"Information on MCP-Codex-Keeper" matching MCP servers:

Call OpenAI Codex from Claude Code for independent second opinions, structured code review, and delegated coding tasks through a FastMCP plugin that drives the codex CLI safely.

Enables Codex CLI to perform code reviews on uncommitted changes via an MCP tool, keeping review context separate from the main session.

Uses Claude as an independent second-model reviewer inside Codex, performing reviews on disposable Git snapshots with structured findings.

Enables auditable, plan-linked Git commit review views for Codex, with interactive file trees, split diffs, line-level explanations, and SHA-256 audit receipts served locally on localhost.

Enables Claude Code agents and subagents to get an independent read-only review of their changes from OpenAI Codex and to continue that same Codex conversation later for re-checks. Runs each request in an isolated CODEX_HOME so those threads stay separate from the Codex desktop app, supporting parallel callers and per-call model, effort, sandbox, and timeout settings.

Gives OpenAI Codex behavioral history from workspace.json, exposing file fragility and co-change partners as tools to enforce safer edits and block incomplete patches.

Helps AI assistants optimize Linux workloads on Arm64 by parsing perf report output, recommending NEON SIMD intrinsics for hot loops, and auditing Python dependency manifests for arm64 wheel availability — all offline and structured.

Lets MCP-compatible AI assistants have read-only conversations with OpenAI Codex CLI for code analysis, review, and Q&A.

Enables developers and AI agents to compress context, plan token budgets, rerank results, patch code, analyze ASTs and dependencies, isolate stack traces, compile polyglot types, solve deterministic math, schedule constraints, judge A/B tests, and diff agent memory checkpoints through 12 specialized tools.

A local MCP server that provides semantic code search for Python codebases using tree-sitter for chunking and LanceDB for vector storage. It enables natural language queries to find relevant code snippets based on meaning rather than just text matching.

Enables independent, read-only adversarial review of candidate test cases and bug findings, returning a review delta that authoring agents reconcile before writing final artifacts.

Enables efficient analysis of large codebases using Claude Code and Kimi K2.5 through the Model Context Protocol, with session caching and parallel processing to reduce costs and time.

Enables fast, low-token code search for AI coding agents via a local BM25 engine built on SQLite FTS5, with support for camelCase, snake_case, and Japanese text. Provides a stateless MCP stdio server and a Hermes adapter for multi-agent environments.

Enables adversarial code review by connecting Claude Code to OpenAI Codex, iterating until consensus is reached between the two AI models.

MCP server that enables Claude Code to send code and plans for review by OpenAI Codex, returning structured feedback inline.

Enables AI coding assistants to interact with OpenAI's Codex AI through the official CLI. Provides direct integration for code analysis, file review, and batch processing with zero API costs.

MCP server that provides npm package information for AI agents during TypeScript development.

Indexes a mono-repo into a knowledge graph and provides MCP tools to query code structure—packages, components, routes, HTTP calls—without file reads or grep round-trips.

Wraps Claude Code's code-review skill so any MCP client can run reviews over a PR, branch, working directory, or last commit, with five parallel reviewer subagents, low-to-max effort levels, and optional fix mode that edits files in place. Also supports follow-up questions on a previous review session and a free environment self-check.

MCP server that lets Claude Code ask GPT Codex for adversarial planning, code review, debugging, research, and risk triage without leaving your project workflow.