Skip to main content
Glama

URL-Context-MCP MCP

by nanameru

URL-Context-MCP MCP Server

The URL-Context-MCP MCP Server provides a tool to analyze and summarize the content of URLs using Google Gemini's URL Context capability via the Gemini API.

Now also supports optional grounding with Google Search alongside URL Context. The server is designed to follow prompt-only orchestration: control whether to search or scrape via the instruction text you provide.

Installation

Prerequisites

  • Node.js 18+
  • Set GOOGLE_API_KEY in your environment

Get a Gemini API key

  • Sign in to Google AI for Developers and create an API key
  • Copy the generated key and set it as GOOGLE_API_KEY for this server
    • Cursor (project): add to .cursor/mcp.json under env
    • Claude CLI one-liner example: shown below
    • Or set it in your shell before launching

Published Package

This MCP server is now available as a published npm package: @taiyokimura/url-context-mcp

  • No need to clone the repository locally
  • Can be run directly via npx @taiyokimura/url-context-mcp@latest
  • See setup instructions below for Cursor and Claude Code

Build locally

cd /Users/kimurataiyou/url-context-mcp npm i npm run build

Setup: Claude Code (CLI)

Use this one-line command (replace with your real API key):

claude mcp add URL-Context-MCP -s user -e GOOGLE_API_KEY="sk-your-real-key" -- npx @taiyokimura/url-context-mcp@latest

To remove the server from Claude Code:

claude mcp remove URL-Context-MCP

Setup: Cursor

Create .cursor/mcp.json at your repository root:

{ "mcpServers": { "URL-Context-MCP": { "command": "npx", "args": ["@taiyokimura/url-context-mcp@latest"], "env": { "GOOGLE_API_KEY": "sk-your-real-key" }, "autoStart": true } } }

Other Clients and Agents

Install in VS Code
Install in VS Code Insiders

Or add via CLI:

code --add-mcp '{"name":"URL-Context-MCP","command":"npx","args":["@taiyokimura/url-context-mcp@latest"],"env":{"GOOGLE_API_KEY":"sk-your-real-key"}}'

Follow the MCP install guide and use the standard config above:

  • Guide: https://modelcontextprotocol.io/quickstart/user

Add MCP Server with:

  • Command: npx
  • Args: ["@taiyokimura/url-context-mcp@latest"]
  • Env: GOOGLE_API_KEY=sk-your-real-key

Advanced settings → Extensions → Add custom extension:

  • Type: STDIO
  • Command: npx
  • Args: @taiyokimura/url-context-mcp@latest
  • Enabled: true

Example ~/.config/opencode/opencode.json:

{ "$schema": "https://opencode.ai/config.json", "mcp": { "url-context-mcp": { "type": "local", "command": [ "npx", "@taiyokimura/url-context-mcp@latest" ], "enabled": true } } }

Open Qodo Gen (VSCode/IntelliJ) → Connect more tools → + Add new MCP → Paste the standard config JSON → Save.

Follow Windsurf MCP documentation and use the standard config above:

  • Docs: https://docs.windsurf.com/windsurf/cascade/mcp

Configuration (Env)

  • GOOGLE_API_KEY: Your Gemini API key

Available Tools

  • analyze_urls
    • inputs:
      • urls: string | string[] (1-20 total)
      • instruction?: string
      • model?: string (default: gemini-2.5-flash)
      • use_google_search?: boolean (default: false) — enable grounding with Google Search in addition to URL Context

Prompt recipes (prompt-only orchestration)

  • Scraping-only (user provided URLs). Example instruction:
    • "ユーザーが貼ったこれらのURLのみをURLコンテキストで解析し、要約・キーファクト・引用URLを日本語で提示。外部検索は禁止。取得失敗は明示。"
  • Research with search + scraping, iterative up to 5 rounds. Example instruction:
    • "以下のテーマを調査。まずGoogle検��で候補を収集し、引用する全URLは必ずURLコンテキストで取得・要約・統合。カバレッジ不十分なら最大5回まで再検索・再収集して補完。日本語で簡潔に要約・キーファクト・引用URLを提示。"

Example invocation (MCP tool call)

{ "name": "analyze_urls", "arguments": { "urls": "https://note.com/hawk735/n/nbc585d0774df", "instruction": "日本語で、要約・キーファクト・引用URLを簡潔に", "use_google_search": true } }

Scraping-only example

{ "name": "analyze_urls", "arguments": { "urls": ["https://example.com/post1", "https://example.com/post2"], "instruction": "ユーザーが貼ったこれらのURLのみをURLコンテキストで解析し、要約・キーファクト・引用URLを日本語で提示。外部検索は禁止。取得失敗は明示。" } }

Research + scraping (iterative) example

{ "name": "google_search", "arguments": { "query": "最新のNext.js 14のApp Routerのベストプラクティス", "instruction": "まずGoogle検索で候補を収集し、引用する全URLは必ずURLコンテキストで取得・要約・統合。カバレッジ不十分なら最大5回まで再検索・再収集して補完。日本語で簡潔に要約・キーファクト・引用URLを提示。" } }

Troubleshooting

  • 401 auth errors: verify GOOGLE_API_KEY
  • Ensure Node 18+
  • For npx usage: npx @taiyokimura/url-context-mcp@latest should work without local build
  • For local development: use absolute path to build/index.js

References

Deploy Server
-
security - not tested
F
license - not found
-
quality - not tested

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

The URL-Context-MCP MCP Server provides a tool to analyze and summarize the content of URLs using Google Gemini's URL Context capability via the Gemini API.

Now also supports optional grounding with Google Search alongside URL Context. The server is designed to follow prompt-only orchestration: con

  1. Installation
    1. Prerequisites
    2. Get a Gemini API key
    3. Published Package
    4. Build locally
  2. Setup: Claude Code (CLI)
    1. Setup: Cursor
      1. Other Clients and Agents
        1. Configuration (Env)
          1. Available Tools
            1. Prompt recipes (prompt-only orchestration)
            2. Example invocation (MCP tool call)
          2. Troubleshooting
            1. References

              Related MCP Servers

              • A
                security
                F
                license
                A
                quality
                An MCP (Model Context Protocol) server that provides Google search capabilities and webpage content analysis tools. This server enables AI models to perform Google searches and analyze webpage content programmatically.
                Last updated -
                10
                138
              • A
                security
                A
                license
                A
                quality
                MCP (Model Context Protocol) server that utilizes the Google Gemini Vision API to interact with YouTube videos. It allows users to get descriptions, summaries, answers to questions, and extract key moments from YouTube videos.
                Last updated -
                4
                7
                6
                MIT License
                • Linux
                • Apple
              • -
                security
                A
                license
                -
                quality
                A Model Context Protocol (MCP) server implementation for the Google Gemini language model. This server allows Claude Desktop users to access the powerful reasoning capabilities of Gemini-2.0-flash-thinking-exp-01-21 model.
                Last updated -
                1
                MIT License
              • A
                security
                A
                license
                A
                quality
                Implementation of Model Context Protocol (MCP) server that provides tools for accessing Google Cloud's Vertex AI Gemini models, supporting features like web search grounding and direct knowledge answering for coding assistance and general queries.
                Last updated -
                20
                11
                85
                MIT License
                • Linux
                • Apple

              View all related MCP servers

              MCP directory API

              We provide all the information about MCP servers via our MCP API.

              curl -X GET 'https://glama.ai/api/mcp/v1/servers/nanameru/url-context-mcp'

              If you have feedback or need assistance with the MCP directory API, please join our Discord server