New Tools for Building Agents

1. openai-python

   1 84 30,871 9.5 Python

   The official Python library for the OpenAI API

   

   If you want to get an idea for the changes, here's a giant commit where they updated ALL of the Python library examples in one go from the old chat completions to the new resources APIs: https://github.com/openai/openai-python/commit/2954945ecc185...

2. SaaSHub

   www.saashub.com featured

   SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives

   

3. mcpx-openai-node

   2 1 16 7.4 TypeScript

   OpenAI node support for MCPX

   

   not implementing doesn't mean its not supported https://github.com/dylibso/mcpx-openai-node (this is for mcp.run tool calling with OpenAI models, not generic)

   but yes, it's the strongest anti-developer move to not directly support MCP. not surprised given OpenAI generally. but would be a very nice addition!

4. mindroot

   3 6 94 9.3 Python

   AI agent web app platform

   

   The Agents SDK they linked to comes up 404.

   BTW I have something somewhat similar to some of this like responses and File Search in MindRoot by using the task API: https://github.com/runvnc/mindroot/blob/main/api.md

   Which could be combined with the query_kb tool from the mr_kb plugin (in my mr_kb repo) which is actually probably better than File Search because it allows searching multiple KBs.

   Anyway, if anyone wants to help with my program, create a plugin on PR, or anything, feel free to connect on GitHub, email or Discord/Telegram (runvnc). I could use some help or any kind of interaction from any software developer on the planet.

5. aiide

   4 5 64 7.5 Python

   Pragmatic framework to build LLM Copilots

   

   I have built myself a much simpler and powerful version of the responses API and it works with all LLM providers.

   https://github.com/Anilturaga/aiide

6. pydantic-ai

   5 47 17,517 9.9 Python

   AI Agent Framework, the Pydantic way

   

7. l1m

   6 2 55 9.2 TypeScript

   The easiest way to get structured data from unstructured text or images using LLMs. No prompt engineering, no chat history, just a simple API to extract structured JSON from text or images.

   

8. smolagents

   7 11 27,712 9.1 Python

   🤗 smolagents: a barebones library for agents that think in code.

   

9. openai-assistants-quickstart

   8 1 1,963 4.2 TypeScript

   OpenAI Assistants API quickstart with Next.js.

   

   If Responses is replacing Assistants, is there a quickstart template available—similar to the one you had for Assistants?

   https://github.com/openai/openai-assistants-quickstart

10. open-interpreter

    9 36 63,811 6.9 Python

    A natural language interface for computers

    

11. IDEA

    10 1 7 9.5 Python

    The Intelligent Data Exploring Assistant (IDEA) helps users efficiently explore and visualize datasets, specializing in geophysical data like sea levels. IDEA was developed at the University of Hawaii Sea Level Center for the Station Explorer Assistant (SEA) and other science applications. (by uhsealevelcenter)

    

12. awesome-ai-agents

    11 1 1,398 4.1 Python

    Awesome list of 300+ agentic AI resources (by slavakurilyak)

    

    Here's a fairly comprehensive list:

    https://github.com/slavakurilyak/awesome-ai-agents

    CrewAI is the most popular VC-backed one, but two that I think are kind of interesting in the open source space are:

    https://github.com/i-am-bee/beeai-framework

    https://github.com/lastmile-ai/mcp-agent

    ... However I think the vast majority of "AI Agent" use-cases in practice right now are actually just workflows, and imo dify is great for those:

    https://github.com/langgenius/dify

13. beeai-framework

    12 6 3,280 9.7 Python

    Build production-ready AI agents in both Python and Typescript.

    

    Here's a fairly comprehensive list:

    https://github.com/slavakurilyak/awesome-ai-agents

    CrewAI is the most popular VC-backed one, but two that I think are kind of interesting in the open source space are:

    https://github.com/i-am-bee/beeai-framework

    https://github.com/lastmile-ai/mcp-agent

    ... However I think the vast majority of "AI Agent" use-cases in practice right now are actually just workflows, and imo dify is great for those:

    https://github.com/langgenius/dify

14. mcp-agent

    13 18 8,353 9.7 Python

    Build effective agents using Model Context Protocol and simple workflow patterns

    

    Here's a fairly comprehensive list:

    https://github.com/slavakurilyak/awesome-ai-agents

    CrewAI is the most popular VC-backed one, but two that I think are kind of interesting in the open source space are:

    https://github.com/i-am-bee/beeai-framework

    https://github.com/lastmile-ai/mcp-agent

    ... However I think the vast majority of "AI Agent" use-cases in practice right now are actually just workflows, and imo dify is great for those:

    https://github.com/langgenius/dify

15. dify

    14 46 143,689 10.0 TypeScript

    Production-ready platform for agentic workflow development.

