# OpenAI Codex CLI — token-optimizer MCP server.
# Merge this into ~/.codex/config.toml (Codex reads MCP servers under
# [mcp_servers.<name>]). Then add the guidance from ../AGENTS.md to your
# project's AGENTS.md (or ~/.codex/AGENTS.md) so Codex knows when to use them.
#
# USE THIS *OR* THE PLUGIN, NOT BOTH. The Codex plugin declares the same server
# in its own .mcp.json. Enabling the plugin and also pasting the block below
# leaves two declarations of one server under the same name, which is at best
# redundant and at worst ambiguous about which settings win. If
# `codex mcp get token-optimizer` already shows the server, the plugin has it
# covered and this file is not needed.

[mcp_servers.token-optimizer]
command = "npx"
args = ["-y", "@ooples/token-optimizer-mcp@latest"]

# DO NOT DROP THESE TIMEOUTS.
#
# Codex's own MCP reference (learn.chatgpt.com/docs/extend/mcp) gives the
# defaults as:
#
#   startup_timeout_sec  Timeout (seconds) for the server to start.        Default: 10
#   tool_timeout_sec     Timeout (seconds) for the server to run a tool.   Default: 60
#
# Ten seconds does not cover a cold start here. `npx -y ...@latest` contacts the
# registry before node is even launched, and the first run then loads the
# tokenizer and opens the cache database. Measured on Windows: 12.1s cold against
# 1.4s warm -- healthy both times, over the default budget exactly once. Codex
# kills the process at the deadline, and the user sees a server that was
# configured and enabled and registered no tools (issue #307).
#
# The plugin's .mcp.json has always carried these values; this file did not, so
# the two supported ways of installing the same server behaved differently.
startup_timeout_sec = 30
tool_timeout_sec = 120

# Optional: point the cache somewhere stable.
# env = { TOKEN_OPTIMIZER_CACHE_DIR = "~/.token-optimizer-cache" }