Web Research Assistant MCP Server

Comprehensive Model Context Protocol (MCP) server that provides web research and discovery capabilities. Includes 13 tools, 4 resources, and 5 prompts for searching, crawling, and analyzing web content, powered by your local Docker SearXNG instance, Exa AI neural search, the crawl4ai project, and Pixabay API:

1. web_search — federated search across multiple engines via SearXNG
2. search_examples — find code examples, tutorials, and articles (defaults to recent content)
3. search_images — find high-quality stock photos, illustrations, and vectors via Pixabay
4. crawl_url — full page content extraction with advanced crawling
5. package_info — detailed package metadata from npm, PyPI, crates.io, Go
6. package_search — discover packages by keywords and functionality
7. github_repo — repository health metrics and development activity
8. translate_error — find solutions for error messages and stack traces from Stack Overflow (auto-detects CORS, fetch, and web errors)
9. api_docs — auto-discover and crawl official API documentation with examples (works for any API - no hardcoded URLs)
10. extract_data — extract structured data (tables, lists, fields, JSON-LD) from web pages with automatic detection
11. compare_tech — compare technologies side-by-side with NPM downloads, GitHub stars, and aspect analysis (React vs Vue, PostgreSQL vs MongoDB, etc.)
12. get_changelog — NEW! Get release notes and changelogs with breaking change detection (upgrade safely from version X to Y)
13. check_service_status — NEW! Instant health checks for 25+ services (Stripe, AWS, GitHub, OpenAI, etc.) - "Is it down or just me?"

All tools feature comprehensive error handling, response size limits, usage tracking, and clear documentation for optimal AI agent integration.

MCP Resources (Direct Data Lookups)

• package://{registry}/{name} - Package info from npm, PyPI, crates.io, or Go modules
• github://{owner}/{repo} - Repository information and health metrics
• status://{service} - Service health status for 120+ services
• changelog://{registry}/{package} - Package release notes and changelogs

MCP Prompts (Reusable Workflows)

• research_package - Comprehensive package evaluation
• debug_error - Structured error debugging with solutions
• compare_technologies - Side-by-side technology comparison
• evaluate_repository - GitHub repository health assessment
• check_service_health - Multi-service status monitoring

Quick Start

Option 1: Full Docker Setup (Recommended)

Everything runs in Docker - no Python installation needed:

./docker-start.sh

This starts both SearXNG and the MCP server in containers. See DOCKER_SETUP.md for details.

Option 2: Python + Docker SearXNG

1. Set up SearXNG (5 minutes):

   # Using Docker (recommended)
   docker run -d -p 2288:8080 searxng/searxng:latest
   

   Then configure search engines - see SEARXNG_SETUP.md for optimized settings.

2. Install the MCP server:

   uvx web-research-assistant  # or: pip install web-research-assistant
   

3. Configure Claude Desktop - add to claude_desktop_config.json:

   {
     "mcpServers": {
       "web-research-assistant": {
         "command": "uvx",
         "args": ["web-research-assistant"]
       }
     }
   }
   

4. Restart Claude Desktop and start researching!

⚠️ For best results: Configure SearXNG with GitHub, Stack Overflow, and other code-focused search engines. See SEARXNG_SETUP.md for the recommended configuration.

Prerequisites

Required

• Python 3.10+
• A running SearXNG instance on http://localhost:2288
  • 📖 See SEARXNG_SETUP.md for complete Docker setup guide
  • ⚠️ IMPORTANT: For best results, enable these search engines in SearXNG:
    • GitHub, Stack Overflow, GitLab (for code search - critical!)
    • DuckDuckGo, Brave (for web search)
    • MDN, Wikipedia (for documentation)
    • Reddit, HackerNews (for tutorials and discussions)
    • See SEARXNG_SETUP.md for the full optimized configuration

Optional

• Exa API key for neural search - Get API key (recommended for better search results)
• Pixabay API key for image search - Get free key
• Playwright browsers for advanced crawling (auto-installed with crawl4ai-setup)

Developer Setup (if running from source)

uv tool install uv  # if you do not already have uv
uv sync              # creates the virtual environment
uv run crawl4ai-setup  # installs Chromium for crawl4ai

You can also use pip install -r requirements.txt if you prefer pip over uv.

