Ask LLM

You:    ask codex to review src/auth.ts for security issues
Codex:  ⚠ verifyToken() compares tokens with === — not timing-safe (line 42)
        ⚠ the session cookie is missing a SameSite attribute
Claude: Good catches — applying both fixes to src/auth.ts.

One prompt. A second model reviews independently; your assistant applies the fix. No copy-pasting between tools.

Your primary AI is confident, but confidence isn't correctness. A second model with no stake in the first answer catches what it glossed over.

Prerequisites: Node.js 24+ (the current LTS), on Linux or macOS, and at least one provider CLI installed and authenticated (see Provider setup).

# One install, every provider — auto-detects what you have
claude mcp add --scope user ask-llm -- npx -y @ask-llm/mcp
# first-class alternative after `npm install -g @ask-llm/mcp`:
# claude mcp add --scope user ask-llm -- ask-llm-mcp

Then try: ask codex to review my last commit. Run npx @ask-llm/mcp doctor if anything looks off.

claude mcp add --scope user codex -- npx -y @ask-llm/codex-mcp
claude mcp add --scope user grok -e XAI_API_KEY="$XAI_API_KEY" -- npx -y @ask-llm/grok-mcp
claude mcp add --scope user antigravity -- npx -y @ask-llm/antigravity-mcp
claude mcp add --scope user ollama -- npx -y @ask-llm/ollama-mcp
claude mcp add --scope user gemini -- npx -y @ask-llm/gemini-mcp

Add to .cursor/mcp.json (project) or ~/.cursor/mcp.json (user):

{
  "mcpServers": {
    "ask-llm": { "command": "npx", "args": ["-y", "@ask-llm/mcp"] }
  }
}

# ~/.codex/config.toml
[mcp_servers.ask-llm]
command = "npx"
args = ["-y", "@ask-llm/mcp"]

Want Codex to consult Claude specifically? codex mcp add claude -- npx -y @ask-llm/claude-mcp

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "ask-llm": { "command": "npx", "args": ["-y", "@ask-llm/mcp"] }
  }
}

Pi has no built-in MCP client, so it installs the host package instead, which registers native ask-* tools plus the shared skills:

pi install npm:@ask-llm/plugin

Then use /skill:codex-review, /skill:multi-review, /skill:compare, /skill:brainstorm, or just describe what you want. See the Pi host guide for trust, data-transfer, and compatibility details.

{ "command": "npx", "args": ["-y", "@ask-llm/mcp"] }

The unified @ask-llm/mcp server is the recommended install: one registration, every provider you have, and parallel fan-out via multi-llm. Each provider is also available standalone.

Gemini CLI is enterprise-only since 2026-06-18. Google restricted Gemini CLI to Gemini Code Assist Standard/Enterprise seats; free, Google AI Pro, and Ultra accounts lost access. @ask-llm/gemini-mcp still installs, but non-enterprise accounts get actionable guidance instead of output. On a subscription plan, use Antigravity (Google's sanctioned successor, covered by AI Pro/Ultra), Codex, Claude, or Ollama. Announcement

Fallbacks fire only under each provider's documented conditions (quota for Gemini/Codex, overload for Claude, rate limit for Antigravity). Grok and Ollama never substitute a model: Grok sends the exact harness catalog ID unchanged, and Ollama returns a clear ollama pull error if the requested model isn't local. Full details in Model Selection.

MCP gives your assistant the tools. The plugin, @ask-llm/plugin, adds the workflows: slash-command reviews with a validation pipeline, multi-model brainstorming, and opt-in continuous pair review.

/plugin marketplace add Lykhoyda/ask-llm
/plugin install ask-llm@ask-llm-plugins

Review agents follow a 4-phase pipeline inspired by Anthropic's code-review plugin: context gathering, prompt construction with explicit false-positive exclusions, synthesis, and source-level validation of each finding.

See the plugin docs for hooks, agents, and configuration.

Session-capable ask-* tools accept an optional sessionId and return a structured AskResponse (provider, response, model, sessionId, usage) via MCP outputSchema alongside the human-readable text. Codex requires sessionId: "" on the first call for a resumable thread. The orchestrator also exposes usage://current-session as an MCP Resource for live JSON snapshots.

ask codex to review the changes in src/auth.ts for security issues
ask claude for an independent opinion on this architecture        (from Codex or another non-Claude client)
ask antigravity to debate the plan in docs/design.md
ask ollama to explain src/config.ts                                 (runs locally, nothing leaves your machine)
ask gemini to summarize @. the current directory                    (1M+ context; @ syntax is Gemini-only)
use multi-llm to compare what codex and grok think about this approach

More patterns in How to Ask and Multi-Turn Sessions.

The @ask-llm/mcp binary (ask-llm-mcp) starts the MCP server when run with no arguments. With arguments it's a CLI; ask-llm-mcp --help is the canonical reference.

# Diagnose your setup: Node version, PATH, provider CLI versions, env vars
npx @ask-llm/mcp doctor                       # human-readable
npx @ask-llm/mcp doctor --json                # full JSON, exit 1 on error
npx @ask-llm/mcp doctor --format toon         # bounded, versioned agent-facing TOON pilot
npx @ask-llm/mcp doctor --format toon --full  # full TOON escape hatch

# Interactive multi-provider REPL: switch providers, persist sessions, watch usage live
npx @ask-llm/mcp repl

The REPL keeps a session per provider (/provider codex, /new, /sessions, /usage) and inherits all executor behavior: quota fallback, stream-json output for Gemini, native session resume.

Install and authenticate whichever providers you want to consult. The unified server detects what's present.

Package	What it is	Version	Downloads
@ask-llm/mcp	Unified MCP server (recommended): all providers, multi-llm, ask-cursor-agent, doctor, REPL
@ask-llm/plugin	Claude Code + Cursor Agent + Pi host package (skills, agents, hooks)
@ask-llm/codex-mcp	Codex-only MCP server
@ask-llm/claude-mcp	Claude-only MCP server
@ask-llm/grok-mcp	Grok-only MCP server
@ask-llm/antigravity-mcp	Antigravity-only MCP server
@ask-llm/ollama-mcp	Ollama-only MCP server
@ask-llm/gemini-mcp	Gemini-only MCP server

• Docs site: lykhoyda.github.io/ask-llm — Getting Started, How It Works, Troubleshooting
• For AI agents: llms.txt · llms-full.txt

Contributions are welcome. Start with the open issues and CONTRIBUTING.md.

MIT. See LICENSE.

Disclaimer: Ask LLM is an unofficial, third-party tool and is not affiliated with, endorsed, or sponsored by Anthropic, Google, OpenAI, or xAI.