--- title: "tradingview-mcp vs awesome-LLM-resources" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/atilaahmettaner-tradingview-mcp-vs-wangrongsheng-awesome-llm-resources" tools: ["atilaahmettaner-tradingview-mcp", "wangrongsheng-awesome-llm-resources"] --- # tradingview-mcp vs awesome-LLM-resources *GraphCanon updated Aug 26, 2026* ## Verdict Pick tradingview-mcp if tradingview-mcp is designed for developers and financial professionals seeking real-time market data and advanced technical analysis tools across multiple trading platforms including Claude, ChatGPT, Cursor among others; pick awesome-LLM-resources if awesome-LLM-resources offers a curated and comprehensive list of resources related to Large Language Models (LLMs), including materials for specialized areas like RAG (Retrieval-Augmented Generation) and agentic RL. [tradingview-mcp](https://pro.cryptosieve.com) reports 4.2k GitHub stars, 911 forks, and 11 open issues, last pushed Aug 24, 2026. [awesome-LLM-resources](https://github.com/WangRongsheng/awesome-LLM-resources) has 8.8k stars, 950 forks, and 23 open issues, last pushed Aug 14, 2026. Figures are from public GitHub metadata via [tradingview-mcp's repository](https://github.com/atilaahmettaner/tradingview-mcp) and [awesome-LLM-resources's repository](https://github.com/WangRongsheng/awesome-LLM-resources). | | [tradingview-mcp](/tools/atilaahmettaner-tradingview-mcp.md) | [awesome-LLM-resources](/tools/wangrongsheng-awesome-llm-resources.md) | | --- | --- | --- | | Tagline | Real-time market data and technical analysis for financial markets | Summary of the world's best LLM resources. | | Stars | 4,229 | 8,845 | | Forks | 911 | 950 | | Open issues | 11 | 23 | | Language | Python | - | | Adopt for | tradingview-mcp is designed for developers and financial professionals seeking real-time market data and advanced technical analysis tools across multiple trading platforms including Claude, ChatGPT, Cursor among others. | awesome-LLM-resources offers a curated and comprehensive list of resources related to Large Language Models (LLMs), including materials for specialized areas like RAG (Retrieval-Augmented Generation) and agentic RL, as a | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | Developer Tools | AI Agents, Developer Tools, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [tradingview-mcp](/tools/atilaahmettaner-tradingview-mcp.md) | [awesome-LLM-resources](/tools/wangrongsheng-awesome-llm-resources.md) | | --- | --- | --- | | Days since push | 1d | 2d | | Open issues (now) | 11 | 23 | | Stars delta | +550 (30d) | +142 (30d) | | Open issues delta | +4 (30d) | -13 (30d) | | Full report | [trust report](/tools/atilaahmettaner-tradingview-mcp/trust.md) | [trust report](/tools/wangrongsheng-awesome-llm-resources/trust.md) | ## Decision facts: tradingview-mcp - **Pricing:** freemium - The MIT license offers free use, but proprietary add-ons may apply costs depending on the services you opt into when extending beyond base capabilities. - **Adopt for:** tradingview-mcp is designed for developers and financial professionals seeking real-time market data and advanced technical analysis tools across multiple trading platforms including Claude, ChatGPT, Cursor among others. ## Decision facts: awesome-LLM-resources - **Adopt for:** awesome-LLM-resources offers a curated and comprehensive list of resources related to Large Language Models (LLMs), including materials for specialized areas like RAG (Retrieval-Augmented Generation) and agentic RL, as a ## Choose when ### Choose tradingview-mcp if… - License: tradingview-mcp is MIT, awesome-LLM-resources is Apache-2.0. - Pricing: The MIT license offers free use, but proprietary add-ons may apply costs depending on the services you opt into when extending beyond base capabilities.. - Tags unique to tradingview-mcp: backtesting, crypto, forex, futures. - tradingview-mcp ships Docker support for self-hosted deployment. - When you need to access real-time market data from various asset classes like stocks, crypto, forex, and futures from global exchanges. ### Choose awesome-LLM-resources if… - License: awesome-LLM-resources is Apache-2.0, tradingview-mcp is MIT. - Tags unique to awesome-LLM-resources: awesome-list, book, course, large language models. - Also covers AI Agents, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training. - - It's ideal when you seek an exhaustive and up-to-date compilation covering extensive knowledge points in LLM technologies. ## When