├── databricks.md ├── coding_assistant.md ├── code-assistants.md ├── aws.md ├── vibe-coding.md ├── anthropic.md ├── June2025.md ├── agents.md ├── LICENSE ├── mcp.md ├── prompt_engineering.md ├── .gitignore └── README.md /databricks.md: -------------------------------------------------------------------------------- 1 | [Using uv as Dependency Manager for Databricks Asset Bundles](https://youtu.be/lzdDE6TzRJs?si=Zqkyqce5SuGfAfqm) 2 | -------------------------------------------------------------------------------- /coding_assistant.md: -------------------------------------------------------------------------------- 1 | # This file holds information related to different coding assistants 2 | 3 | Claude Code from Anthropic -> https://anthropic.skilljar.com/claude-code-in-action 4 | -------------------------------------------------------------------------------- /code-assistants.md: -------------------------------------------------------------------------------- 1 | This file holds the widely used Coding assistants link. 2 | 3 | **Amazon Q** 4 | - https://docs.aws.amazon.com/amazonq/latest/qdeveloper-ug/command-line-installing.html 5 | -------------------------------------------------------------------------------- /aws.md: -------------------------------------------------------------------------------- 1 | Good intro to Agentcore -> https://dev.to/aws-heroes/amazon-bedrock-agentcore-runtime-part-1-introduction-e5i 2 | Agentcore Latest doc -> https://aws.amazon.com/blogs/machine-learning/iterate-faster-with-amazon-bedrock-agentcore-runtime-direct-code-deployment/ 3 | Code for Agentcore examples -> https://github.com/VincentV89/agentic-ai-with-mcp-and-strands 4 | -------------------------------------------------------------------------------- /vibe-coding.md: -------------------------------------------------------------------------------- 1 | This file holds links for docs or courses related to vibe coding. 2 | 3 | **Replit** 4 | - https://learn.deeplearning.ai/courses/vibe-coding-101-with-replit/information 5 | - Some tips in vibe-coding 6 | - Be precise 7 | - Be Well organized 8 | - Be patient 9 | - Remember, tooling and communicating with AI is the key for vibe-coding. That's all you need 😉 10 | -------------------------------------------------------------------------------- /anthropic.md: -------------------------------------------------------------------------------- 1 | This file holds important links related to Anthropic. 2 | --- 3 | - https://github.com/anthropics/claude-quickstarts/tree/main/computer-use-demo 4 | - https://learn.deeplearning.ai/courses/building-toward-computer-use-with-anthropic/information 5 | - https://github.com/anthropics/skills.git 6 | 7 | image 8 | source for this screenshot: https://youtu.be/m-5DjcgFmfQ?si=AmTFvrR5QSDCrO9S 9 | -------------------------------------------------------------------------------- /June2025.md: -------------------------------------------------------------------------------- 1 | ### Important links 2 | - [OpenAPI Tools](https://openapitools.com/) -> OpenAPI Specs to MCP Servers Instantly 3 | - [LangFlow](https://www.langflow.org/) -> Langflow is a powerful tool to build and deploy AI agents and MCP servers. It comes with batteries included and supports all major LLMs, vector databases and a growing library of AI tools. 4 | - [LlamaDeploy](https://docs.llamaindex.ai/en/stable/module_guides/llama_deploy/) -> LlamaDeploy (formerly llama-agents) is an async-first framework for deploying, scaling, and productionizing agentic multi-service systems based on workflows from llama_index. 