This PR adds support for streamable HTTP MCP servers when the
`experimental_use_rmcp_client` is enabled.
To set one up, simply add a new mcp server config with the url:
```
[mcp_servers.figma]
url = "http://127.0.0.1:3845/mcp"
```
It also supports an optional `bearer_token` which will be provided in an
authorization header. The full oauth flow is not supported yet.
The config parsing will throw if it detects that the user mixed and
matched config fields (like command + bearer token or url + env).
The best way to review it is to review `core/src` and then
`rmcp-client/src/rmcp_client.rs` first. The rest is tests and
propagating the `Transport` struct around the codebase.
Example with the Figma MCP:
<img width="5084" height="1614" alt="CleanShot 2025-09-26 at 13 35 40"
src="https://github.com/user-attachments/assets/eaf2771e-df3e-4300-816b-184d7dec5a28"
/>
- Render `send a message to load usage data` in the beginning of the
session
- Render `data not available yet` if received no rate limits
- nit case
- Deleted stall snapshots that were moved to
`codex-rs/tui/src/status/snapshots`
The [official Rust
SDK](57fc428c57)
has come a long way since we first started our mcp client implementation
5 months ago and, today, it is much more complete than our own
stdio-only implementation.
This PR introduces a new config flag `experimental_use_rmcp_client`
which will use a new mcp client powered by the sdk instead of our own.
To keep this PR simple, I've only implemented the same stdio MCP
functionality that we had but will expand on it with future PRs.
---------
Co-authored-by: pakrym-oai <pakrym@openai.com>
Extracting tasks in a module and start abstraction behind a Trait (more
to come on this but each task will be tackled in a dedicated PR)
The goal was to drop the ActiveTask and to have a (potentially) set of
tasks during each turn
Certain shell commands are potentially dangerous, and we want to check
for them.
Unless the user has explicitly approved a command, we will *always* ask
them for approval
when one of these commands is encountered, regardless of whether they
are in a sandbox, or what their approval policy is.
The first (of probably many) such examples is `git reset --hard`. We
will be conservative and check for any `git reset`
This addresses bug #4092
Testing:
* Confirmed error occurs prior to fix if logging in using API key and no
`~/.codex` directory exists
* Confirmed after fix that `~/.codex` directory is properly created and
error doesn't occur
# External (non-OpenAI) Pull Request Requirements
Before opening this Pull Request, please read the dedicated
"Contributing" markdown file or your PR may be closed:
https://github.com/openai/codex/blob/main/docs/contributing.md
If your PR conforms to our contribution guidelines, replace this text
with a detailed and high quality description of your changes.
This changes the reqwest client used in tests to be sandbox-friendly,
and skips a bunch of other tests that don't work inside the
sandbox/without network.
I would like to be able to swap in a different way to resolve model
sampling requests, so this refactoring consolidates things behind
`attempt_stream_responses()` to make that easier. Ideally, we would
support an in-memory backend that we can use in our integration tests,
for example.
## Current State Observations
- `Session` currently holds many unrelated responsibilities (history,
approval queues, task handles, rollout recorder, shell discovery, token
tracking, etc.), making it hard to reason about ownership and lifetimes.
- The anonymous `State` struct inside `codex.rs` mixes session-long data
with turn-scoped queues and approval bookkeeping.
- Turn execution (`run_task`) relies on ad-hoc local variables that
should conceptually belong to a per-turn state object.
- External modules (`codex::compact`, tests) frequently poke the raw
`Session.state` mutex, which couples them to implementation details.
- Interrupts, approvals, and rollout persistence all have bespoke
cleanup paths, contributing to subtle bugs when a turn is aborted
mid-flight.
## Desired End State
- Keep a slim `Session` object that acts as the orchestrator and façade.
It should expose a focused API (submit, approvals, interrupts, event
emission) without storing unrelated fields directly.
- Introduce a `state` module that encapsulates all mutable data
structures:
- `SessionState`: session-persistent data (history, approved commands,
token/rate-limit info, maybe user preferences).
