About ask-ollama
Ask LLM is an MCP server for developers who want a second model’s review of code or plans from within a coding assistant. It connects authenticated provider accounts and local Ollama models, while leaving edits to the current assistant.
Key features
- 01Cross-model code and plan reviews
- 02Provider account-based access
- 03Local Ollama inference
- 04Optional per-edit pairing
- 05Read-only review controls
Use cases
- 01Review staged changes for bugs
- 02Challenge a project plan
- 03Compare models on a coding task
MCP support
It exposes review capabilities to MCP-compatible coding assistants and configures their connection to model providers. The current assistant remains responsible for applying accepted changes.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
npx -y @ask-llm/ollama-mcpOLLAMA_HOSTOllama server address (default: http://localhost:11434)GMCPT_TIMEOUT_MSTimeout for Ollama execution in milliseconds (default: 300000 = 5 minutes)GMCPT_LOG_LEVELLog verbosity: debug, info, warn, error (default: warn)Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.
Tools
3Saved tool list · updated 2w ago
| Parameter | Type | Required | Description |
|---|---|---|---|
| model | string | No | DO NOT set this parameter unless the user explicitly requests a specific model. The tool uses qwen3.8:27b by default; if the model isn't pulled locally it returns a clear "ollama pull" error rather than substituting another model. |
| prompt | string | Yes | The question, code review request, or analysis task to send to Ollama |
| sessionId | string | No | Optional session ID for multi-turn conversations. Pass an empty string to start a new session (the response will include the new ID); pass a previous [Session ID: ...] value to continue the same chat. Conversation history is stored in /tmp/ask-llm-sessions/ for 24h. |
Details
From the project READMEAsk LLM
Second opinions for coding agents.
Get a second opinion on your code or plan, inside your coding assistant, using the model subscriptions you already have.
For individual developers and small teams who already use a coding assistant and pay for another model subscription: ask a different vendor's model to review your changes or challenge your plan, without API keys, copy-paste, or leaving the session.
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.
Install
You need Node.js 24+ on Linux or macOS. Before your first review, both your coding assistant (for example Claude Code) and the provider you will consult (for example Codex) must be installed and signed in. Ask LLM configures the connection; it does not install providers or sign you in. If a provider CLI such as Codex has never been signed in on this machine, sign in first and rerun setup.
npm i -g @ask-llm/mcp && ask-llm setup
Setup asks you to confirm each detected host and workflow. Inspect the preview, confirm your assistant's registration and workflows, decline the others, then follow any printed manual steps. Restart your assistant or start a new session in your project.
Your first review
With both Claude Code and Codex installed and signed in, open Claude Code in your project and ask:
Ask Codex to review my staged changes for bugs and missing error handling. Check each finding against the source before proposing fixes.
Working in Codex with a Claude subscription? Ask Claude instead. Choose a provider from a different vendor than your current assistant. A successful review names the reviewer and model, cites relevant code, and reports findings or says it found none. Your assistant applies changes after you decide what to accept. If the request fails, run ask-llm doctor and follow the troubleshooting guide for your selected assistant and reviewer. Warnings about providers you do not use do not require installing them or adding API keys.
For plans, try: “Ask Claude to challenge this plan: what assumptions could fail, and what simpler approach would fit our constraints?”
After an on-demand review, pair review can add ongoing feedback. Pairing requires explicit opt-in; setup leaves it off.
Supported hosts
A host is the assistant you work in; a provider is the model you consult.
| Host | Experience |
|---|---|
| Claude Code | Reviews, plan critique, comparisons; isolated reviewers and opt-in per-edit pairing |
| Codex, Cursor, Grok Build, Gemini CLI | Tools and portable workflows; pairing on demand |
| Antigravity | Tools; setup prints a manual step for workflows |
| Pi 0.83.0+ | Native tools and portable workflows; opt-in per-edit pairing |
| Claude Desktop | Tools only |
| OpenCode | Tools and portable workflows; setup verified with fixtures only |
See host compatibility for the complete matrix and manual setup limits, including existing Codex registrations.
Supported providers
| Provider | Access |
|---|---|
| Codex | Your authenticated Codex CLI/account |
| Claude | Your authenticated Claude Code account; consult it from a host other than Claude Code |
| Grok | Authenticated Grok Build, an exact Cursor model, or the explicit metered xAI API option |
| Antigravity | Your authenticated agy subscription; execution is off by default, and opt-in has no read-only guarantee |
| Ollama | Local models on your machine |
| Gemini | An eligible Gemini Code Assist Standard/Enterprise seat |
Cursor Agent can also consult exact models from your Cursor catalog. It is a connection route, with usage governed by your Cursor plan.
Trust and cost
Review runs use read-only provider controls; the assistant you work in remains the editor. Antigravity refuses execution until explicitly enabled and cannot guarantee read-only access after opt-in. Review only material you are allowed to share with the selected provider.
Calls consume your existing provider plan's quota or follow that account's billing. Grok's xAI API is a separate, metered option requiring an API key; Ask LLM never enables billing or overage for you. Ollama supports local inference. Ask LLM sends no telemetry; provider and host data policies still apply.
Agreement between models is not proof of correctness. Validate findings against the code, tests, and your requirements. See data flow and costs and fallbacks.
Migrating from @ask-llm/*
Follow the migration guide before retiring earlier registrations.
Upgrade or remove · Troubleshooting · Documentation
Contributions: CONTRIBUTING.md. Licensed under MIT.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.