My Experience Using Gemini CLI with 6 MCP Servers

I connected 6 MCP servers to Gemini CLI and actually used it for development for a month. Here's my honest review of how useful it really is.

First, let me explain the terms in under 1 minute

• Gemini CLI: A command-line tool that lets you use Google's Gemini model directly from the terminal. (This article is based on Gemini 2.5 Pro as the default model.)
• MCP(Server): Model Context Protocol. Simply put, it's a 'plugin server' that attaches tools and context (data/permissions) to AI. It adds practical capabilities like file editing, git repository exploration, browser automation, and DB queries.
• IDE: An integrated environment that combines a code editor + build/debugging/search and other features needed for development.
• Repository: A space for version-controlling source code and documents. Like GitHub.
• Diff: A comparison result showing file changes (additions/deletions) in 'green/red'.
• Schema: Database structure (tables/columns/types) definition.

Why is MCP important?

Gemini CLI is smart, but it needs tools for real-world tasks like accessing latest data, file editing, git exploration, browser manipulation, and DB analysis. MCP servers fill that gap and connect planning → searching → editing → testing → deployment in one line.

1) Context7 MCP — Pull the latest docs/examples directly

One-line intro: When you're struggling with outdated API examples or false documentation(?), inject version-matched latest references and code snippets directly into your session.

Why it's good

• Greatly reduces errors/hallucinations from API changes
• Get accurate examples matching your library version
• Easy to mix with prompts using "use context7" naturally

Key points

• Real-time, version-specific document/example search from source repositories
• Works with any library as long as documentation is integrated

Practical prompt example (Gemini CLI)

use context7
Goal: Add OAuth to our Next.js app with the latest library version.
Please fetch version-specific docs and a minimal working example.

2) Filesystem MCP — 'Safe editing' for large-scale refactoring

One-line intro: Read/write/move/delete files across your entire project, with clean mass modifications using pattern matching + indentation preservation.

Why it's good

• Check differences with dry-run before complex replacement tasks
• Clear change tracking with Git-style diff
• Security boundary settings to access only specified directories

Key points

• Recursive search, batch editing of multiple files
• Optimal for large codebase refactoring/cleanup

Practical prompt example (Gemini CLI)

use filesystem
Plan: Update all fetch() calls to a new API client and keep indentation.
Do a dry-run first and show a concise diff summary before applying.

3) GitMCP — Reduce hallucinations with 'real' git repository

One-line intro: Read actual documents/code directly from any GitHub (or public git) repository to increase accuracy and relevance.

Why it's good

• Check even small OSS or personal repos directly in their latest state
• Smart search extracts only the essentials without wasting tokens
• OK to fix on a specific repo, but dynamic exploration is also available when needed

Key points

• Supports both public repos and Pages
• Advantageous for generating code that matches your repo's standards and style

Practical prompt example (Gemini CLI)

use gitmcp
Target repo: <owner>/<repo>
Find the current auth flow implementation and summarize key entry points.
Propose a minimal PR diff to add 2FA support.

4) Sequential Thinking MCP — Step-by-step thinking (Plan → Revise → Decide)

One-line intro: Equip your session with structured thinking including problem decomposition, alternative branching, hypothesis-verification, and unnecessary information filtering.

Why it's good

• Provides a systematic framework for app design/research/debugging
• Dynamically adjusts depth and path when new information comes in

Key points

• Multi-step review while preserving context
• Easy to leave design decision rationale as text

Practical prompt example (Gemini CLI)

use sequential-thinking
Goal: Design a plugin system for our CLI.
Break the problem into steps, branch two alternative designs,
then propose a merge plan with trade-offs and a revision cycle.

5) Supabase MCP — Test DB and types all at once

One-line intro: Connect to your Supabase project for schema exploration/queries/migrations/logs, and even automatic TypeScript type generation.

Why it's good

• Safely understand structure with read-only mode
• Extract perfect types based on schema to make frontend/server code robust
• Supports real workflow including branches/edge functions/migrations

Key points

• Enhanced security by specifying project scope
• Real-time logs and advisor for debugging

Practical prompt example (Gemini CLI)

use supabase
Inspect schema and generate strict TypeScript types for our tables.
Produce a typed query example and a safe migration plan.
Enable read-only mode during exploration.

6) Playwright MCP — Browser automation/testing in your hands

One-line intro: Fast and robust automation based on accessibility tree (roles/focus) rather than screenshot matching.

Why it's good

• Supports various engines including Chrome/Firefox/WebKit/Edge
• Rich practical options including profile separation, proxy/network control, trace saving
• Vision mode for screenshot-based interaction also available when needed

Key points

• Viewport/device emulation, service worker blocking, HTTPS error handling
• Stable for testing, scraping, and form automation

Practical prompt example (Gemini CLI)

use playwright
Task: Fill and submit a signup form using accessibility roles.
Run in an isolated profile, save a trace, and retry on network flakiness.
Export a minimal test script we can commit to CI.