ask-gemini-mcp
Provides an interface to the Google Gemini CLI, enabling AI agents to leverage Gemini's massive 1M+ token context window for large-scale codebase analysis, architectural reviews, and structured code editing.
Ask LLM
Package | Type | Version | Downloads |
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Claude Code Plugin |
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MCP servers + Claude Code plugin for AI-to-AI collaboration
Get a second opinion before you ship. Ask LLM lets your AI assistant — Claude Code, Cursor, Claude Desktop, or any of 40+ MCP clients — consult a second model to review your code, debate a plan, or catch a bug it might have missed. Pick the reviewer that fits: OpenAI Codex (GPT-5.5), Google Antigravity (agy), a local Ollama model, or Gemini (1M+ token context). Standard MCP, no prompt hacks.
⚠️ Gemini CLI goes enterprise-only on 2026-06-18: From that date Google restricts Gemini CLI to Gemini Code Assist Standard/Enterprise seats, and free, Google AI Pro, and Ultra accounts lose access.
ask-gemini-mcpstill installs, but a non-enterprise account then surfaces actionable guidance instead of output. Free/Pro users: switch toask-antigravity(the Google-sanctioned successor, subscription-backed via Google AI Pro/Ultra),ask-codex, orask-ollama. Announcement
Why a second opinion?
Your primary AI is confident — but confidence isn't correctness. A second model, with no stake in the first one's answer, catches what it missed.
Second opinion on code — before you commit to an approach, have another model review it independently.
Debate a plan — send an architecture proposal for critique, alternatives, and trade-off analysis.
Review a diff — have a different model analyze your changes to surface issues your primary AI glossed over.
Read more than fits — Gemini and Antigravity's large context windows ingest whole codebases at once.
Keep it local — run reviews through Ollama when nothing can leave your machine.
Related MCP server: SystemPrompt Coding Agent
In action
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-paste between tools.
Quick Start
Claude Code
# All-in-one — auto-detects installed providers
claude mcp add --scope user ask-llm -- npx -y ask-llm-mcpclaude mcp add --scope user gemini -- npx -y ask-gemini-mcp
claude mcp add --scope user codex -- npx -y ask-codex-mcp
claude mcp add --scope user ollama -- npx -y ask-ollama-mcp
claude mcp add --scope user antigravity -- npx -y ask-antigravity-mcpClaude Desktop
Add to claude_desktop_config.json:
{
"mcpServers": {
"ask-llm": {
"command": "npx",
"args": ["-y", "ask-llm-mcp"]
}
}
}{
"mcpServers": {
"gemini": {
"command": "npx",
"args": ["-y", "ask-gemini-mcp"]
},
"codex": {
"command": "npx",
"args": ["-y", "ask-codex-mcp"]
},
"ollama": {
"command": "npx",
"args": ["-y", "ask-ollama-mcp"]
}
}
}Cursor (.cursor/mcp.json):
{
"mcpServers": {
"ask-llm": { "command": "npx", "args": ["-y", "ask-llm-mcp"] }
}
}Codex CLI (~/.codex/config.toml):
[mcp_servers.ask-llm]
command = "npx"
args = ["-y", "ask-llm-mcp"]Any MCP Client (STDIO transport):
{ "command": "npx", "args": ["-y", "ask-llm-mcp"] }Replace ask-llm-mcp with ask-codex-mcp, ask-antigravity-mcp, ask-ollama-mcp, or ask-gemini-mcp for a single provider.