5 | -------------------------------------------------------------------------------- /agents.md: -------------------------------------------------------------------------------- 1 | This page holds different frameworks to create agents. 2 | --- 3 | **CrewAI** 4 | - https://www.crewai.com/ ( Framework and Platform ) 5 | - https://learn.deeplearning.ai/courses/multi-ai-agent-systems-with-crewai/information 6 | image 7 | - Different agent for different tasks, this also provide us to use diff LLMs for different Agents. 8 | image 9 | - Agent, task and Crew ( 3 components ) 10 | - Tasks are sequential by default 11 | image 12 | 13 | 14 | 15 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2024 Sudarshan Koirala 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /mcp.md: -------------------------------------------------------------------------------- 1 | # All about Model Context Protocol (MCP) 2 | 3 | Github Repo -> https://github.com/modelcontextprotocol 4 | 5 | Anthropic Courses in MCP 6 | - https://anthropic.skilljar.com/introduction-to-model-context-protocol 7 | - https://anthropic.skilljar.com/model-context-protocol-advanced-topics 8 | 9 | ---- 10 | 11 | - [All about MCP](https://modelcontextprotocol.io/introduction) 12 | - [MCP announcement from Claude](https://www.anthropic.com/news/model-context-protocol) 13 | - [Claude for Desktop](https://claude.ai/download) 14 | - [Claude code](https://docs.anthropic.com/en/docs/agents-and-tools/claude-code/overview) 15 | - [Good blog post about Intro to MCP](https://blog.aitoolhouse.com/introduction-to-the-model-context-protocol-mcp-a-developers-guide-to-the-mcp-for-smarter-ai-assistants/) 16 | - [Offical Github MCP Servers](https://github.com/modelcontextprotocol/servers) 17 | - [Awesome MCP Servers](https://github.com/punkpeye/awesome-mcp-servers) 18 | - [What is MCP, and Why Is Everyone Suddenly Talking About It](https://huggingface.co/blog/Kseniase/mcp) 19 | - [MCP server Directory](https://www.pulsemcp.com/servers) 20 | - [Awesome MCP Servers and Clients](https://mcp.so/) 21 | - [FastMCP](https://gofastmcp.com/getting-started/welcome) 22 | - [What is Model Context Protocol (MCP)? How it simplifies AI integrations compared to APIs](https://norahsakal.com/blog/mcp-vs-api-model-context-protocol-explained/#when-are-traditional-apis-better) 23 | - [Open Source MCP Servers, Glama.ai](https://glama.ai/mcp/servers) 24 | - [MCP Inspector, Visual testing tool for MCP servers](https://github.com/modelcontextprotocol/inspector) 25 | - [AWS MCP server webpage](https://awslabs.github.io/mcp/) 26 | -------------------------------------------------------------------------------- /prompt_engineering.md: -------------------------------------------------------------------------------- 1 | # This page is for mainly focused on resources related to Prompt Engineering 2 | 3 | Prompt Engineering guide from Anthropics -> https://github.com/anthropics/prompt-eng-interactive-tutorial 4 | 5 | 6 | ## Top-Tier Official Resources for Prompting 7 | 8 | https://learn.microsoft.com/en-us/training/paths/craft-effective-prompts-copilot-microsoft-365/ 9 | https://support.microsoft.com/en-us/topic/learn-about-copilot-prompts-f6c3b467-f07c-4db1-ae54-ffac96184dd5 10 | https://learn.microsoft.com/en-us/ai-builder/prompt-library 11 | https://help.openai.com/en/articles/6654000-best-practices-for-prompt-engineering-with-the-openai-api 12 | https://docs.anthropic.com/en/docs/build-with-claude/prompt-engineering/overview 13 | 14 | ## Interactive Training Platforms 15 | 16 | https://grow.google/prompting-essentials/ 17 | https://www.coursera.org/learn/generative-ai-prompt-engineering-for-everyone 18 | https://learnprompting.org/docs/introduction 19 | 20 | ## Specialized Business Tools 21 | 22 | https://dataplatform.cloud.ibm.com/docs/content/wsj/analyze-data/fm-prompt-lab.html?context=wx 23 | https://netskill.com/course/tech-development/development-tools/prompt-engineering/ 24 | https://www.happy.co.uk/it-courses/courses-and-training/the-art-of-ai-prompt-engineering/ 25 | 26 | ## Frameworks & Methodologies 27 | 28 | https://medium.com/@thomasczerny/co-star-framework-for-prompt-structuring-7f9a8c221224 29 | https://digitalrepository.unm.edu/ulls_fsp/211/ 30 | https://www.factspan.com/blogs/advanced-prompt-engineering-with-chatgpt-frameworks/ 31 | 32 | ## Implementation & Assessment Tools 33 | 34 | https://github.com/promptslab/Awesome-Prompt-Engineering 35 | https://promptengineering.org/build-your-personalized-prompt-library-for-generative-ai/ 36 | https://teamai.com/blog/prompt-libraries/building-a-prompt-library-for-my-team/ 37 | 38 | ## Advanced Corporate Applications 39 | 40 | https://lanternstudios.com/insights/blog/prompting-guide-for-copilot-for-microsoft-365/ 41 | https://regoconsulting.com/mastering-microsoft-copilot-best-practices-for-prompt-engineering-in-microsoft-365/ 42 | https://www.promptingguide.ai/ 43 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | share/python-wheels/ 24 | *.egg-info/ 25 | .installed.cfg 26 | *.egg 27 | MANIFEST 28 | 29 | # PyInstaller 30 | # Usually these files are written by a python script from a template 31 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 32 | *.manifest 33 | *.spec 34 | 35 | # Installer logs 36 | pip-log.txt 37 | pip-delete-this-directory.txt 38 | 39 | # Unit test / coverage reports 40 | htmlcov/ 41 | .tox/ 42 | .nox/ 43 | .coverage 44 | .coverage.* 45 | .cache 46 | nosetests.xml 47 | coverage.xml 48 | *.cover 49 | *.py,cover 50 | .hypothesis/ 51 | .pytest_cache/ 52 | cover/ 53 | 54 | # Translations 55 | *.mo 56 | *.pot 57 | 58 | # Django stuff: 59 | *.log 60 | local_settings.py 61 | db.sqlite3 62 | db.sqlite3-journal 63 | 64 | # Flask stuff: 65 | instance/ 66 | .webassets-cache 67 | 68 | # Scrapy stuff: 69 | .scrapy 70 | 71 | # Sphinx documentation 72 | docs/_build/ 73 | 74 | # PyBuilder 75 | .pybuilder/ 76 | target/ 77 | 78 | # Jupyter Notebook 79 | .ipynb_checkpoints 80 | 81 | # IPython 82 | profile_default/ 83 | ipython_config.py 84 | 85 | # pyenv 86 | # For a library or package, you might want to ignore these files since the code is 87 | # intended to run in multiple environments; otherwise, check them in: 88 | # .python-version 89 | 90 | # pipenv 91 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 92 | # However, in case of collaboration, if having platform-specific dependencies or dependencies 93 | # having no cross-platform support, pipenv may install dependencies that don't work, or not 94 | # install all needed dependencies. 95 | #Pipfile.lock 96 | 97 | # poetry 98 | # Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. 99 | # This is especially recommended for binary packages to ensure reproducibility, and is more 100 | # commonly ignored for libraries. 101 | # https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control 102 | #poetry.lock 103 | 104 | # pdm 105 | # Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. 106 | #pdm.lock 107 | # pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it 108 | # in version control. 