    

    Here's a fairly comprehensive list:

    https://github.com/slavakurilyak/awesome-ai-agents

    CrewAI is the most popular VC-backed one, but two that I think are kind of interesting in the open source space are:

    https://github.com/i-am-bee/beeai-framework

    https://github.com/lastmile-ai/mcp-agent

    ... However I think the vast majority of "AI Agent" use-cases in practice right now are actually just workflows, and imo dify is great for those:

    https://github.com/langgenius/dify

16. quickstart-resources

    15 4 1,107 8.5 Go

    A repository of servers and clients from the Model Context Protocol tutorials

    

    I don't like it. I don't like the OpenAI API all that much either but at least it's lightweight. I think it would fit better on mcp.anthropic.com to go along with their email address mcp-support@anthropic.com at the bottom of https://modelcontextprotocol.io/

    I wish they'd done a smaller launch of it and gather feedback rather than announcing a supposed new standard which feels a lot like a wrapper.

    This here is atrocious https://github.com/modelcontextprotocol/quickstart-resources... It includes this mcp PyPI package which pulls in a bunch of other PyPI dependencies.

    Compare that to this get weather example: https://api-docs.deepseek.com/guides/function_calling/

17. servers

    16 398 86,733 9.8 TypeScript

    Model Context Protocol Servers

    

    I don't like it. I don't like the OpenAI API all that much either but at least it's lightweight. I think it would fit better on mcp.anthropic.com to go along with their email address mcp-support@anthropic.com at the bottom of https://modelcontextprotocol.io/

    I wish they'd done a smaller launch of it and gather feedback rather than announcing a supposed new standard which feels a lot like a wrapper.

    This here is atrocious https://github.com/modelcontextprotocol/quickstart-resources... It includes this mcp PyPI package which pulls in a bunch of other PyPI dependencies.

    Compare that to this get weather example: https://api-docs.deepseek.com/guides/function_calling/

18. agento6

    17 1 5 7.6 Python

    

    I was fortunate to get early access to the new Agent SDK and APIs that OpenAI dropped today and made an open source project to show some of the capabilities [1]. If you are using any of the other agent frameworks like LangGraph/LangChain, AutoGen, Crew, etc I definitely suggest giving this agent SDK a spin.

    To ease into it, I added the entire SDK with examples and full documentation as a single text file in my repo [2] so you can quickly get up to speed be adding it to a prompt and just asking about it or getting some quick start code to play around with.

    The code in my repo is very modular so you can try implementing any module using one of the other frameworks to do a head-to-head.

    Here’s a blog post with some more thoughts on this SDK [3] and some if its major capabilities.

    I’m liking it. A lot!

    [1] https://github.com/dazzaji/agento6

    [2] https://raw.githubusercontent.com/dazzaji/agento6/refs/heads...

    [3] https://www.dazzagreenwood.com/p/unleashing-creativity-with-...

19. opik-mcp

    18 1 208 9.2 Python

    Model Context Protocol (MCP) implementation for Opik enabling seamless IDE integration and unified access to prompts, projects, traces, and metrics.

    

    100% but this is not the same thing, nor is this going to replace the agent SDK (or visa versa). Agents will always need some form of communication protocol, if we look at the world and agentic frameworks its a sea of logos and without some forms of open standards this would be hard.

    I'm currently at Comet and I have personally worked on MCP implementations AND have made some contributions to Agent SDK in the form of a native integration and improvement to test suite.

    - https://github.com/comet-ml/opik-mcp

    - https://github.com/openai/openai-agents-python/pull/91

    I think the key to what OpenAI is pushing towards is simplicity for developers through very easy to use components. I won't comment on the strategy or pricing etc, but on first glance as a developer the simple modular approach and lack of bloat in their SDK is refreshing.

    Kudos to the team and people working on the edge to innovate and think differently in an already crowded and shifting landscape.

20. openai-agents-python

    19 21 26,925 9.9 Python

    A lightweight, powerful framework for multi-agent workflows

    

    100% but this is not the same thing, nor is this going to replace the agent SDK (or visa versa). Agents will always need some form of communication protocol, if we look at the world and agentic frameworks its a sea of logos and without some forms of open standards this would be hard.

    I'm currently at Comet and I have personally worked on MCP implementations AND have made some contributions to Agent SDK in the form of a native integration and improvement to test suite.

    - https://github.com/comet-ml/opik-mcp

    - https://github.com/openai/openai-agents-python/pull/91

    I think the key to what OpenAI is pushing towards is simplicity for developers through very easy to use components. I won't comment on the strategy or pricing etc, but on first glance as a developer the simple modular approach and lack of bloat in their SDK is refreshing.

    Kudos to the team and people working on the edge to innovate and think differently in an already crowded and shifting landscape.

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