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## Why
Selected plugin metadata is stable, but MCP processes are live runtime
state. They need different lifetimes:
- the MCP extension caches manifest, MCP, and connector declarations for
each stable selected root;
- each model step projects that cached metadata through the roots that
resolved as ready for that exact step;
- the MCP manager is rebuilt only when that availability projection
changes.
This matches executor skills: both features consume the same resolved
step roots instead of inferring readiness from the turn's selected
environments.
## Behavior
```text
E1 not ready for this step
-> no E1 MCP servers or connectors
-> cached plugin metadata stays in ext/mcp
E1 becomes ready
-> reuse cached metadata
-> publish one MCP runtime containing E1 capabilities
same ready roots on the next step
-> reuse the exact runtime; no rediscovery and no MCP restart
resume
-> create new extension thread state and a new MCP runtime
```
All model-facing consumers use the same step snapshot:
```text
resolved selected roots
|
v
extension MCP/connector projection
|
v
{ MCP config, connector snapshot, MCP manager }
|
+-> advertise model tools
+-> build app/connector tools
+-> execute MCP calls
```
## Cache contract
The existing MCP extension owns a cache keyed by the full
`SelectedCapabilityRoot`:
```rust
let state = thread_store.get_or_init(SelectedExecutorPluginMcpState::default);
```
The cache lives with extension thread state. Environment availability
filters projection but does not invalidate metadata. Resume creates new
thread state. There is no file watcher or executor generation because
contents behind a stable environment/root are assumed stable.
## What changes
- Keeps executor plugin discovery and cached metadata in `ext/mcp`.
- Caches MCP and connector declarations together per selected root.
- Uses the step's already-resolved capability roots, including lazy
environments that are not turn environments.
- Reuses the current MCP runtime when the ready-root projection is
unchanged.
- Uses the same step MCP manager and connector snapshot for
model-visible tools and execution.
- Resolves direct thread-scoped MCP requests from the current
selected-root projection.
## Deliberately out of scope
- `app/list` remains based on the latest global host-plugin state; this
PR does not make its response or notifications thread-specific.
- `required = true` startup semantics do not apply to delayed executor
MCP activation.
- No filesystem/content invalidation.
- No transport-disconnect watcher.
- No executor generations or environment replacement semantics.
- No client sharing across complete manager replacements.
## Stack
1. Extension-owned World State sections.
2. Project executor skills through World State.
3. Pin one MCP runtime to each model step.
4. **This PR:** project selected MCP and connector state from
extension-owned metadata.
5. Integration coverage for selected capability availability and resume.
## Verification
-
`selected_plugin_servers_use_managed_requirements_for_the_selected_root_id`
- The stacked integration PR covers unavailable to ready activation,
unchanged-runtime reuse, skills, MCP tools, connector attribution, and
cold resume.
3095ea9c3d
·
2026-06-26 01:36:44 +01:00
7,867 Commits
Codex CLI is a coding agent from OpenAI that runs locally on your computer.
If you want Codex in your code editor (VS Code, Cursor, Windsurf), install in your IDE.
If you want the desktop app experience, run
codex app or visit the Codex App page.
If you are looking for the cloud-based agent from OpenAI, Codex Web, go to chatgpt.com/codex.
Quickstart
Installing and running Codex CLI
Run the following on Mac or Linux to install Codex CLI:
curl -fsSL https://chatgpt.com/codex/install.sh | sh
Run the following on Windows to install Codex CLI:
powershell -ExecutionPolicy ByPass -c "irm https://chatgpt.com/codex/install.ps1 | iex"
Codex CLI can also be installed via the following package managers:
# Install using npm
npm install -g @openai/codex
# Install using Homebrew
brew install --cask codex
Then simply run codex to get started.
You can also go to the latest GitHub Release and download the appropriate binary for your platform.
Each GitHub Release contains many executables, but in practice, you likely want one of these:
- macOS
- Apple Silicon/arm64:
codex-aarch64-apple-darwin.tar.gz - x86_64 (older Mac hardware):
codex-x86_64-apple-darwin.tar.gz
- Apple Silicon/arm64:
- Linux
- x86_64:
codex-x86_64-unknown-linux-musl.tar.gz - arm64:
codex-aarch64-unknown-linux-musl.tar.gz
- x86_64:
Each archive contains a single entry with the platform baked into the name (e.g., codex-x86_64-unknown-linux-musl), so you likely want to rename it to codex after extracting it.
Using Codex with your ChatGPT plan
Run codex and select Sign in with ChatGPT. We recommend signing into your ChatGPT account to use Codex as part of your Plus, Pro, Business, Edu, or Enterprise plan. Learn more about what's included in your ChatGPT plan.
You can also use Codex with an API key, but this requires additional setup.
Docs
This repository is licensed under the Apache-2.0 License.