# Consensus vs OpenCrab Consensus records 6,014,388 monthly visits with -1.2% month-over-month growth and Freemium pricing. OpenCrab records 0 monthly visits with -100% growth and Freemium pricing. | Metric | [Consensus](https://openaitools.app/tool/consensus) | [OpenCrab](https://openaitools.app/tool/opencrab) | | :--- | :--- | :--- | | Website URL | https://consensus.app | https://opencrab.sh | | Categories | AI Search Engine, AI Research Tool, AI Papers, AI Article Summarizer | AI Knowledge Graph, AI Agent, AI Research Tool | | Pricing Model | Freemium | Freemium | | Monthly Visits | 6,014,388 | 0 | | MoM Growth Rate | -1.2% | -100% | | Primary Market | United States | Global | | Direct Visits | 2,918,713 | 0 | | Review Score | 4.7 | 4.1 | | Saved Count | 31 | 0 | | Supported Platforms | Website | Website | ## Consensus Consensus works like a scholarly search engine supercharged by AI. Instead of returning a flat list of PDFs, you ask a natural-language research question and Consensus extracts claims from relevant papers, then shows you what the studies actually find. A Consensus Meter summarizes the weight of evidence for yes/no questions, so you can see at a glance whether scientists largely agree, disagree, or remain divided. The platform indexes hundreds of millions of peer-reviewed papers spanning medicine, biology, psychology, economics and more. Answers link straight back to the source studies, and you can filter by study design, journal quality, sample size and publication year to separate stronger evidence from weaker signals. Features like Deep Search, Topic Synthesis and Skills let researchers build a working knowledge base over time rather than starting from scratch on every query. Consensus is designed for researchers, clinicians, students and analysts who need trustworthy signals from the scientific record without drowning in irrelevant results. A free tier gives limited AI-powered searches each month, while paid plans unlock unlimited use, advanced filters and deeper synthesis. **Pricing & Plans:** Freemium. A free tier offers a limited number of AI-powered searches per month; paid individual plans unlock unlimited searches and advanced research features, with discounted student pricing and team/enterprise options. - **Evidence-grounded answers:** Ask a research question in plain language and get answers synthesized from peer-reviewed studies, with each claim linked to its source paper. - **Consensus Meter:** A visual summary shows how the scientific literature leans on a yes/no question, indicating agreement, disagreement or mixed evidence. - **Powerful filters:** Narrow results by study design, sample size, journal quality, publication year and more to prioritize high-quality evidence. - **Topic synthesis and Deep Search:** Aggregate findings across many studies into structured summaries that map what is known and where the gaps are. - **Research workspace:** Save papers, organize sources and build a persistent knowledge base for literature reviews and ongoing projects. **Strengths:** Answers cite real peer-reviewed papers, so claims are verifiable; Consensus Meter makes it easy to gauge scientific agreement at a glance; Rich filters help separate high-quality evidence from weaker studies; Fast, clean interface designed around research workflows **Limitations:** Free tier caps the number of AI-assisted searches per month; Coverage is strongest for STEM and health fields, lighter for some humanities topics; It guides you toward sources but is not a substitute for reading full papers [Profile (Markdown)](https://openaitools.app/tool/consensus.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 Consensus and OpenCrab compare in monthly traffic? Consensus has 6,014,388 monthly visits, while OpenCrab has 0. Traffic estimates describe audience size, not product quality. ### How do their growth rates compare? Consensus has a month-over-month growth rate of -1.2%; OpenCrab has -100%. ### How does pricing compare? Consensus: Freemium. Freemium. A free tier offers a limited number of AI-powered searches per month; paid individual plans unlock unlimited searches and advanced research features, with discounted student pricing and team/enterprise options. 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 | [Perplexity](https://openaitools.app/tool/perplexity-ai) | 88,310,223 | -3.7% | Freemium | Covers general web sources alongside academic papers, but lacks specialized scientific synthesis metrics and consensus ratings. | [.md](https://openaitools.app/tool/perplexity-ai.md) | | 3 | [Semantic Scholar](https://openaitools.app/tool/semantic-scholar) | 8,198,672 | +5.8% | Free | Completely free access to a massive scholarly index, but offers less automated natural-language evidence synthesis than Consensus. | [.md](https://openaitools.app/tool/semantic-scholar.md) | | 4 | [Kagi Search](https://openaitools.app/tool/kagi-search) | 4,647,605 | +3.2% | Free Trial, Paid | A paid, ad-free search engine that answers to its users | [.md](https://openaitools.app/tool/kagi-search.md) | | 5 | [SciSpace](https://openaitools.app/tool/scispace) | 4,464,111 | +8.6% | Freemium | Provides deeper PDF reading and interactive literature analysis tools, but is less focused on quick evidence aggregation. | [.md](https://openaitools.app/tool/scispace.md) | | 6 | [Elicit](https://openaitools.app/tool/elicit) | 1,751,507 | +3.1% | Freemium | Performs advanced systematic review data extraction and evidence synthesis, but has a more complex interface than Consensus. | [.md](https://openaitools.app/tool/elicit.md) | | 7 | [Jenni](https://openaitools.app/tool/jenni) | 1,498,133 | +5.2% | Freemium | The AI workspace where researchers read, write, and cite with every claim traceable to its source | [.md](https://openaitools.app/tool/jenni.md) | | 8 | [Rayyan](https://openaitools.app/tool/rayyan) | 1,116,437 | +7.9% | Freemium | AI-assisted systematic review software for screening, extraction, and evidence synthesis at scale | [.md](https://openaitools.app/tool/rayyan.md) | | 9 | [Scite](https://openaitools.app/tool/scite) | 841,974 | +1.1% | Free Trial, Contact for Pricing | Tracks how papers are cited with Smart Citations to gauge reliability, but features a less direct Q&A synthesis. | [.md](https://openaitools.app/tool/scite.md) | | 10 | [ResearchRabbit](https://openaitools.app/tool/researchrabbit) | 831,571 | +3.1% | Free | Excellent for visual citation mapping and literature discovery, but lacks automated paper Q&A and evidence synthesis. | [.md](https://openaitools.app/tool/researchrabbit.md) | --- Source: https://openaitools.app/compare/consensus-vs-opencrab More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)