NOT to use tradingview-mcp - Do not use if you are developing for a non-MCP compatible platform or if real-time data and complex technical analysis are not required. - Avoid using this tool if your project focuses specifically on financial advice platforms that do not require integration with multiple assets types in real time. ## When NOT to use awesome-LLM-resources - - Avoid using this resource if you specifically need detailed step-by-step guides or hands-on tutorials that focus deeply on a single technology rather than broad coverage. - - It might not be the best choice when you are looking for resources in languages other than English, especially given its extensive English content. ## Common questions ### What is the difference between tradingview-mcp and awesome-LLM-resources? tradingview-mcp: Real-time market data and technical analysis for financial markets. awesome-LLM-resources: Summary of the world's best LLM resources.. See the comparison table for live GitHub stats and shared categories. ### When should I choose tradingview-mcp over awesome-LLM-resources? Choose tradingview-mcp over awesome-LLM-resources when License: tradingview-mcp is MIT, awesome-LLM-resources is Apache-2.0; Pricing: The MIT license offers free use, but proprietary add-ons may apply costs depending on the services you opt into when extending beyond base capabilities.; Tags unique to tradingview-mcp: backtesting, crypto, forex, futures; tradingview-mcp ships Docker support for self-hosted deployment; When you need to access real-time market data from various asset classes like stocks, crypto, forex, and futures from global exchanges. ### When should I choose awesome-LLM-resources over tradingview-mcp? Choose awesome-LLM-resources over tradingview-mcp when License: awesome-LLM-resources is Apache-2.0, tradingview-mcp is MIT; Tags unique to awesome-LLM-resources: awesome-list, book, course, large language models; Also covers AI Agents, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training; - It's ideal when you seek an exhaustive and up-to-date compilation covering extensive knowledge points in LLM technologies. ### When should I avoid tradingview-mcp? Do not use if you are developing for a non-MCP compatible platform or if real-time data and complex technical analysis are not required. Avoid using this tool if your project focuses specifically on financial advice platforms that do not require integration with multiple assets types in real time. ### When should I avoid awesome-LLM-resources? - Avoid using this resource if you specifically need detailed step-by-step guides or hands-on tutorials that focus deeply on a single technology rather than broad coverage. - It might not be the best choice when you are looking for resources in languages other than English, especially given its extensive English content. ### Is tradingview-mcp or awesome-LLM-resources more popular on GitHub? awesome-LLM-resources has more GitHub stars (8,845 vs 4,229). Stars measure visibility, not whether either tool fits your constraints. ### Are tradingview-mcp and awesome-LLM-resources open source? Yes - both are open-source projects on GitHub (tradingview-mcp: MIT, awesome-LLM-resources: Apache-2.0). ### Where can I find alternatives to tradingview-mcp or awesome-LLM-resources? GraphCanon lists graph-backed alternatives at [tradingview-mcp alternatives](/tools/atilaahmettaner-tradingview-mcp/alternatives) and [awesome-LLM-resources alternatives](/tools/wangrongsheng-awesome-llm-resources/alternatives) ([tradingview-mcp markdown twin](/tools/atilaahmettaner-tradingview-mcp/alternatives.md), [awesome-LLM-resources markdown twin](/tools/wangrongsheng-awesome-llm-resources/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/atilaahmettaner-tradingview-mcp-vs-wangrongsheng-awesome-llm-resources.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, tradingview-mcp or awesome-LLM-resources? tradingview-mcp: Very active. awesome-LLM-resources: Very active. 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 tradingview-mcp and awesome-LLM-resources? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [tradingview-mcp trust report](/tools/atilaahmettaner-tradingview-mcp/trust); [awesome-LLM-resources trust report](/tools/wangrongsheng-awesome-llm-resources/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=atilaahmettaner-tradingview-mcp`](/api/graphcanon/graph?tool=atilaahmettaner-tradingview-mcp) - 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/_