109 | # https://pdm.fming.dev/#use-with-ide 110 | .pdm.toml 111 | 112 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm 113 | __pypackages__/ 114 | 115 | # Celery stuff 116 | celerybeat-schedule 117 | celerybeat.pid 118 | 119 | # SageMath parsed files 120 | *.sage.py 121 | 122 | # Environments 123 | .env 124 | .venv 125 | env/ 126 | venv/ 127 | ENV/ 128 | env.bak/ 129 | venv.bak/ 130 | 131 | # Spyder project settings 132 | .spyderproject 133 | .spyproject 134 | 135 | # Rope project settings 136 | .ropeproject 137 | 138 | # mkdocs documentation 139 | /site 140 | 141 | # mypy 142 | .mypy_cache/ 143 | .dmypy.json 144 | dmypy.json 145 | 146 | # Pyre type checker 147 | .pyre/ 148 | 149 | # pytype static type analyzer 150 | .pytype/ 151 | 152 | # Cython debug symbols 153 | cython_debug/ 154 | 155 | # PyCharm 156 | # JetBrains specific template is maintained in a separate JetBrains.gitignore that can 157 | # be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore 158 | # and can be added to the global gitignore or merged into this file. For a more nuclear 159 | # option (not recommended) you can uncomment the following to ignore the entire idea folder. 160 | #.idea/ 161 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | Hello 👋, this is live-in document, might be updated as you are reading this 😎🧠 2 | Update June 2025: Decided to create a file for each month to organize the resources. 3 | 4 | # Resources to get started with Large Language Models (LLMs) 5 | 6 | ### [My Youtube Channel](https://www.youtube.com/@datasciencebasics) 7 | 8 | - To be clear, this is not a roadmap for `getting started` with LLMs. 9 | - I am not covering the books you should study, university studies, certificates, etc. 10 | - I assume you have basic understanding of NLP stuffs, programming knowledge ( mainly Python and Maths ). 11 | - You might argue, why Maths as everything is automated. Well, well, behind the scene, almost everything is Maths 🧠 ) 12 | - Calculus, Probability, Linear Algebra 13 | - You need to know, Lets say what is matrix, how dot product works, etc etc. 14 | - These are some of the resources which I suggest you to get started. 15 | - After knowing the basics and how things work, it's upon you, what to do ( Or lets say if it's your cup of tea / coffee or not ) 16 | > Remember one thing, using LLMs and implementing are two different things, you need not necessary know how to implement, but you need to know how to use it in right way. 17 | 18 | ## Videos in Neural Networks and LLMs 19 | - [A Hacker's Guide to Language Models](https://youtu.be/jkrNMKz9pWU?si=-PLRJrXB80E27Q_m) by Jeremy Howard. 20 | - [[1hr Talk] Intro to Large Language Models](https://youtu.be/zjkBMFhNj_g?si=hw-BLphS85ORXL7i) by Andrej Karpathy. 21 | - [Neural Networks: Zero to Hero](https://youtube.com/playlist?list=PLAqhIrjkxbuWI23v9cThsA9GvCAUhRvKZ&si=eTu3ESyFvq7JFdPD) by Andrej Karpathy. 22 | - [Building RAG from scratch Using Python, LangChain and OpenAI API](https://youtu.be/BrsocJb-fAo?si=13-fYpjIBp9rmdhw) by Santiago. 23 | --- 24 | 25 | ## Free Courses 26 | - [fast.ai courses](https://www.fast.ai/) --> `Optional but highly recommended` 27 | - [DeepLearning.AI short courses](https://www.deeplearning.ai/short-courses/) -- My request, try to complete all this free short courses. 28 | - [DeepLearning.AI Specializations](https://www.deeplearning.ai/courses/) 29 | --- 30 | 31 | ## Prompt Engineering 32 | - [Prompt Engineering Guide](https://www.promptingguide.ai/) 33 | - [OpenAI doc about Prompt Engineering](https://platform.openai.com/docs/guides/prompt-engineering) 34 | - [Strategies to harness the power of LLMs](https://towardsdatascience.com/how-i-won-singapores-gpt-4-prompt-engineering-competition-34c195a93d41) 35 | -[Prompt Engineering](https://github.com/NirDiamant/Prompt_Engineering) 36 | - There is one from deeplearing.ai free short courses too about ChatGPT Prompt Engineering for Developers. 