Installation

Option 1: Using uvx (Recommended - No installation needed!)

uvx web-research-assistant

This runs the server directly from PyPI without installing it globally.

Option 2: Install with pip

pip install web-research-assistant
web-research-assistant

Option 3: Install with uv

uv tool install web-research-assistant
web-research-assistant

By default the server communicates over stdio, which makes it easy to wire into Claude Desktop or any other MCP host.

MCP Client Configuration

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

Option 1: Using uvx (Recommended - No installation needed!)

{
  "mcpServers": {
    "web-research-assistant": {
      "command": "uvx",
      "args": ["web-research-assistant"]
    }
  }
}

Option 2: Using installed package

{
  "mcpServers": {
    "web-research-assistant": {
      "command": "web-research-assistant"
    }
  }
}

OpenCode

Add to ~/.config/opencode/opencode.json:

Using uvx (Recommended)

{
  "mcp": {
    "web-research-assistant": {
      "type": "local",
      "command": ["uvx", "web-research-assistant"],
      "enabled": true
    }
  }
}

Using installed package

{
  "mcp": {
    "web-research-assistant": {
      "type": "local",
      "command": ["web-research-assistant"],
      "enabled": true
    }
  }
}

Development (Running from source)

For Claude Desktop:

{
  "mcpServers": {
    "web-research-assistant": {
      "command": "uv",
      "args": [
        "--directory",
        "/ABSOLUTE/PATH/TO/web-research-assistant",
        "run",
        "web-research-assistant"
      ]
    }
  }
}

For OpenCode:

{
  "mcp": {
    "web-research-assistant": {
      "type": "local",
      "command": [
        "uv",
        "--directory",
        "/ABSOLUTE/PATH/TO/web-research-assistant",
        "run",
        "web-research-assistant"
      ],
      "enabled": true
    }
  }
}

Restart your MCP client afterwards. The MCP tools will be available immediately.

Tool behavior

Tool	When to use	Arguments
web_search	Use first to gather recent information and URLs from SearXNG. Returns 1–10 ranked snippets with clickable URLs.	query (required), reasoning (required), optional category (defaults to general), and max_results (defaults to 5).
search_examples	Find code examples, tutorials, and technical articles. Optimized for technical content with optional time filtering. Perfect for learning APIs or finding usage patterns.	query (required, e.g., "Python async examples"), reasoning (required), content_type (code/articles/both, defaults to both), time_range (day/week/month/year/all, defaults to all), optional max_results (defaults to 5).
search_images	Find high-quality royalty-free stock images from Pixabay. Returns photos, illustrations, or vectors. Requires PIXABAY_API_KEY environment variable.	query (required, e.g., "mountain landscape"), reasoning (required), image_type (all/photo/illustration/vector, defaults to all), orientation (all/horizontal/vertical, defaults to all), optional max_results (defaults to 10).
crawl_url	Call immediately after search when you need the actual article body for quoting, summarizing, or extracting data.	url (required), reasoning (required), optional max_chars (defaults to 8000 characters).
package_info	Look up specific npm, PyPI, crates.io, or Go package metadata including version, downloads, license, and dependencies. Use when you know the package name.	name (required package name), reasoning (required), registry (npm/pypi/crates/go, defaults to npm).
package_search	Search for packages by keywords or functionality (e.g., "web framework", "json parser"). Use when you need to find packages that solve a specific problem.	query (required search terms), reasoning (required), registry (npm/pypi/crates/go, defaults to npm), optional max_results (defaults to 5).
github_repo	Get GitHub repository health metrics including stars, forks, issues, recent commits, and project details. Use when evaluating open source projects.	repo (required, owner/repo or full URL), reasoning (required), optional include_commits (defaults to true).
translate_error	Find Stack Overflow solutions for error messages and stack traces. Auto-detects language/framework, extracts key terms (CORS, map, undefined, etc.), filters irrelevant results, and prioritizes Stack Overflow solutions. Handles web-specific errors (CORS, fetch).	error_message (required stack trace or error text), reasoning (required), optional language (auto-detected), optional framework (auto-detected), optional max_results (defaults to 5).
api_docs	Auto-discover and crawl official API documentation. Dynamically finds docs URLs using patterns (docs.{api}.com, {api}.com/docs, etc.), searches for specific topics, crawls pages, and extracts overview, parameters, examples, and related links. Works for ANY API - no hardcoded URLs. Perfect for API integration and learning.	api_name (required, e.g., "stripe", "react"), topic (required, e.g., "create customer", "hooks"), reasoning (required), optional max_results (defaults to 2 pages).
extract_data	Extract structured data from HTML pages. Supports tables, lists, fields (via CSS selectors), JSON-LD, and auto-detection. Returns clean JSON output. More efficient than parsing full page text. Perfect for scraping pricing tables, package specs, release notes, or any structured content.	url (required), reasoning (required), extract_type (table/list/fields/json-ld/auto, defaults to auto), optional selectors (CSS selectors for fields mode), optional max_items (defaults to 100).
compare_tech	Compare 2-5 technologies side-by-side. Auto-detects category (framework/database/language) and gathers data from NPM, GitHub, and web search. Returns structured comparison with popularity metrics (downloads, stars), performance insights, and best-use summaries. Fast parallel processing (3-4s).	technologies (required list of 2-5 names), reasoning (required), optional category (auto-detects if not provided), optional aspects (auto-selected by category), optional max_results_per_tech (defaults to 3).
get_changelog	NEW! Get release notes and changelogs for package upgrades. Fetches GitHub releases, highlights breaking changes, and provides upgrade recommendations. Answers "What changed in version X → Y?" and "Are there breaking changes?" Perfect for planning dependency updates.	package (required name), reasoning (required), optional registry (npm/pypi/auto, defaults to auto), optional max_releases (defaults to 5).
check_service_status	NEW! Instantly check if external services are experiencing issues. Covers 25+ popular services (Stripe, AWS, GitHub, OpenAI, Vercel, etc.). Returns operational status, current incidents, and component health. Critical for production debugging - know immediately if the issue is external. Response time < 2s.	service (required name, e.g., "stripe", "aws"), reasoning (required).