- `ActiveTurn`: metadata for the currently running turn (sub-id, task
kind, abort handle) and an `Arc<TurnState>`.
- `TurnState`: all turn-scoped pieces (pending inputs, approval waiters,
diff tracker, review history, auto-compact flags, last agent message,
outstanding tool call bookkeeping).
- Group long-lived helpers/managers into a dedicated `SessionServices`
struct so `Session` does not accumulate "random" fields.
- Provide clear, lock-safe APIs so other modules never touch raw
mutexes.
- Ensure every turn creates/drops a `TurnState` and that
interrupts/finishes delegate cleanup to it.
For the most part, we try to avoid environment variables in favor of
config options so the environment variables do not leak into child
processes. These environment variables are no longer honored, so let's
delete them to be clear.
Ultimately, I would also like to eliminate `CODEX_RS_SSE_FIXTURE` in
favor of something cleaner.
refactors command_safety files into its own package, so we can add
platform-specific ones
Also creates a windows-specific of `is_known_safe_command` that just
returns false always, since that is what happens today.
The only file to watch is the cargo.toml
All the others come from just fix + a few manual small fix
The set of rules have been taken from the list of clippy rules
arbitrarily while trying to optimise the learning and style of the code
while limiting the loss of productivity
Adds the following options:
1. Review current changes
2. Review a specific commit
3. Review against a base branch (PR style)
4. Custom instructions
<img width="487" height="330" alt="Screenshot 2025-09-20 at 2 11 36 PM"
src="https://github.com/user-attachments/assets/edb0aaa5-5747-47fa-881f-cc4c4f7fe8bc"
/>
---
\+ Adds the following UI helpers:
1. Makes list selection searchable
2. Adds navigation to the bottom pane, so you could add a stack of
popups
3. Basic custom prompt view
We currently get information about rate limits in the response headers.
We want to forward them to the clients to have better transparency.
UI/UX plans have been discussed and this information is needed.
Currently, we change the tool description according to the sandbox
policy and approval policy. This breaks the cache when the user hits
`/approvals`. This PR does the following:
- Always use the shell with escalation parameter:
- removes `create_shell_tool_for_sandbox` and always uses unified tool
via `create_shell_tool`
- Reject the func call when the model uses escalation parameter when it
cannot.
### Why Use `tokio::sync::Mutex`
`std::sync::Mutex` are not _async-aware_. As a result, they will block
the entire thread instead of just yielding the task. Furthermore they
can be poisoned which is not the case of `tokio` Mutex.
This allows the Tokio runtime to continue running other tasks while
waiting for the lock, preventing deadlocks and performance bottlenecks.
In general, this is preferred in async environment
Proposal: We want to record a dev message like so:
```
{
"type": "message",
"role": "user",
"content": [
{
"type": "input_text",
"text": "<user_action>
<context>User initiated a review task. Here's the full review output from reviewer model. User may select one or more comments to resolve.</context>
<action>review</action>
<results>
{findings_str}
</results>
</user_action>"
}
]
},
```
Without showing in the chat transcript.
Rough idea, but it fixes issue where the user finishes a review thread,
and asks the parent "fix the rest of the review issues" thinking that
the parent knows about it.
### Question: Why not a tool call?
Because the agent didn't make the call, it was a human. + we haven't
implemented sub-agents yet, and we'll need to think about the way we
represent these human-led tool calls for the agent.
1. Adds the environment prompt (including cwd) to review thread
2. Prepends the review prompt as a user message (temporary fix so the
instructions are not replaced on backend)
3. Sets reasoning to low
4. Sets default review model to `gpt-5-codex`
## Summary
SendUserTurn has not been correctly handling updates to policies. While
the tui protocol handles this in `Op::OverrideTurnContext`, the
SendUserTurn should be appending `EnvironmentContext` messages when the
sandbox settings change. MCP client behavior should match the cli
behavior, so we update `SendUserTurn` message to match.
## Testing
- [x] Added prompt caching tests