37 | - There are many courses, articles, videos about this topic, it needs constant learning and experimenting. 38 | --- 39 | 40 | ## Frameworks which I have explored untill now, there are many, you can give a try ( your world, your rules ) 41 | - [LangChain](https://www.langchain.com/) 42 | - [All you need to know about LangChain](https://youtu.be/EIejozA1W7I?si=rPBJnh7uEWVRa8ce) 43 | - [LlamaIndex](https://www.llamaindex.ai/) 44 | - [All you need to know about LlamaIndex](https://youtu.be/FbQowFipEP4?si=GIZI73RzJZy1B_cj) 45 | --- 46 | 47 | ### Google, Microsoft and AWS has their own courses ( you can pick the one where you want to start) 48 | ### OpenAI has really good [documentation](https://platform.openai.com/docs/introduction) and [Cookbook](https://cookbook.openai.com/) 49 | 50 | ## Youtube ( Free University ) 51 | - There is unlimited knoweledge you can grasp, try to find the best ones and follow them instead of jumping among videos. 52 | - Main thing is to understand things and try it yourself. Unless you try (practice youself), you won't learn. 53 | - I have videos on LLMs with playlist on langchain, chainlit and Llamaindex. Many LLMs videos to follow in 2024 54 | - [Langchain playlist](https://youtube.com/playlist?list=PLz-qytj7eIWVd1a5SsQ1dzOjVDHdgC1Ck&si=UsnrzCA1kUsYLtLe) 55 | - [LlamaIndex playlist](https://youtube.com/playlist?list=PLz-qytj7eIWWqLRAJh-Q_fuvs0qH739zz&si=ljn51QFH4qbFL3uz) 56 | --- 57 | 58 | > Main thing I want to highlight, practice practice and practice, take help with AI assistants 👇 59 | 60 | ## AI Assistants ( Remember, personal use or enterprise use ) 61 | - [Perplexity AI](https://perplexity.ai/pro?referral_code=YAWB6JNV) --> let's put this way, it's Google Search with LLMs with it. 62 | - [Perplexity Labs, For Open Source models](https://labs.perplexity.ai/) 63 | - [ChatGPT](https://chat.openai.com/) --> Based on your need, free or paid version. ( Team, Enterprise , etc) 64 | - [Bing Chat](https://www.bing.com/search?q=Bing+AI&showconv=1&FORM=hpcodx) , Bing Enterprise. 65 | - [Hugging Chat](https://huggingface.co/chat/) 66 | - [Le Chat Mistral](https://chat.mistral.ai) 67 | 68 | --- 69 | 70 | ## Make RAG work properly 71 | - First, think on tweeking basic stuffs 72 | - Cleaning document ( choose right parsing , eg. LlamaParse, Unstructured ) 73 | - Better Chunking strategies 74 | - Choosing right embeddings model 75 | - Choosing right Vectorstore 76 | - Passing parsing Instructions, Reranking 77 | - Choosing right Large Language Models 78 | 79 | Links to follow for better understanding. 80 | 81 | - [Chunk visualizer](https://huggingface.co/spaces/m-ric/chunk_visualizer) 82 | - [Tokenizer, from OpenAI](https://platform.openai.com/tokenizer) 83 | - [Huggingface Massive Text Embedding Benchmark (MTEB) Leaderboard](https://huggingface.co/spaces/mteb/leaderboard) 84 | - [What is a Vector Database & How Does it Work? Use Cases + Examples](https://www.pinecone.io/learn/vector-database/) 85 | - [Chunking Strategies for LLM Applications](https://www.pinecone.io/learn/chunking-strategies/) 86 | - [🤗 Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) 87 | - [🏆 LMSYS Chatbot Arena Leaderboard](https://chat.lmsys.org/) 88 | - [12 RAG Pain Points and Proposed Solutions](https://towardsdatascience.com/12-rag-pain-points-and-proposed-solutions-43709939a28c) 89 | - [Optimizing RAG with Hybrid Search & Reranking](https://superlinked.com/vectorhub/optimizing-rag-with-hybrid-search-and-reranking) 90 | - [Improving RAG performance with Knowledge Graphs](https://superlinked.com/vectorhub/improving-rag-performance-with-knowledge-graphs) 91 | - [Enhancing RAG with a Multi-Agent System](https://superlinked.com/vectorhub/enhancing-rag-with-a-multi-agent-system) 92 | 93 | ----- 94 | ## Important Links Updated ( 22 August 2024 ) 95 | - [Llama-3-Groq-Tool-Use Models](https://wow.groq.com/introducing-llama-3-groq-tool-use-models/) 96 | - [Berkeley Funciton Calling Leaderboard](https://gorilla.cs.berkeley.edu/leaderboard.html#leaderboard) 97 | - [Independent analysis of AI models and API providers](https://artificialanalysis.ai/) :pushpin: 98 | 99 | ---- 100 | ## Important Links Updated ( 02 September 2024 ) 101 | ### AWS 102 | - [Evaluating RAG applications with Amazon Bedrock knowledge base evaluation](https://aws.amazon.com/blogs/machine-learning/evaluating-rag-applications-with-amazon-bedrock-knowledge-base-evaluation/) 103 | - [AWS Samples](https://github.com/aws-samples) 104 | 105 | ---- 106 | - [LangChain Azure Integration](https://devblogs.microsoft.com/azure-sql/langchain-with-sqlvectorstore/) 107 | - [RAG vs Agentic RAG](https://www.analyticsvidhya.com/blog/2024/11/rag-vs-agentic-rag/) 108 | - [Comphrensive Guide in RAG Implementation](https://newsletter.armand.so/p/comprehensive-guide-rag-implementations) 109 | ---- 110 | 111 | ### RAG and Agents 112 | - [RAG_Techniques](https://github.com/NirDiamant/RAG_Techniques) 113 | - [GenAI Agents](https://github.com/NirDiamant/GenAI_Agents) 114 | 115 | ---- 116 | - [2024-AI-Timeline Huggingface Space](https://huggingface.co/spaces/reach-vb/2024-ai-timeline) 117 | - [The Rise of AI Engineer](https://www.latent.space/p/ai-engineer?utm_campaign=post&utm_medium=web) 118 | --- 119 | 120 | ### LLM Docs 121 | - [Anthropic Docs](https://docs.anthropic.com/en/home) 122 | - [OpenAI Docs](https://platform.openai.com/docs/overview) 123 | 124 | ### Model Context Protocol 125 | - [All about MCP](https://modelcontextprotocol.io/introduction) 126 | - [MCP announcement from Claude](https://www.anthropic.com/news/model-context-protocol) 127 | - [Claude for Desktop](https://claude.ai/download) 128 | - [Claude code](https://docs.anthropic.com/en/docs/agents-and-tools/claude-code/overview) 129 | - [Good blog post about Intro to MCP](https://blog.aitoolhouse.com/introduction-to-the-model-context-protocol-mcp-a-developers-guide-to-the-mcp-for-smarter-ai-assistants/) 130 | - [Offical Github MCP Servers](https://github.com/modelcontextprotocol/servers) 131 | - [Awesome MCP Servers](https://github.com/punkpeye/awesome-mcp-servers) 132 | - [What is MCP, and Why Is Everyone Suddenly Talking About It](https://huggingface.co/blog/Kseniase/mcp) 133 | - [MCP server Directory](https://www.pulsemcp.com/servers) 134 | - [Awesome MCP Servers and Clients](https://mcp.so/) 135 | - [FastMCP](https://gofastmcp.com/getting-started/welcome) 136 | - [What is Model Context Protocol (MCP)? How it simplifies AI integrations compared to APIs](https://norahsakal.com/blog/mcp-vs-api-model-context-protocol-explained/#when-are-traditional-apis-better) 137 | - [Open Source MCP Servers, Glama.ai](https://glama.ai/mcp/servers) 138 | - [MCP Inspector, Visual testing tool for MCP servers](https://github.com/modelcontextprotocol/inspector) 139 | 140 | ### Leaked System Prompts 141 | - [Leaked system prompts](https://github.com/jujumilk3/leaked-system-prompts) 142 | > Cheers !! 143 | Last Updated: February 2025 144 | --------------------------------------------------------------------------------