--- title: "firecrawl vs JARVIS" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/firecrawl-firecrawl-vs-likhithsai2580-jarvis" tools: ["firecrawl-firecrawl", "likhithsai2580-jarvis"] --- # firecrawl vs JARVIS *GraphCanon updated Sep 20, 2026* ## Verdict Pick firecrawl if firecrawl is a web data API for large-scale web scraping, searching, and data extraction tasks, supporting AI agents for intelligent web interaction and data retrieval; pick JARVIS if jARVIS is a Python-based AI assistant offering multifunctional capabilities including voice interaction and visual interfaces. [firecrawl](https://firecrawl.dev) reports 182k GitHub stars, 9.8k forks, and 641 open issues, last pushed Sep 18, 2026. [JARVIS](https://github.com/Likhithsai2580/JARVIS) has 147 stars, 64 forks, and 2 open issues, last pushed Jul 30, 2026. Figures are from public GitHub metadata via [firecrawl's repository](https://github.com/firecrawl/firecrawl) and [JARVIS's repository](https://github.com/Likhithsai2580/JARVIS). | | [firecrawl](/tools/firecrawl-firecrawl.md) | [JARVIS](/tools/likhithsai2580-jarvis.md) | | --- | --- | --- | | Tagline | The web data API to search, scrape, and interact at scale. | A versatile AI assistant that integrates various functionalities | | Stars | 181,801 | 147 | | Forks | 9,842 | 64 | | Open issues | 641 | 2 | | Language | TypeScript | Python | | Adopt for | Firecrawl is a web data API for large-scale web scraping, searching, and data extraction tasks, supporting AI agents for intelligent web interaction and data retrieval. | JARVIS is a Python-based AI assistant offering multifunctional capabilities including voice interaction and visual interfaces. | | Persona | - | - | | Runtime | - | - | | License | AGPL-3.0 for the main project, MIT License for SDKs and some UI components. | MIT | | Categories | AI Agents, Data & Retrieval | AI Agents, Data & Retrieval, Speech & Audio | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [firecrawl](/tools/firecrawl-firecrawl.md) | [JARVIS](/tools/likhithsai2580-jarvis.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Steady (60%) | | Days since push | 0d | 51d | | Open issues (now) | 641 | 2 | | Stars delta | +14k (30d) | +4 (30d) | | Open issues delta | +133 (30d) | 0 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/firecrawl-firecrawl/trust.md) | [trust report](/tools/likhithsai2580-jarvis/trust.md) | ## Decision facts: firecrawl - **Pricing:** unknown - Pricing details are not provided in the repository data. - **Requirements:** Users must respect websites' policies when scraping and comply with robots.txt directives. - **Adopt for:** Firecrawl is a web data API for large-scale web scraping, searching, and data extraction tasks, supporting AI agents for intelligent web interaction and data retrieval. - **License detail:** AGPL-3.0 for the main project, MIT License for SDKs and some UI components. ## Decision facts: JARVIS - **Adopt for:** JARVIS is a Python-based AI assistant offering multifunctional capabilities including voice interaction and visual interfaces. ## Choose when ### Choose firecrawl if… - firecrawl is primarily TypeScript; JARVIS is Python. - License: firecrawl is AGPL-3.0, JARVIS is MIT. - Pricing: Pricing details are not provided in the repository data.. - Requirements: Users must respect websites' policies when scraping and comply with robots.txt directives.. - Tags unique to firecrawl: ai, ai-agents, ai-crawler, ai-scraping. - When you need to perform large-scale web scraping and data extraction tasks with support for AI-driven web interactions. ### Choose JARVIS if… - JARVIS is primarily Python; firecrawl is TypeScript. - License: JARVIS is MIT, firecrawl is AGPL-3.0. - Tags unique to JARVIS: agent, agents, assistant, g4f. - Also covers Speech & Audio. - Use JARVIS if you require an offline-capable AI assistant with local LLM support, enhancing privacy and reducing reliance on cloud services. ## When NOT to use firecrawl - If your project requires a tool that does not support AI-driven interactions and you prefer a simpler, more straightforward scraping solution. - When you are looking for a solution that does not come with the AGPL-3.0 license, as this might not be compatible with your project's licensing requirements. ## When NOT to use JARVIS - Avoid using JARVIS if you need a solution that strictly operates in an online environment; it is better suited for scenarios where both offline and online modes are acceptable. - Do not use JARVIS if your project requires highly specialized functionality that the multifunctional design of JARVIS cannot support with its current integrations. ## Common questions ### What is the difference between firecrawl and JARVIS? firecrawl: The web data API to search, scrape, and interact at scale.. JARVIS: A versatile AI assistant that integrates various functionalities. See the comparison table for live GitHub stats and shared categories. ### When should I choose firecrawl over JARVIS? Choose firecrawl over JARVIS when firecrawl is primarily TypeScript; JARVIS is Python; License: firecrawl is AGPL-3.0, JARVIS is MIT; Pricing: Pricing details are not provided in the repository data.; Requirements: Users must respect websites' policies when scraping and comply with robots.txt directives.; Tags unique to firecrawl: ai, ai-agents, ai-crawler, ai-scraping; When you need to perform large-scale web scraping and data extraction tasks with support for AI-driven web interactions. ### When should I choose JARVIS over firecrawl? Choose JARVIS over firecrawl when JARVIS is primarily Python; firecrawl is TypeScript; License: JARVIS is MIT, firecrawl is AGPL-3.0; Tags unique to JARVIS: agent, agents, assistant, g4f; Also covers Speech & Audio; Use JARVIS if you require an offline-capable AI assistant with local LLM support, enhancing privacy and reducing reliance on cloud services. ### When should I avoid firecrawl? If your project requires a tool that does not support AI-driven interactions and you prefer a simpler, more straightforward scraping solution. When you are looking for a solution that does not come with the AGPL-3.0 license, as this might not be compatible with your project's licensing requirements. ### When should I avoid JARVIS? Avoid using JARVIS if you need a solution that strictly operates in an online environment; it is better suited for scenarios where both offline and online modes are acceptable. Do not use JARVIS if your project requires highly specialized functionality that the multifunctional design of JARVIS cannot support with its current integrations. ### Is firecrawl or JARVIS more popular on GitHub? firecrawl has more GitHub stars (181,801 vs 147). Stars measure visibility, not whether either tool fits your constraints. ### Are firecrawl and JARVIS open source? Yes - both are open-source projects on GitHub (firecrawl: AGPL-3.0, JARVIS: MIT). ### Where can I find alternatives to firecrawl or JARVIS? GraphCanon lists graph-backed alternatives at [firecrawl alternatives](/tools/firecrawl-firecrawl/alternatives) and [JARVIS alternatives](/tools/likhithsai2580-jarvis/alternatives) ([firecrawl markdown twin](/tools/firecrawl-firecrawl/alternatives.md), [JARVIS markdown twin](/tools/likhithsai2580-jarvis/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/firecrawl-firecrawl-vs-likhithsai2580-jarvis.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, firecrawl or JARVIS? firecrawl: Very active. JARVIS: Steady. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for firecrawl and JARVIS? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [firecrawl trust report](/tools/firecrawl-firecrawl/trust); [JARVIS trust report](/tools/likhithsai2580-jarvis/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=firecrawl-firecrawl`](/api/graphcanon/graph?tool=firecrawl-firecrawl) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_