About Gpt2099.nu
Gpt2099.nu is an MCP server published by cablehead in the AI category: a Nushell cross.stream extension to interact with LLMs and MCP servers.
The repository has 26 stars and 4 forks, with the last commit 7 months ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues before depending on it in production.
Install
git clone https://github.com/cablehead/gpt2099.nuThis server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.
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Static checks derived from the repository 14 hours ago. Heuristics on the source, not an audit.
- ✓README presentThe repository ships documentation.
- !License declaredNo license file. Legally you have no right to use it in a product.
- ✓Tests presentA test suite exists in the repository.
- ✓Dependencies pinnedA lockfile pins dependency versions.
- ✓No dynamic code executionSource scan found no eval, dynamic Function, or shell execution.
- !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.
README
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.
gpt2099already 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
"lady on the track" provided by mobygratis
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.
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
README fetched from the repository 14 hours ago. The original is authoritative.