ask-gemini-mcp

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.

One prompt. A second model reviews independently; your assistant applies the fix — no copy-paste between tools.

# All-in-one — auto-detects installed providers claude mcp add --scope user ask-llm -- npx -y @ask-llm/mcp

claude mcp add --scope user gemini -- npx -y @ask-llm/gemini-mcp claude mcp add --scope user codex -- npx -y @ask-llm/codex-mcp claude mcp add --scope user ollama -- npx -y @ask-llm/ollama-mcp claude mcp add --scope user antigravity -- npx -y @ask-llm/antigravity-mcp

Pi is a host harness, not another consulted provider. Install the canonical dual-host package; it exposes the shared skills plus native provider tools because Pi intentionally has no built-in MCP client:

Invoke/skill:codex-review,/skill:multi-review,/skill:compare,/skill:brainstorm, or describe the workflow naturally. The package registersask-codex,ask-gemini,ask-ollama,ask-antigravity, and deterministic concurrentask-multitools. Provider CLI authentication is unchanged and separate from Pi's host-model login.

Pi codex-pair requires the repository marker, Pi project trust,andinteractive user-owned consent via/codex-pair; a committed marker alone never authorizes source transfer or cost. Pi surfaces findings non-blockingly and does not claim Claude's blocking Stop-gate or one-shot print parity. Independentfable-reviewremains Claude Code-only and is excluded from Pi.

@ask-llm/pluginis one package, version, release lifecycle, and canonical skill corpus. Claude Code loads its existing marketplace agents/hooks; Pi loads explicit native tools, portable skill adapters, and a thin lifecycle extension.

TheAsk LLM pluginadds multi-provider code review, brainstorming, and automated hooks directly into Claude Code:

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

Session-capableask-*tools accept an optionalsessionIdparameter and return a structuredAskResponse(provider, response, model, sessionId, usage) via MCPoutputSchemaalongside the human-readable text. Codex requiressessionId: ""on the first call for a resumable thread; omitting it makes that call ephemeral. The orchestrator (@ask-llm/mcp) also exposesusage://current-sessionas 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 MCP client) 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 approach

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 error

The 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).

Gemini, Codex, Claude, and Antigravity automatically fall back under their documented provider-specific conditions. Ollama runs locally and never substitutes a model — if the requested model isn't pulled, it returns a clearollama pullerror.

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

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