gpt2099

A Nushell scriptable
MCP client
with editable context threads
stored in cross.stream

Features

- Consistent API Across Models: Connect to Anthropic, Cerebras, Cohere, Gemini, and OpenAI
through a single, simple interface. (Add providers easily.)
- Persistent, Editable Conversations:
Conversation threads are
saved across sessions. Review, edit, and control your own context window — no black-box history.
- Flexible Tool Integration: Connect to MCP servers to extend functionality. gpt2099 already
rivals Claude Code for local file
editing, but with full provider independence and deeper flexibility.
- Document Support: Upload and reference documents (PDFs, images, text files) directly in
conversations with automatic content-type detection and optional caching.

Built on cross.stream for event-driven processing, gpt2099
brings modern AI directly into your Nushell workflow — fully scriptable, fully inspectable, all in
the terminal.

https://github.com/user-attachments/assets/1254aaa1-2ca2-46b5-96e8-b5e466c735bd

<small><i>"lady on the track" provided by mobygratis</i><small>

Getting started

Step 1.

First, install and configure cross.stream. Once set up, you'll
have the full cross.stream ecosystem of tools for editing and
working with your context windows.

- https://cablehead.github.io/xs/getting-started/installation/

After this step you should be able to run:

"as easy as" | .append abc123
.last abc123 | .cas

Step 2.

It really is easy from here.

overlay use -pr ./gpt

Step 3.

Initialize the cross.stream command that performs the actual LLM call. This appends the command to
your event stream so later gpt invocations can use it:

gpt init

Step 4.

Enable your preferred provider. This stores the API key for later use:

gpt provider enable

Step 5.

Set up a milli alias for a lightweight model (try OpenAI's gpt-4.1-mini or Anthropic's
claude-3-5-haiku-20241022):

gpt provider ptr milli --set

Step 6.

Give it a spin:

"hola" | gpt -p milli

Documentation

- Commands Reference - Complete command syntax and options
- How-To Guides - Task-oriented workflows:
- Configure Providers - Set up AI providers and model
aliases
- Work with Documents - Register and use documents in
conversations
- Manage Conversations - Threading, bookmarking, and
continuation
- Use MCP Servers - Extend functionality with external tools
- Generate Code Context - Create structured context from
Git repositories

Reference Documentation

- Provider API - Technical specification for implementing
providers
- Schemas - Complete data structure reference for all gpt2099
schemas

FAQ

- Why does the name include 2099? What else would you call the future?

Original intro

This is how the project looked, 4 hours into its inception:

https://github.com/user-attachments/assets/768cc655-a892-47cc-bf64-8b5f61c41f35