Runs evidence-aware, multi-provider research with the Librarium v2 CLI. Use for deep research, competitive research, answer-engine visibility checks, or questions needing grounded multi-source coverage.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Run research queries through Librarium’s v2 public provider/profile catalog. There are 34 built-in providers and 41 implemented profiles. Preserve the profile and collection provenance when reporting results; do not turn source counts or agreement into a confidence claim.
Before the first query in an orb, run librarium --version and require major
version 2. The Librarium repository's .agents/setup installs its built v2
checkout globally. In other orbs, install the published v2 package when it is
available:
npm install -g 'librarium@^2'
Do not silently fall back to Librarium 1.x or install a mutable Git branch. If
npm has no v2 release yet, report that distribution blocker instead. Configure
available API keys with librarium init --auto, then inspect the usable matrix
offline with librarium doctor and librarium ls --json. This confirms only
configuration and credential presence, not authentication or connectivity, and
does not load configured custom provider code. Use librarium doctor --live
only when the user explicitly wants live connectivity tests; it loads trusted
custom providers, makes provider network requests, and may incur charges. Never
print secret values.
Analyze the user's research question. Determine:
quick for a curated low-latency
set, deep for research-report profiles, visibility for an explicit
nine-perspective comparison, all for catalog-derived coverage). Use
custom:<name> for a user-authored group.sync for quick queries, mixed for deep research)Select providers based on query type:
quick; add named durable profiles or
deep only when the question warrants the latency and possible spend.quick group (AI-grounded only, fast)all only after confirming its configured,
credentialed membership and cost exposure.visibility only when you deliberately want six
SearchAPI-collected consumer-surface observations compared with three
first-party API baselines. Treat the six collection-vendor results as
correlated evidence, not independent confirmation.--providers (canonical IDs or display names,
e.g. -p "Exa Search,brave-search")Run the query:
librarium run "your query here" --group <group> [--mode mixed]
If a profile is background/durable and was submitted in async mode:
librarium status --wait
Once the provider is observed complete, retrieve the terminal result:
librarium status --retrieve
Read the output files:
summary.md -- Overall research summary with statisticssources.json -- Deduplicated citations ranked by frequency{provider}.md files for detailed per-provider resultsrun.json -- Machine-readable manifestCombine findings from multiple providers into a coherent answer. Record source overlap and provenance, but do not convert a higher citation count into a confidence score: shared collectors and repeated sources can make that evidence correlated.
| Command | Purpose |
|---|---|
librarium run <query> | Run research query |
librarium run <query> --group quick | Fast AI-grounded search |
librarium run <query> --group deep | Deep research (async) |
librarium run <query> --group visibility | Compare six collected consumer surfaces with three first-party API baselines |
librarium run <query> --group all | Catalog-derived selectable coverage |
librarium answer <query> | Fan out (default quick) and synthesize one grounded, cited answer to answer.md |
librarium run <query> --max-cost 0.50 | Stop launching providers once API-reported cost crosses the budget |
librarium run <query> --yes | Skip the deep-research pre-flight confirm (3+ deep providers) |
librarium status | Check async tasks |
librarium status --wait --retrieve | Wait and fetch Node CLI async results |
librarium live-validation --fixture /absolute/path/to/fixture.json | Replay a strict, network-free canonical fixture |
librarium usage [--days N] [--json] | Aggregate API-reported cost and tokens across past runs |
librarium run <query> --html --open | Run, then open an HTML report |
librarium run <query> --jsonl | Run, then write machine-readable results.jsonl |
librarium browse | Browse past runs interactively |
librarium html [run-dir] | Generate report.html for a run |
librarium jsonl [run-dir] | Generate results.jsonl for a run |
librarium refine <goal> | Tier-tuned query variants, no dispatch |
librarium ls | List providers and status |
librarium doctor | Check provider configuration and credential presence offline |
librarium doctor --live | Test connectivity with provider network requests; charges may apply |
librarium config | Show resolved config |
librarium cleanup [--days N] [--dry-run] | Delete run dirs older than N days (default 30) |
librarium clear [--dry-run] [-i] [--yes] | Delete all run dirs (alias for cleanup --all); -i to pick interactively |
Instead of shelling out to the CLI, agents can drive librarium over the Model Context Protocol with librarium mcp (stdio transport). Register it once with claude mcp add librarium -- librarium mcp, then call the tools: research, get_results, check_async, list_providers, list_groups. The research tool runs the same silent file-writing pipeline as librarium run and returns a compact structured result; fetch full provider markdown with get_results.
| Tier | Providers | Speed | Depth |
|---|---|---|---|
| background/durable | exa/research, openai-research/research, gemini-deep/research, perplexity-sonar-deep/research, perplexity-deep-research/research, you-research/research, parallel/research, and valyu/research | Minutes to longer | Persisted handles that can be polled and retrieved |
| inline | Search, grounded, collected surface, and chat profiles | Usually seconds | Immediate response; no durable handle |
The six SearchAPI surface profiles observe consumer-facing ChatGPT, Gemini,
Perplexity, Google AI Mode, Bing Copilot, and Google AI Overview output through
one upstream collector. Treat agreement among them as correlated visibility
evidence, not independent corroboration or parity with a particular logged-in
user. zeroRetention is an account capability: if explicitly configured,
Librarium fails closed when the account rejects it. It makes no broader
retention or privacy guarantee. SerpBase may log search queries for billing,
debugging, abuse prevention, and account logs; no zero-retention mode or fixed
public retention period is documented.
./agents/librarium/{timestamp}-{slug}/
prompt.md, run.json, summary.md, sources.json
{provider}.md, {provider}.meta.json
answer.md (when using `librarium answer`)
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
日本語の概要は準備中です。原文の説明を表示しています。