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
Our recent integration shipped on day 1:
- https://www.comet.com/docs/opik/tracing/integrations/openai_...
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.
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!
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. And for some reason they say "we recommend uv". How is that related to just setting up a tool for an AI to use?
Compare that to this get weather example: https://api-docs.deepseek.com/guides/function_calling/
It makes me not want to use Claude/Anthropic.
The pyproject.toml in the Model Context Protocol example is just showing the new, "best" way to distribute and install Python projects and dependencies. If you haven't used uv before, it makes working with Python projects substantially better.
The Model Context Protocol server lets the model autonomously use the tool and incorporate its result. It's a much cleaner (imo obviously) separation of tool definition and execution.
> [Q] Does the Agents SDK support MCP connections? So can we easily give certain agents tools via MCP client server connections?
> [A] You're able to define any tools you want, so you could implement MCP tools via function calling
in short, we need to do some plumbing work.
relevant issue in the repo: https://github.com/openai/openai-agents-python/issues/23
Querying schema from prompt is great, but also being able to say "I cannot see the Create Project button on the projects list screen. Use MCP to see if user with email me@domain.com has the appropriate permissions" is just amazing.
This SDK is trying to provide a bunch of code for implementing specific agent codebases. There are a bunch of open source ones already, so this is OpenAI throwing their hat in the ring.
IMO this OpenAI release is kind of ecosystem-hostile in that they are directly competing with their users, in the same way that the GPT apps were.
https://github.com/slavakurilyak/awesome-ai-agents
CrewAI is a 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
[edit] worth mentioning [langfuse](https://github.com/langfuse/langfuse), which is more like a platform that addresses the observability/evals/prompt management piece of the puzzle as opposed to a full-on "agent framework". In practice I have not yet run into a case where I needed something like what OpenAI just released, nor crewAI etc (despite it feeling like those cases may be coming)
I just realized BeeAI is IBM's project: https://www.ibm.com/think/news/beeai-open-source-multiagent
I also see there's https://ai.pydantic.dev/ but it lacks MCP support. Finally, the MCP site maintains a nice client list:
https://modelcontextprotocol.io/clients#feature-support-matr...
It does not specify how “agentic” systems interact with each other. Depending on what you mean there.