# Liminary vs OpenCrab

Liminary records 12,246 monthly visits with -30.4% month-over-month growth and Freemium pricing. OpenCrab records 0 monthly visits with -100% growth and Freemium pricing.

| Metric | [Liminary](https://openaitools.app/tool/liminary) | [OpenCrab](https://openaitools.app/tool/opencrab) |
| :--- | :--- | :--- |
| Website URL | https://liminary.io | https://opencrab.sh |
| Categories | AI Knowledge Management, AI Summarizer, AI Youtube Summary, AI Article Summarizer | AI Knowledge Graph, AI Agent, AI Research Tool |
| Pricing Model | Freemium | Freemium |
| Monthly Visits | 12,246 | 0 |
| MoM Growth Rate | -30.4% | -100% |
| Primary Market | United States | Global |
| Direct Visits | 4,874 | 0 |
| Review Score | 4.1 | 4.1 |
| Saved Count | 0 | 0 |
| Supported Platforms | Website | Website |

## Liminary

Liminary targets a familiar professional failure mode: you do the research, then spend the first hour of the next project re-finding it. The tool acts as a persistent memory layer. Articles, reports, PDFs, videos and AI chats are saved with one click while you browse, and you can add your own notes and context as you read, so the stored knowledge reflects your thinking and not just the source text.

Retrieval is the differentiating part. Rather than waiting for you to search, Liminary proactively surfaces what is relevant while you write, and it now includes Magnet, a meeting sidekick that pulls in the right material in real time. Answers are grounded in your saved sources, with every insight traceable to a citation and every source one click away. Fact-checking and gap detection run against your own material rather than the open internet, so you can verify claims and spot missing pieces before someone else does.

Security is positioned as a core feature rather than an afterthought: data is encrypted, siloed to your workspace, and never used to train AI models, with the team crediting ex-Dropbox security, ML and search engineers. The product is aimed at consultants, researchers, analysts and small teams whose recommendations carry professional risk if the underlying facts are wrong.

Practicalities: Liminary ships as browser extensions for Chrome and Firefox with a rated 5-out-of-5 presence on the Chrome Web Store, and the vendor publishes benchmark posts on long-term memory evaluation. Pricing structure beyond a free download is presented on the site; check there for current plan tiers.

**Pricing & Plans:** Free download available to get started. Subscription tiers for professional and small-team use are listed on the Liminary site. Check the official pricing page for current plan details, since published tiers may change.

- **One-click saving anywhere:** Capture web pages, PDFs, videos, reports and LLM chats while you browse, then annotate them with your own notes and context.
- **Proactive recall:** Instead of waiting for a search, Liminary surfaces the relevant saved material while you write and inside meetings.
- **Magnet meeting sidekick:** A meeting companion that pulls in the right information at the right moment, then saves the summary, full transcript and your notes for later recall.
- **Sourced, traceable answers:** Every answer points back to where it came from, internal or external, so you can verify claims rather than trust a black box.
- **Fact check and gap detection:** Validate claims against your own saved sources and find what is missing in a draft, including directly inside Notion.

**Strengths:** Proactive recall means relevant knowledge finds you instead of requiring a search; Answers stay traceable to saved sources, which suits high-stakes professional work; Captures many source types in one place: pages, PDFs, videos and AI chats; Explicit privacy stance: encrypted, siloed per workspace and never used for model training

**Limitations:** Value depends on you actually saving sources, so the habit has to be built first; Overlaps with note tools like Notion, which can mean deciding where knowledge should live; Full plan structure is not fully clear from the landing page alone, so pricing needs checking

[Profile (Markdown)](https://openaitools.app/tool/liminary.md)

## OpenCrab

OpenCrab is built around a simple idea: knowledge should be structured as a graph before agents reason over it. You feed the platform documents, URLs, notes or code, and it handles the unglamorous work of parsing, OCR and chunking. From there it extracts entities, concepts, evidence, relationships and claims, weaving them into a source-attributed ontology graph.

The second half of the product is reuse. Graphs can be saved as versioned ontology packs, shared with teammates, or published and sold through the marketplace. A researcher can turn a stack of papers into a queryable, citation-backed graph; a domain expert can package their know-how as a sellable pack; an AI builder can wire the graph into an agent as long-term memory.

The connector layer is what ties it together. A single MCP server means Claude, ChatGPT, Cursor, Codex and other clients all see the same graph, so grounded retrieval travels with you across tools rather than being locked in one workspace. Pricing starts free, with paid tiers for private ingestion and pack publishing.

