Comparison
tradingview-mcp vs awesome-LLM-resources
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 is a curated list of resources related to large language models, covering a wide range of topics from multimodal generation to model training and inference.
Markdown twin · tradingview-mcp alternatives · awesome-LLM-resources alternatives
GraphCanon updated Sep 20, 2026
10views this month
vs
Trust & integrity
| Signal | tradingview-mcp | awesome-LLM-resources |
|---|---|---|
| Maintenance | Active (18d since push) As of Sep 20, 2026 · github_public_v1 | Very active (3d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 20, 2026 · github_public_v1 | Not a fork · Personal account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Sep 18, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- tradingview-mcp
- Real-time market data and technical analysis for financial markets
- awesome-LLM-resources
- Summary of the world's best LLM resources.
Stars
- tradingview-mcp
- 4.6k
- awesome-LLM-resources
- 9.0k
Forks
- tradingview-mcp
- 960
- awesome-LLM-resources
- 993
Open issues
- tradingview-mcp
- 16
- awesome-LLM-resources
- 40
Language
- tradingview-mcp
- Python
- awesome-LLM-resources
- -
Adopt for
- tradingview-mcp
- 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
- awesome-LLM-resources is a curated list of resources related to large language models, covering a wide range of topics from multimodal generation to model training and inference.
Persona
- tradingview-mcp
- -
- awesome-LLM-resources
- -
Runtime
- tradingview-mcp
- -
- awesome-LLM-resources
- -
License
- tradingview-mcp
- MIT
- awesome-LLM-resources
- The repository is licensed under Apache-2.0, allowing for free use, modification, and distribution.
Last pushed
- tradingview-mcp
- Sep 1, 2026
- awesome-LLM-resources
- Sep 14, 2026
Categories
- tradingview-mcp
- Developer Tools
- awesome-LLM-resources
- AI Agents, Computer Vision, Data & Retrieval, Developer Tools, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training
Trust and health
Maintenance
- tradingview-mcp
- Active (82%)
- awesome-LLM-resources
- Very active (96%)
Days since push
- tradingview-mcp
- 18d
- awesome-LLM-resources
- 3d
Open issues (now)
- tradingview-mcp
- 16
- awesome-LLM-resources
- 40
Stars delta
- tradingview-mcp
- +913 (30d)
- awesome-LLM-resources
- +123 (30d)
Open issues delta
- tradingview-mcp
- +9 (30d)
- awesome-LLM-resources
- +17 (30d)
Full report
- tradingview-mcp
- Trust report
- awesome-LLM-resources
- Trust report
Shared compatibility
- ChatGPT · tradingview-mcp: Works with ChatGPT · awesome-LLM-resources: Works with ChatGPT
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.
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.
Choose awesome-LLM-resources if…
- License: awesome-LLM-resources is Apache-2.0, tradingview-mcp is MIT.
- Pricing: The repository itself is free to use, but some linked resources may require payment or have associated costs..
- Requirements: The repository does not specify any technical requirements for accessing its content..
- Tags unique to awesome-LLM-resources: awesome-list, book, course, large-language-models.
- Also covers AI Agents, Computer Vision, Data & Retrieval, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training.
- When you need a comprehensive list of resources for large language models, including multimodal generation, agents, programming assistance, and more.
When NOT to use awesome-LLM-resources
- If you are looking for a tool that provides direct access to LLM APIs or services, as this repository is a list of resources rather than a service provider.
- When you need real-time support or a community forum for troubleshooting LLM-related issues, as this repository is a static list of resources without interactive support.
Explore
tradingview-mcp trust report →awesome-LLM-resources trust report →Developer Tools category →AI Agents category →Computer Vision category →Data & Retrieval category →Evaluation & Observability category →Inference & Serving category →LLM Frameworks category →Model Training category →All comparisonsStack workflowsTrending tools
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (atilaahmettaner/tradingview-mcp) · observed Sep 20, 2026
- GitHub forks (atilaahmettaner/tradingview-mcp) · observed Sep 20, 2026
- Last push (atilaahmettaner/tradingview-mcp) · observed Sep 1, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (WangRongsheng/awesome-LLM-resources) · observed Sep 20, 2026
- GitHub forks (WangRongsheng/awesome-LLM-resources) · observed Sep 20, 2026
- Last push (WangRongsheng/awesome-LLM-resources) · observed Sep 14, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
GitHub stars on cards: tradingview-mcp 4.6k · awesome-LLM-resources 9.0k (synced Sep 20, 2026).
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; Pricing: The repository itself is free to use, but some linked resources may require payment or have associated costs.; Requirements: The repository does not specify any technical requirements for accessing its content.; Tags unique to awesome-LLM-resources: awesome-list, book, course, large-language-models; Also covers AI Agents, Computer Vision, Data & Retrieval, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training; When you need a comprehensive list of resources for large language models, including multimodal generation, agents, programming assistance, and more.
- 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?
- If you are looking for a tool that provides direct access to LLM APIs or services, as this repository is a list of resources rather than a service provider. When you need real-time support or a community forum for troubleshooting LLM-related issues, as this repository is a static list of resources without interactive support.
- Is tradingview-mcp or awesome-LLM-resources more popular on GitHub?
- awesome-LLM-resources has more GitHub stars (8,968 vs 4,592). 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 and awesome-LLM-resources alternatives (tradingview-mcp markdown twin, awesome-LLM-resources markdown twin), 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 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: 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; awesome-LLM-resources trust report.