Choose your reviewer
Provider | Best for | Model (default → fallback) | Notes |
Codex | Code reasoning, targeted reviews, architecture critique |
| Requires an OpenAI/Codex account |
Antigravity | A subscription-backed second opinion; larger-context reads |
| Google AI Pro/Ultra plan; one-shot, experimental |
Ollama | Private/local review, zero cost, offline |
| Runs entirely on your machine |
Gemini | Whole-codebase reads (1M+ tokens) |
| ⚠️ Enterprise-gated from 2026-06-18 |
Unified ( | One install for all of the above; fan out in parallel | routes per call | Recommended |
Claude Code Plugin
The Ask LLM plugin adds multi-provider code review, brainstorming, and automated hooks directly into Claude Code:
/plugin marketplace add Lykhoyda/ask-llm
/plugin install ask-llm@ask-llm-pluginsWhat You Get
Feature | Description |
| Parallel Antigravity + Codex review with 4-phase validation pipeline and consensus highlighting (gemini via |
| Gemini-only review with confidence filtering |
| Codex-only review with confidence filtering |
| Local review — no data leaves your machine |
| Subscription-backed review via Google Antigravity ( |
| Multi-LLM brainstorm: Claude Opus researches the topic against real files in parallel with external providers (Gemini/Codex/Ollama), then synthesizes all findings with verified findings weighted higher |
| Side-by-side raw responses from multiple providers, no synthesis — for when you want to see how each provider phrases the same answer |
| Opt-in continuous review — runs Codex against every Edit/Write/MultiEdit when a |
The review agents use 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 details.
Prerequisites
Node.js v20.0.0 or higher (LTS)
At least one provider:
Codex CLI — installed and authenticated
Antigravity CLI (
agy) — installed and logged in once (Google AI Pro/Ultra)Ollama — running locally with a model pulled (
ollama pull qwen3.6:27b)Gemini CLI —
npm install -g @google/gemini-cli && gemini login(enterprise-gated from 2026-06-18)
MCP Tools
Tool | Package | Purpose |
| ask-gemini-mcp | Send prompts to Gemini CLI with |
| ask-gemini-mcp | Get structured OLD/NEW code edit blocks from Gemini |
| ask-gemini-mcp | Retrieve chunks from cached large responses |
| ask-codex-mcp | Send prompts to Codex CLI. GPT-5.5 with mini fallback. Native session resume via |
| ask-ollama-mcp | Send prompts to local Ollama. Fully private, zero cost. Server-side conversation replay via |
| ask-antigravity-mcp | Send a prompt to Google Antigravity ( |
| ask-llm-mcp | Unified orchestrator — pick provider per call. Fan out to all installed providers |
| ask-llm-mcp | Dispatch the same prompt to multiple providers in parallel; returns per-provider responses + usage in one call |
| all | Per-session token totals, fallback counts, breakdowns by provider/model — all in-memory, no persistence |
| ask-llm-mcp | Self-diagnosis: Node version, PATH resolution, provider CLI presence + versions. Read-only |
| all | Connection test — verify MCP setup |
All ask-* tools accept an optional sessionId parameter for multi-turn conversations and now return a structured AskResponse (provider, response, model, sessionId, usage) via MCP outputSchema alongside the human-readable text. The orchestrator (ask-llm-mcp) also exposes usage://current-session as an MCP Resource for live JSON snapshots.
Usage Examples
ask codex to review the changes in src/auth.ts for security issues
ask antigravity to debate this architecture plan in docs/design.md
ask ollama to explain src/config.ts (runs locally, no data sent anywhere)
ask gemini to summarize @. the current directory (1M+ context, @ is Gemini-only)
use multi-llm to compare what codex and gemini think about this approachCLI Subcommands
The orchestrator binary (ask-llm-mcp) supports two CLI modes alongside the default MCP server:
# Interactive multi-provider REPL — switch providers, persist sessions, see usage live
npx ask-llm-mcp repl
# Diagnose your setup — Node version, PATH, provider CLI versions, env vars
npx ask-llm-mcp doctor # human-readable
npx ask-llm-mcp doctor --json # machine-readable, exit 1 on errorThe REPL ships sessions per provider (/provider gemini, /provider codex, /new, /sessions, /usage) and inherits all the executor behavior (quota fallback, stream-json output for Gemini, native session resume).
Models
Provider | Default | Fallback |
Gemini |
|
|
Codex |
|
|
Ollama |
| — (local; errors if the model isn't pulled) |
Gemini and Codex automatically fall back to a lighter model on quota errors. Ollama runs locally and never substitutes a model — if the requested model isn't pulled, it returns a clear ollama pull error.
Documentation
Docs site: lykhoyda.github.io/ask-llm
AI-readable: llms.txt | llms-full.txt
Contributing
Contributions are welcome! See open issues for things to work on.
License
MIT License. See LICENSE for details.
Disclaimer: This is an unofficial, third-party tool and is not affiliated with, endorsed, or sponsored by Google or OpenAI.
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Maintenance
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