the current DB pipeline, not for the manual.mikrotik.com Docusaurus migration.
api-canvas
DataCanvas primitive reference — a Tier 3 SQL/analytical workspace for tabular MCP servers, backed by DuckDB. Use when registering tables from upstream APIs, running ad-hoc SQL across them, and exporting results. Covers the acquire → register → query → export flow, per-table TTL, the token-sharing pattern for…
api-canvas
DataCanvas primitive reference — a Tier 3 SQL/analytical workspace for tabular MCP servers, backed by DuckDB. Use when registering tables from upstream APIs, running ad-hoc SQL across them, and exporting results. Covers the acquire → register → query → export flow, per-table TTL, the token-sharing pattern for…
api-canvas
DataCanvas primitive reference — a Tier 3 SQL/analytical workspace for tabular MCP servers, backed by DuckDB. Use when registering tables from upstream APIs, running ad-hoc SQL across them, and exporting results. Covers the acquire → register → query → export flow, per-table TTL, the token-sharing pattern for…
api-mirror
Stand up a persistent, self-refreshing local mirror of a bulk upstream dataset with the MirrorService (@cyanheads/mcp-ts-core/mirror). Use when a server wraps a large or slow API and should query a synced local index (embedded SQLite + FTS5) instead of paginating the live API per request.
api-canvas
DataCanvas primitive reference — a Tier 3 SQL/analytical workspace for tabular MCP servers, backed by DuckDB. Use when registering tables from upstream APIs, running ad-hoc SQL across them, and exporting results. Covers the acquire → register → query → export flow, per-table TTL, the token-sharing pattern for…