**Pricing & Plans:** Free tier at $0/month for exploring and sharing public ontology packs and basic graph queries. Pro is $10/month for private document ingestion and a personal graph RAG workspace. Expert is $30/month for pack publishing workflows and MCP reverse ingest. Billing is handled securely via Paddle and can be changed at any time.

- **Document ingestion and parsing:** Upload documents, URLs, notes or code and let the platform handle parsing, OCR and chunking automatically.
- **Ontology graph construction:** Extract entities, concepts, evidence, relationships and claims into a graph where every node traces back to a source.
- **Reusable ontology packs:** Bundle a graph into a versioned, reusable pack you can share with your team or sell in the marketplace.
- **MCP server integration:** One MCP server lets Claude, ChatGPT, Cursor, Codex and other clients query the same graph.
- **Graph RAG querying:** Retrieve grounded, cited answers from your graph instead of relying on a model's memory alone.

**Strengths:** Turns unstructured documents into a source-attributed graph rather than a flat vector index; MCP server means the same grounded knowledge works across Claude, ChatGPT, Cursor and Codex; Ontology packs are reusable, shareable and sellable, creating value beyond a single project; CRUD-style tiers are affordable, with a genuinely usable free level

**Limitations:** Some features (pack publishing, MCP reverse ingest) are gated behind the Expert tier; Best value requires feeding it well-structured documents; messy inputs limit graph quality; The public library and marketplace are still relatively young, so niche ontologies may be sparse

[Profile (Markdown)](https://openaitools.app/tool/opencrab.md)

## Frequently Asked Questions

### How do Liminary and OpenCrab compare in monthly traffic?

Liminary has 12,246 monthly visits, while OpenCrab has 0. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Liminary has a month-over-month growth rate of -30.4%; OpenCrab has -100%.

### How does pricing compare?

Liminary: Freemium. Free download available to get started. Subscription tiers for professional and small-team use are listed on the Liminary site. Check the official pricing page for current plan details, since published tiers may change. OpenCrab: Freemium. Free tier at $0/month for exploring and sharing public ontology packs and basic graph queries. Pro is $10/month for private document ingestion and a personal graph RAG workspace. Expert is $30/month for pack publishing workflows and MCP reverse ingest. Billing is handled securely via Paddle and can be changed at any time.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Notion](https://openaitools.app/tool/t) | 173,441,670 | +0.1% | Freemium | The AI workspace where teams and agents get work done together | [.md](https://openaitools.app/tool/t.md) |
| 2 | [Studocu](https://openaitools.app/tool/studocu-global) | 39,297,122 | +1.1% | Freemium | Share and access study materials worldwide — with AI study tools built in | [.md](https://openaitools.app/tool/studocu-global.md) |
| 3 | [SciSpace](https://openaitools.app/tool/scispace) | 4,464,111 | +8.6% | Freemium | AI research platform for reading, understanding and writing scientific papers | [.md](https://openaitools.app/tool/scispace.md) |
| 4 | [Readray (formerly Lilys AI)](https://openaitools.app/tool/lilys-ai) | 967,113 | -9.7% | Freemium | A proactive AI reading lens for papers, videos, and web pages | [.md](https://openaitools.app/tool/lilys-ai.md) |
| 5 | [Connected Papers](https://openaitools.app/tool/connected-papers) | 750,576 | +3.1% | Freemium | Explore the academic literature as a visual graph of related papers | [.md](https://openaitools.app/tool/connected-papers.md) |
| 6 | [Linnk.AI](https://openaitools.app/tool/linnk-ai) | 451,514 | +12.4% | Freemium | Translate, summarize, and understand documents in 154 languages without losing the layout | [.md](https://openaitools.app/tool/linnk-ai.md) |
| 7 | [LlamaIndex](https://openaitools.app/tool/llamaindex) | 387,910 | +19.9% | Freemium, Contact for Pricing | Turn any document into AI-ready context with agentic parsing and extraction | [.md](https://openaitools.app/tool/llamaindex.md) |
| 8 | [Scholarcy](https://openaitools.app/tool/scholarcy) | 195,058 | +4.6% | Freemium | Turn research papers and articles into interactive summary flashcards | [.md](https://openaitools.app/tool/scholarcy.md) |
| 9 | [Fabric](https://openaitools.app/tool/fabric) | 168,987 | +2.7% | Freemium | Your files, notes and meetings in one drive — with an AI that knows all of it. | [.md](https://openaitools.app/tool/fabric.md) |
| 10 | [Mem.ai](https://openaitools.app/tool/mem-ai) | 137,457 | -1.2% | Freemium, Paid | An AI notes app that organizes your knowledge for you | [.md](https://openaitools.app/tool/mem-ai.md) |

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Source: https://openaitools.app/compare/liminary-vs-opencrab

More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)