This updates the MCP server so that if it receives an
`ExecApprovalRequest` from the `Codex` session, it in turn sends an [MCP
elicitation](https://modelcontextprotocol.io/specification/draft/client/elicitation)
to the client to ask for the approval decision. Upon getting a response,
it forwards the client's decision via `Op::ExecApproval`.
Admittedly, we should be doing the same thing for
`ApplyPatchApprovalRequest`, but this is our first time experimenting
with elicitations, so I'm inclined to defer wiring that code path up
until we feel good about how this one works.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/1623).
* __->__ #1623
* #1622
* #1621
* #1620
Previous to this change, `MessageProcessor` had a
`tokio::sync::mpsc::Sender<JSONRPCMessage>` as an abstraction for server
code to send a message down to the MCP client. Because `Sender` is cheap
to `clone()`, it was straightforward to make it available to tasks
scheduled with `tokio::task::spawn()`.
This worked well when we were only sending notifications or responses
back down to the client, but we want to add support for sending
elicitations in #1623, which means that we need to be able to send
_requests_ to the client, and now we need a bit of centralization to
ensure all request ids are unique.
To that end, this PR introduces `OutgoingMessageSender`, which houses
the existing `Sender<OutgoingMessage>` as well as an `AtomicI64` to mint
out new, unique request ids. It has methods like `send_request()` and
`send_response()` so that callers do not have to deal with
`JSONRPCMessage` directly, as having to set the `jsonrpc` for each
message was a bit tedious (this cleans up `codex_tool_runner.rs` quite a
bit).
We do not have `OutgoingMessageSender` implement `Clone` because it is
important that the `AtomicI64` is shared across all users of
`OutgoingMessageSender`. As such, `Arc<OutgoingMessageSender>` must be
used instead, as it is frequently shared with new tokio tasks.
As part of this change, we update `message_processor.rs` to embrace
`await`, though we must be careful that no individual handler blocks the
main loop and prevents other messages from being handled.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/1622).
* #1623
* __->__ #1622
* #1621
* #1620
This updates the schema in `generate_mcp_types.py` from `2025-03-26` to
`2025-06-18`, regenerates `mcp-types/src/lib.rs`, and then updates all
the code that uses `mcp-types` to honor the changes.
Ran
```
npx @modelcontextprotocol/inspector just codex mcp
```
and verified that I was able to invoke the `codex` tool, as expected.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/1621).
* #1623
* #1622
* __->__ #1621
https://github.com/openai/codex/pull/1086 is a work-in-progress to make
Linux sandboxing work more like Seatbelt where, for the command we want
to sandbox, we build up the command and then hand it, and some sandbox
configuration flags, to another command to set up the sandbox and then
run it.
In the case of Seatbelt, macOS provides this helper binary and provides
it at `/usr/bin/sandbox-exec`. For Linux, we have to build our own and
pass it through (which is what #1086 does), so this makes the new
`codex_linux_sandbox_exe` available on `Config` so that it will later be
available in `exec.rs` when we need it in #1086.
Sets submodules to use workspace lints. Added denying unwrap as a
workspace level lint, which found a couple of cases where we could have
propagated errors. Also manually labeled ones that were fine by my eye.
Some effects of this change:
- New formatting changes across many files. No functionality changes
should occur from that.
- Calls to `set_env` are considered unsafe, since this only happens in
tests we wrap them in `unsafe` blocks
This PR replaces the placeholder `"echo"` tool call in the MCP server
with a `"codex"` tool that calls Codex. Events such as
`ExecApprovalRequest` and `ApplyPatchApprovalRequest` are not handled
properly yet, but I have `approval_policy = "never"` set in my
`~/.codex/config.toml` such that those codepaths are not exercised.
The schema for this MPC tool is defined by a new `CodexToolCallParam`
struct introduced in this PR. It is fairly similar to `ConfigOverrides`,
as the param is used to help create the `Config` used to start the Codex
session, though it also includes the `prompt` used to kick off the
session.
This PR also introduces the use of the third-party `schemars` crate to
generate the JSON schema, which is verified in the
`verify_codex_tool_json_schema()` unit test.
Events that are dispatched during the Codex session are sent back to the
MCP client as MCP notifications. This gives the client a way to monitor
progress as the tool call itself may take minutes to complete depending
on the complexity of the task requested by the user.
In the video below, I launched the server via:
```shell
mcp-server$ RUST_LOG=debug npx @modelcontextprotocol/inspector cargo run --
```
In the video, you can see the flow of:
* requesting the list of tools
* choosing the **codex** tool
* entering a value for **prompt** and then making the tool call
Note that I left the other fields blank because when unspecified, the
values in my `~/.codex/config.toml` were used:
https://github.com/user-attachments/assets/1975058c-b004-43ef-8c8d-800a953b8192
Note that while using the inspector, I did run into
https://github.com/modelcontextprotocol/inspector/issues/293, though the
tip about ensuring I had only one instance of the **MCP Inspector** tab
open in my browser seemed to fix things.
Michael Bolin ·
jcoens-openai ·