DSPy intersects both in the MCP → DSPy and DSPy → MCP directions.

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https://twitter.com/aalberici/status/1985297677978861890

In this snippet, we see how we are creating an MCP server which exposes one tool, the research_notion tool, which is itself a DSPy AI agent calling the Notion MCP server as tools.

Honestly, me too.

This morning, I had Claude Code setting up stuff on my server and my client by itself, in one session, on both machines! That is simply amazing.

In the last 3 days, I have created 2 new, genuinely useful Python libraries with Claude Code. One is for easily adding text to the GNOME status bar, and another is for doing speech-to-text very simply. Codex/Claude Code-like tools excel at making libraries, so I am building MAIVI (My AI Voice Assistant) one library at a time. In the end, the code for MAIVI will be a single file where I import all those libraries and simply connect them together.

I made both libraries through the CLI. To look at files (sometimes), I am back to using a simple text editor—no need for VSCode when you don't change the code yourself anymore.

It's all about system architecture, design, and product now.

link to projects below. github.com/maximerivest/p…

Using AI as functions should not be hard.

FunctAI will be very nice. I might graduate it from experiment to project.

All examples work on my machine. Just needs to polish and push :) 🧵

Today, I woke up and I thought:

Wouldn't it be nice if I could use an llm for autocomplete instead of small dumb copilot/cursor type models?

Speed + Quality of Kimi-K2 on Groq makes it possible!

So, in 1 hour, I vibe coded a vscode extension, just before starting my day at work. Here is how 🧵

ps: I only took about ~5 prompts. 1. For the first prompt, I opened a fresh conversation in with all 4: o3-pro, gemini 2.5-pro, opus 4 extended thinking and grok 4-heavy.

the prompt was:

I want to be able to press a keyboarb shortcut in vscode and the whole content of my current code (plus the other opened tab), plus instructions to a open ai end point would be sent to them and the ai would automcomplete and add code for the 'section'. the ai will decide what section its confident to predict how should we do it?

I just released the first version of Attachments CLI 🖇️!

$ uv tool install attachments

$ attachments ~/my_repo/ --clipboard --glob '**/*.py'

Attachments is a Python library (and cli!) with a simple mission: to be your universal LLM funnel.

path -> clipboard

in 1 line This line below gets me all the .ts files and their content that are found in the attjsplay directory AND a tree of the directory.

att ~/Projects/maximumplay/src/attjsplay/ --clipboard --glob '*.ts' --mode structure --files

I needed to understand exactly what DSPy was sending to the LLMs on my behalf before I could trust it.

If you are like me, just run adapter.format yourself (the default is ChatAdapter) and you will see exactly what is happening. If you do not like the result, implement your own. DSPy is modular and fully supports that.

See the thread for how it renders. So the ChatAdapter would do that: