## Summary
- reduce public module visibility across Rust crates, preferring private
or crate-private modules with explicit crate-root public exports
- update external call sites and tests to use the intended public crate
APIs instead of reaching through module trees
- add the module visibility guideline to AGENTS.md
## Validation
- `cargo check --workspace --all-targets --message-format=short` passed
before the final fix/format pass
- `just fix` completed successfully
- `just fmt` completed successfully
- `git diff --check` passed
## Why
This finishes the config-type move out of `codex-core` by removing the
temporary compatibility shim in `codex_core::config::types`. Callers now
depend on `codex-config` directly, which keeps these config model types
owned by the config crate instead of re-expanding `codex-core` as a
transitive API surface.
## What Changed
- Removed the `codex-rs/core/src/config/types.rs` re-export shim and the
`core::config::ApprovalsReviewer` re-export.
- Updated `codex-core`, `codex-cli`, `codex-tui`, `codex-app-server`,
`codex-mcp-server`, and `codex-linux-sandbox` call sites to import
`codex_config::types` directly.
- Added explicit `codex-config` dependencies to downstream crates that
previously relied on the `codex-core` re-export.
- Regenerated `codex-rs/core/config.schema.json` after updating the
config docs path reference.
## Why
`codex-core` was re-exporting APIs owned by sibling `codex-*` crates,
which made downstream crates depend on `codex-core` as a proxy module
instead of the actual owner crate.
Removing those forwards makes crate boundaries explicit and lets leaf
crates drop unnecessary `codex-core` dependencies. In this PR, this
reduces the dependency on `codex-core` to `codex-login` in the following
files:
```
codex-rs/backend-client/Cargo.toml
codex-rs/mcp-server/tests/common/Cargo.toml
```
## What
- Remove `codex-rs/core/src/lib.rs` re-exports for symbols owned by
`codex-login`, `codex-mcp`, `codex-rollout`, `codex-analytics`,
`codex-protocol`, `codex-shell-command`, `codex-sandboxing`,
`codex-tools`, and `codex-utils-path`.
- Delete the `default_client` forwarding shim in `codex-rs/core`.
- Update in-crate and downstream callsites to import directly from the
owning `codex-*` crate.
- Add direct Cargo dependencies where callsites now target the owner
crate, and remove `codex-core` from `codex-rs/backend-client`.
## Why
`codex-mcp` already owns the shared MCP API surface, including `auth`,
`McpConfig`, `CODEX_APPS_MCP_SERVER_NAME`, and tool-name helpers in
[`codex-rs/codex-mcp/src/mcp/mod.rs`](https://github.com/openai/codex/blob/f61e85dbfb5373cde6827d232ac8ea447c237e81/codex-rs/codex-mcp/src/mcp/mod.rs#L1-L35).
Re-exporting that surface from `codex_core::mcp` gives downstream crates
two import paths for the same API and hides the real crate dependency.
This PR keeps `codex_core::mcp` focused on the local `McpManager`
wrapper in
[`codex-rs/core/src/mcp.rs`](https://github.com/openai/codex/blob/f61e85dbfb5373cde6827d232ac8ea447c237e81/codex-rs/core/src/mcp.rs#L13-L40)
and makes consumers import shared MCP APIs from `codex_mcp` directly.
## What
- Remove the `codex_mcp::mcp` re-export surface from `core/src/mcp.rs`.
- Update `codex-core` internals plus `codex-app-server`, `codex-cli`,
and `codex-tui` test code to import MCP APIs from `codex_mcp::mcp`
directly.
- Add explicit `codex-mcp` dependencies where those crates now use that
API surface, and refresh `Cargo.lock`.
## Verification
- `just bazel-lock-check`
- `cargo test -p codex-core -p codex-cli -p codex-tui`
- `codex-cli` passed.
- `codex-core` still fails five unrelated config tests in
`core/src/config/config_tests.rs` (`approvals_reviewer_*` and
`smart_approvals_alias_*`).
- A broader `cargo test -p codex-core -p codex-app-server -p codex-cli
-p codex-tui` run previously hung in `codex-app-server` test
`in_process_start_uses_requested_session_source_for_thread_start`.
- [x] Auto / unspecified approval mode: read-only tools now skip before
guardian routing.
- [x] Approve / always-allow mode: read-only tools still skip, now via
the shared early return.
- [x] Prompt mode: read-only tools no longer skip; they continue to
approval.
## Summary
- enrich `codex.mcp.call` with `tool`, `connector_id`, and sanitized
`connector_name` for actual MCP executions
- record `codex.mcp.call.duration_ms` for actual MCP executions so
connector-level latency is visible in metrics
- keep skipped, blocked, declined, and cancelled paths on the plain
status-only `codex.mcp.call` counter
## Included Changes
- `codex-rs/core/src/mcp_tool_call.rs`: add connector-sliced MCP count
and duration metrics only for executed tool calls, while leaving
non-executed outcomes as status-only counts
- `codex-rs/core/src/mcp_tool_call_tests.rs`: cover metric tag shaping,
connector-name sanitization, and the new duration metric tags
## Testing
- `cargo test -p codex-core`
- `just fix -p codex-core`
- `just fmt`
## Notes
- `cargo test -p codex-core` still hits existing unrelated failures in
approvals-reviewer config tests and the sandboxed JS REPL `mktemp` test
- full workspace `cargo test` was not run
---------
Co-authored-by: Codex <noreply@openai.com>
## Summary
- add an explicit `mcp.tools.call` span around MCP tool execution in
core
- keep MCP span validation local to `mcp_tool_call_tests` instead of
broadening the integration test suite
- inline the turn/session correlation fields directly in the span
initializer
## Included Changes
- `codex-rs/core/src/mcp_tool_call.rs`: wrap the existing MCP tool call
in `mcp.tools.call` and inline `conversation.id`, `session.id`, and
`turn.id` in the span initializer
- `codex-rs/core/src/mcp_tool_call_tests.rs`: assert the MCP span
records the expected correlation and server fields
## Testing
- `cargo test -p codex-core`
- `just fmt`
## Notes
- `cargo test -p codex-core` still hits existing unrelated failures in
guardian-config tests and the sandboxed JS REPL `mktemp` test
- metric work moved to stacked PR #15792
- transport-level RMCP spans and trace propagation remain in stacked PR
#15792
- full workspace `cargo test` was not run
---------
Co-authored-by: Codex <noreply@openai.com>
## Summary
- move the analytics events client into codex-analytics
- update codex-core and app-server callsites to use the new crate
## Testing
- CI
---------
Co-authored-by: Codex <noreply@openai.com>
- Changed `requires_mcp_tool_approval` to apply MCP spec defaults when
annotations are missing.
- Unannotated tools now default to:
- `readOnlyHint = false`
- `destructiveHint = true`
- `openWorldHint = true`
- This means unannotated MCP tools now go through approval/ARC
monitoring instead of silently bypassing it.
- Explicitly read-only tools still skip approval unless they are also
explicitly marked destructive.
**Previous behavior**
Failed open for missing annotations, which was unsafe for custom MCP
tools that omitted or forgot annotations.
---------
Co-authored-by: colby-oai <228809017+colby-oai@users.noreply.github.com>
- Split the feature system into a new `codex-features` crate.
- Cut `codex-core` and workspace consumers over to the new config and
warning APIs.
Co-authored-by: Ahmed Ibrahim <219906144+aibrahim-oai@users.noreply.github.com>
Co-authored-by: Codex <noreply@openai.com>
## Summary
Some background. We're looking to instrument GA turns end to end. Right
now a big gap is grouping mcp tool calls with their codex sessions. We
send session id and turn id headers to the responses call but not the
mcp/wham calls.
Ideally we could pass the args as headers like with responses, but given
the setup of the rmcp client, we can't send as headers without either
changing the rmcp package upstream to allow per request headers or
introducing a mutex which break concurrency. An earlier attempt made the
assumption that we had 1 client per thread, which allowed us to set
headers at the start of a turn. @pakrym mentioned that this assumption
might break in the near future.
So the solution now is to package the turn metadata/session id into the
_meta field in the post body and pull out in codex-backend.
- send turn metadata to MCP servers via `tools/call` `_meta` instead of
assuming per-thread request headers on shared clients
- preserve the existing `_codex_apps` metadata while adding
`x-codex-turn-metadata` for all MCP tool calls
- extend tests to cover both custom MCP servers and the codex apps
search flow
---------
Co-authored-by: Codex <noreply@openai.com>
## Why
Once the repo-local lint exists, `codex-rs` needs to follow the
checked-in convention and CI needs to keep it from drifting. This commit
applies the fallback `/*param*/` style consistently across existing
positional literal call sites without changing those APIs.
The longer-term preference is still to avoid APIs that require comments
by choosing clearer parameter types and call shapes. This PR is
intentionally the mechanical follow-through for the places where the
existing signatures stay in place.
After rebasing onto newer `main`, the rollout also had to cover newly
introduced `tui_app_server` call sites. That made it clear the first cut
of the CI job was too expensive for the common path: it was spending
almost as much time installing `cargo-dylint` and re-testing the lint
crate as a representative test job spends running product tests. The CI
update keeps the full workspace enforcement but trims that extra
overhead from ordinary `codex-rs` PRs.
## What changed
- keep a dedicated `argument_comment_lint` job in `rust-ci`
- mechanically annotate remaining opaque positional literals across
`codex-rs` with exact `/*param*/` comments, including the rebased
`tui_app_server` call sites that now fall under the lint
- keep the checked-in style aligned with the lint policy by using
`/*param*/` and leaving string and char literals uncommented
- cache `cargo-dylint`, `dylint-link`, and the relevant Cargo
registry/git metadata in the lint job
- split changed-path detection so the lint crate's own `cargo test` step
runs only when `tools/argument-comment-lint/*` or `rust-ci.yml` changes
- continue to run the repo wrapper over the `codex-rs` workspace, so
product-code enforcement is unchanged
Most of the code changes in this commit are intentionally mechanical
comment rewrites or insertions driven by the lint itself.
## Verification
- `./tools/argument-comment-lint/run.sh --workspace`
- `cargo test -p codex-tui-app-server -p codex-tui`
- parsed `.github/workflows/rust-ci.yml` locally with PyYAML
---
* -> #14652
* #14651
## Summary
- reuse a guardian subagent session across approvals so reviews keep a
stable prompt cache key and avoid one-shot startup overhead
- clear the guardian child history before each review so prior guardian
decisions do not leak into later approvals
- include the `smart_approvals` -> `guardian_approval` feature flag
rename in the same PR to minimize release latency on a very tight
timeline
- add regression coverage for prompt-cache-key reuse without
prior-review prompt bleed
## Request
- Bug/enhancement request: internal guardian prompt-cache and latency
improvement request
---------
Co-authored-by: Codex <noreply@openai.com>
## Summary
- add `approvals_reviewer = "user" | "guardian_subagent"` as the runtime
control for who reviews approval requests
- route Smart Approvals guardian review through core for command
execution, file changes, managed-network approvals, MCP approvals, and
delegated/subagent approval flows
- expose guardian review in app-server with temporary unstable
`item/autoApprovalReview/{started,completed}` notifications carrying
`targetItemId`, `review`, and `action`
- update the TUI so Smart Approvals can be enabled from `/experimental`,
aligned with the matching `/approvals` mode, and surfaced clearly while
reviews are pending or resolved
## Runtime model
This PR does not introduce a new `approval_policy`.
Instead:
- `approval_policy` still controls when approval is needed
- `approvals_reviewer` controls who reviewable approval requests are
routed to:
- `user`
- `guardian_subagent`
`guardian_subagent` is a carefully prompted reviewer subagent that
gathers relevant context and applies a risk-based decision framework
before approving or denying the request.
The `smart_approvals` feature flag is a rollout/UI gate. Core runtime
behavior keys off `approvals_reviewer`.
When Smart Approvals is enabled from the TUI, it also switches the
current `/approvals` settings to the matching Smart Approvals mode so
users immediately see guardian review in the active thread:
- `approval_policy = on-request`
- `approvals_reviewer = guardian_subagent`
- `sandbox_mode = workspace-write`
Users can still change `/approvals` afterward.
Config-load behavior stays intentionally narrow:
- plain `smart_approvals = true` in `config.toml` remains just the
rollout/UI gate and does not auto-set `approvals_reviewer`
- the deprecated `guardian_approval = true` alias migration does
backfill `approvals_reviewer = "guardian_subagent"` in the same scope
when that reviewer is not already configured there, so old configs
preserve their original guardian-enabled behavior
ARC remains a separate safety check. For MCP tool approvals, ARC
escalations now flow into the configured reviewer instead of always
bypassing guardian and forcing manual review.
## Config stability
The runtime reviewer override is stable, but the config-backed
app-server protocol shape is still settling.
- `thread/start`, `thread/resume`, and `turn/start` keep stable
`approvalsReviewer` overrides
- the config-backed `approvals_reviewer` exposure returned via
`config/read` (including profile-level config) is now marked
`[UNSTABLE]` / experimental in the app-server protocol until we are more
confident in that config surface
## App-server surface
This PR intentionally keeps the guardian app-server shape narrow and
temporary.
It adds generic unstable lifecycle notifications:
- `item/autoApprovalReview/started`
- `item/autoApprovalReview/completed`
with payloads of the form:
- `{ threadId, turnId, targetItemId, review, action? }`
`review` is currently:
- `{ status, riskScore?, riskLevel?, rationale? }`
- where `status` is one of `inProgress`, `approved`, `denied`, or
`aborted`
`action` carries the guardian action summary payload from core when
available. This lets clients render temporary standalone pending-review
UI, including parallel reviews, even when the underlying tool item has
not been emitted yet.
These notifications are explicitly documented as `[UNSTABLE]` and
expected to change soon.
This PR does **not** persist guardian review state onto `thread/read`
tool items. The intended follow-up is to attach guardian review state to
the reviewed tool item lifecycle instead, which would improve
consistency with manual approvals and allow thread history / reconnect
flows to replay guardian review state directly.
## TUI behavior
- `/experimental` exposes the rollout gate as `Smart Approvals`
- enabling it in the TUI enables the feature and switches the current
session to the matching Smart Approvals `/approvals` mode
- disabling it in the TUI clears the persisted `approvals_reviewer`
override when appropriate and returns the session to default manual
review when the effective reviewer changes
- `/approvals` still exposes the reviewer choice directly
- the TUI renders:
- pending guardian review state in the live status footer, including
parallel review aggregation
- resolved approval/denial state in history
## Scope notes
This PR includes the supporting core/runtime work needed to make Smart
Approvals usable end-to-end:
- shell / unified-exec / apply_patch / managed-network / MCP guardian
review
- delegated/subagent approval routing into guardian review
- guardian review risk metadata and action summaries for app-server/TUI
- config/profile/TUI handling for `smart_approvals`, `guardian_approval`
alias migration, and `approvals_reviewer`
- a small internal cleanup of delegated approval forwarding to dedupe
fallback paths and simplify guardian-vs-parent approval waiting (no
intended behavior change)
Out of scope for this PR:
- redesigning the existing manual approval protocol shapes
- persisting guardian review state onto app-server `ThreadItem`s
- delegated MCP elicitation auto-review (the current delegated MCP
guardian shim only covers the legacy `RequestUserInput` path)
---------
Co-authored-by: Codex <noreply@openai.com>
## Why
PR #13783 moved the `codex.rs` unit tests into `codex_tests.rs`. This
applies the same extraction pattern across the rest of `codex-rs/core`
so the production modules stay focused on runtime code instead of large
inline test blocks.
Keeping the tests in sibling files also makes follow-up edits easier to
review because product changes no longer have to share a file with
hundreds or thousands of lines of test scaffolding.
## What changed
- replaced each inline `mod tests { ... }` in `codex-rs/core/src/**`
with a path-based module declaration
- moved each extracted unit test module into a sibling `*_tests.rs`
file, using `mod_tests.rs` for `mod.rs` modules
- preserved the existing `cfg(...)` guards and module-local structure so
the refactor remains structural rather than behavioral
## Testing
- `cargo test -p codex-core --lib` (`1653 passed; 0 failed; 5 ignored`)
- `just fix -p codex-core`
- `cargo fmt --check`
- `cargo shear`
## Why
to support a new bring your own search tool in Responses
API(https://developers.openai.com/api/docs/guides/tools-tool-search#client-executed-tool-search)
we migrating our bm25 search tool to use official way to execute search
on client and communicate additional tools to the model.
## What
- replace the legacy `search_tool_bm25` flow with client-executed
`tool_search`
- add protocol, SSE, history, and normalization support for
`tool_search_call` and `tool_search_output`
- return namespaced Codex Apps search results and wire namespaced
follow-up tool calls back into MCP dispatch
Summary
- drop `McpToolOutput` in favor of `CallToolResult`, moving its helpers
to keep MCP tooling focused on the final result shape
- wire the new schema definitions through code mode, context, handlers,
and spec modules so MCP tools serialize the exact output shape expected
by the model
- extend code mode tests to cover multiple MCP call scenarios and ensure
the serialized data matches the new schema
- refresh JS runner helpers and protocol models alongside the schema
changes
Testing
- Not run (not requested)
## Summary
- add ARC monitor support for MCP tool calls by serializing MCP approval
requests into the ARC action shape and sending the relevant
conversation/policy context to the `/api/codex/safety/arc` endpoint
- route ARC outcomes back into MCP approval flow so `ask-user` falls
back to a user prompt and `steer-model` blocks the tool call, with
guardian/ARC tests covering the new request shape
- update the TUI approval copy from “Approve Once” to “Allow” / “Allow
for this session” and refresh the related
snapshots
---------
Co-authored-by: Fouad Matin <fouad@openai.com>
Co-authored-by: Fouad Matin <169186268+fouad-openai@users.noreply.github.com>
## Summary
- remove the remaining model-visible guardian-specific `on-request`
prompt additions so enabling the feature does not change the main
approval-policy instructions
- neutralize user-facing guardian wording to talk about automatic
approval review / approval requests rather than a second reviewer or
only sandbox escalations
- tighten guardian retry-context handling so agent-authored
`justification` stays in the structured action JSON and is not also
injected as raw retry context
- simplify guardian review plumbing in core by deleting dead
prompt-append paths and trimming some request/transcript setup code
## Notable Changes
- delete the dead `permissions/approval_policy/guardian.md` append path
and stop threading `guardian_approval_enabled` through model-facing
developer-instruction builders
- rename the experimental feature copy to `Automatic approval review`
and update the `/experimental` snapshot text accordingly
- make approval-review status strings generic across shell, patch,
network, and MCP review types
- forward real sandbox/network retry reasons for shell and unified-exec
guardian review, but do not pass agent-authored justification as raw
retry context
- simplify `guardian.rs` by removing the one-field request wrapper,
deduping reasoning-effort selection, and cleaning up transcript entry
collection
## Testing
- `just fmt`
- full validation left to CI
---------
Co-authored-by: Codex <noreply@openai.com>
## Summary
- add the guardian reviewer flow for `on-request` approvals in command,
patch, sandbox-retry, and managed-network approval paths
- keep guardian behind `features.guardian_approval` instead of exposing
a public `approval_policy = guardian` mode
- route ordinary `OnRequest` approvals to the guardian subagent when the
feature is enabled, without changing the public approval-mode surface
## Public model
- public approval modes stay unchanged
- guardian is enabled via `features.guardian_approval`
- when that feature is on, `approval_policy = on-request` keeps the same
approval boundaries but sends those approval requests to the guardian
reviewer instead of the user
- `/experimental` only persists the feature flag; it does not rewrite
`approval_policy`
- CLI and app-server no longer expose a separate `guardian` approval
mode in this PR
## Guardian reviewer
- the reviewer runs as a normal subagent and reuses the existing
subagent/thread machinery
- it is locked to a read-only sandbox and `approval_policy = never`
- it does not inherit user/project exec-policy rules
- it prefers `gpt-5.4` when the current provider exposes it, otherwise
falls back to the parent turn's active model
- it fail-closes on timeout, startup failure, malformed output, or any
other review error
- it currently auto-approves only when `risk_score < 80`
## Review context and policy
- guardian mirrors `OnRequest` approval semantics rather than
introducing a separate approval policy
- explicit `require_escalated` requests follow the same approval surface
as `OnRequest`; the difference is only who reviews them
- managed-network allowlist misses that enter the approval flow are also
reviewed by guardian
- the review prompt includes bounded recent transcript history plus
recent tool call/result evidence
- transcript entries and planned-action strings are truncated with
explicit `<guardian_truncated ... />` markers so large payloads stay
bounded
- apply-patch reviews include the full patch content (without
duplicating the structured `changes` payload)
- the guardian request layout is snapshot-tested using the same
model-visible Responses request formatter used elsewhere in core
## Guardian network behavior
- the guardian subagent inherits the parent session's managed-network
allowlist when one exists, so it can use the same approved network
surface while reviewing
- exact session-scoped network approvals are copied into the guardian
session with protocol/port scope preserved
- those copied approvals are now seeded before the guardian's first turn
is submitted, so inherited approvals are available during any immediate
review-time checks
## Out of scope / follow-ups
- the sandbox-permission validation split was pulled into a separate PR
and is not part of this diff
- a future follow-up can enable `serde_json` preserve-order in
`codex-core` and then simplify the guardian action rendering further
---------
Co-authored-by: Codex <noreply@openai.com>
## Summary
This is a purely mechanical refactor of `OtelManager` ->
`SessionTelemetry` to better convey what the struct is doing. No
behavior change.
## Why
`OtelManager` ended up sounding much broader than what this type
actually does. It doesn't manage OTEL globally; it's the session-scoped
telemetry surface for emitting log/trace events and recording metrics
with consistent session metadata (`app_version`, `model`, `slug`,
`originator`, etc.).
`SessionTelemetry` is a more accurate name, and updating the call sites
makes that boundary a lot easier to follow.
## Validation
- `just fmt`
- `cargo test -p codex-otel`
- `cargo test -p codex-core`
- use `skills_for_cwd` lookup to scope allowed skills and build
invocation context for downstream processing
- add detection in `stream_events_utils` to classify tool calls as
implicit skill invocations per the proposal (script runners, extensions,
`scripts` dirs, and SKILL.md reads)
- deduplicate invocations per turn and emit analytics/OTEL events on the
same background queue as explicit invokes
Summary
- ensure destructive tool annotations short-circuit to require approval
- simplify approval logic to only require read/write + open-world when
destructive is false
- update the unit test to cover the new destructive behavior
Testing
- Not run (not requested)
Summary
This PR expands MCP client-side approval behavior beyond codex_apps and
tightens elicitation capability signaling.
- Removed the codex_apps-only gate in MCP tool approval checks, so
local/custom MCP servers are now eligible for the same client-side
approval prompt flow when tool annotations indicate side effects.
- Updated approval memory keying to support tools without a connector ID
(connector_id: Option<String>), allowing “Approve this Session” to be
remembered even when connector metadata is missing.
- Updated prompt text for non-codex_apps tools to identify origin as The
<server> MCP server instead of This app.
- Added MCP initialization capability policy so only codex_apps
advertises MCP elicitation capability; other servers advertise no
elicitation support.
- Added regression tests for:
server-specific prompt copy behavior
codex-apps-only elicitation capability advertisement
Testing
- Not run (not requested)
- Replace image blocks in MCP tool results with a text placeholder when
the active model does not accept image input.
- Add an e2e rmcp test to verify sanitized tool output is what gets sent
back to the model.
Took over the work that @aaronl-openai started here:
https://github.com/openai/codex/pull/10397
Now that app-server clients are able to set up custom tools (called
`dynamic_tools` in app-server), we should expose a way for clients to
pass in not just text, but also image outputs. This is something the
Responses API already supports for function call outputs, where you can
pass in either a string or an array of content outputs (text, image,
file):
https://platform.openai.com/docs/api-reference/responses/create#responses_create-input-input_item_list-item-function_tool_call_output-output-array-input_image
So let's just plumb it through in Codex (with the caveat that we only
support text and image for now). This is implemented end-to-end across
app-server v2 protocol types and core tool handling.
## Breaking API change
NOTE: This introduces a breaking change with dynamic tools, but I think
it's ok since this concept was only recently introduced
(https://github.com/openai/codex/pull/9539) and it's better to get the
API contract correct. I don't think there are any real consumers of this
yet (not even the Codex App).
Old shape:
`{ "output": "dynamic-ok", "success": true }`
New shape:
```
{
"contentItems": [
{ "type": "inputText", "text": "dynamic-ok" },
{ "type": "inputImage", "imageUrl": "data:image/png;base64,AAA" }
]
"success": true
}
```
This PR adds a new approval option for app/MCP tool calls: “Allow and
remember” (session-scoped).
When selected, Codex stores a temporary approval and auto-approves
matching future calls for the rest of the session.
Added a session-scoped approval key (`server`, `connector_id`,
`tool_name`) and persisted it in `tool_approvals` as
`ApprovedForSession`.
On subsequent matching calls, approval is skipped and treated as
accepted.
- Updated the approval question options to conditionally include:
- Accept
- Allow and remember (conditional)
- Decline
- Cancel
The new “Allow and remember” option is only shown when all of these are
true:
1. The call is routed through the Codex Apps MCP server (codex_apps).
2. The tool requires approval based on annotations:
- read_only_hint == false, and
- destructive_hint == true or open_world_hint == true.
3. The tool includes a connector_id in metadata (used to build the
remembered approval key).
If no `connector_id` is present, the prompt still appears (when approval
is required), but only with the existing choices (Accept / Decline /
Cancel). Approval prompting in this path has an explicit early return
unless server == `codex_apps`.
We started working with MCP in Codex before
https://crates.io/crates/rmcp was mature, so we had our own crate for
MCP types that was generated from the MCP schema:
https://github.com/openai/codex/blob/8b95d3e082376f4cb23e92641705a22afb28a9da/codex-rs/mcp-types/README.md
Now that `rmcp` is more mature, it makes more sense to use their MCP
types in Rust, as they handle details (like the `_meta` field) that our
custom version ignored. Though one advantage that our custom types had
is that our generated types implemented `JsonSchema` and `ts_rs::TS`,
whereas the types in `rmcp` do not. As such, part of the work of this PR
is leveraging the adapters between `rmcp` types and the serializable
types that are API for us (app server and MCP) introduced in #10356.
Note this PR results in a number of changes to
`codex-rs/app-server-protocol/schema`, which merit special attention
during review. We must ensure that these changes are still
backwards-compatible, which is possible because we have:
```diff
- export type CallToolResult = { content: Array<ContentBlock>, isError?: boolean, structuredContent?: JsonValue, };
+ export type CallToolResult = { content: Array<JsonValue>, structuredContent?: JsonValue, isError?: boolean, _meta?: JsonValue, };
```
so `ContentBlock` has been replaced with the more general `JsonValue`.
Note that `ContentBlock` was defined as:
```typescript
export type ContentBlock = TextContent | ImageContent | AudioContent | ResourceLink | EmbeddedResource;
```
so the deletion of those individual variants should not be a cause of
great concern.
Similarly, we have the following change in
`codex-rs/app-server-protocol/schema/typescript/Tool.ts`:
```
- export type Tool = { annotations?: ToolAnnotations, description?: string, inputSchema: ToolInputSchema, name: string, outputSchema?: ToolOutputSchema, title?: string, };
+ export type Tool = { name: string, title?: string, description?: string, inputSchema: JsonValue, outputSchema?: JsonValue, annotations?: JsonValue, icons?: Array<JsonValue>, _meta?: JsonValue, };
```
so:
- `annotations?: ToolAnnotations` ➡️ `JsonValue`
- `inputSchema: ToolInputSchema` ➡️ `JsonValue`
- `outputSchema?: ToolOutputSchema` ➡️ `JsonValue`
and two new fields: `icons?: Array<JsonValue>, _meta?: JsonValue`
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/10349).
* #10357
* __->__ #10349
* #10356
It's pretty amazing we have gotten here without the ability for the
model to see image content from MCP tool calls.
This PR builds off of 4391 and fixes#4819. I would like @KKcorps to get
adequete credit here but I also want to get this fix in ASAP so I gave
him a week to update it and haven't gotten a response so I'm going to
take it across the finish line.
This test highlights how absured the current situation is. I asked the
model to read this image using the Chrome MCP
<img width="2378" height="674" alt="image"
src="https://github.com/user-attachments/assets/9ef52608-72a2-4423-9f5e-7ae36b2b56e0"
/>
After this change, it correctly outputs:
> Captured the page: image dhows a dark terminal-style UI labeled
`OpenAI Codex (v0.0.0)` with prompt `model: gpt-5-codex medium` and
working directory `/codex/codex-rs`
(and more)
Before this change, it said:
> Took the full-page screenshot you asked for. It shows a long,
horizontally repeating pattern of stylized people in orange, light-blue,
and mustard clothing, holding hands in alternating poses against a white
background. No text or other graphics-just rows of flat illustration
stretching off to the right.
Without this change, the Figma, Playwright, Chrome, and other visual MCP
servers are pretty much entirely useless.
I tested this change with the openai respones api as well as a third
party completions api
Today `sub_id` is an ID of a single incoming Codex Op submition. We then
associate all events triggered by this operation using the same
`sub_id`.
At the same time we are also creating a TurnContext per submission and
we'd like to start associating some events (item added/item completed)
with an entire turn instead of just the operation that started it.
Using turn context when sending events give us flexibility to change
notification scheme.
pakrym-oai