Results are automatically trimmed (default 8 KB) so they stay well within MCP response expectations. If truncation happens, the text ends with a note reminding the model that more detail is available on request.

Resources

MCP Resources provide direct data access via URI templates - perfect for quick lookups without tool calls.

Resource URI	Description	Example
package://{registry}/{name}	Package metadata (version, downloads, license, dependencies)	package://npm/express
github://{owner}/{repo}	Repository info (stars, forks, issues, activity)	github://facebook/react
status://{service}	Service health status	status://stripe
changelog://{registry}/{package}	Release notes and changelogs	changelog://npm/typescript

Prompts

MCP Prompts are reusable message templates that guide AI assistants through common workflows.

Prompt	Arguments	Use Case
research_package	package_name, registry	Evaluate a package before adding it as a dependency
debug_error	error_message, language (optional), framework (optional)	Debug an error with context and solutions
compare_technologies	tech1, tech2, tech3 (optional), tech4 (optional), tech5 (optional)	Compare frameworks, databases, or languages
evaluate_repository	owner, repo	Assess a GitHub project's health and activity
check_service_health	services (comma-separated)	Monitor multiple services at once

Configuration

Environment variables let you adapt the server without touching code:

Variable	Default	Description
SEARXNG_BASE_URL	http://localhost:2288/search	Endpoint queried by web_search.
SEARXNG_DEFAULT_CATEGORY	general	Category used when none is provided.
SEARXNG_DEFAULT_RESULTS	5	Default number of search hits.
SEARXNG_MAX_RESULTS	10	Hard cap on hits per request.
SEARXNG_CRAWL_MAX_CHARS	8000	Default character budget for crawl_url.
MCP_MAX_RESPONSE_CHARS	8000	Overall response limit applied to every tool reply.
SEARXNG_MCP_USER_AGENT	web-research-assistant/0.1	User-Agent header for outward HTTP calls.
PIXABAY_API_KEY	(empty)	API key for Pixabay image search. Get free key at pixabay.com/api/docs.
EXA_API_KEY	(empty)	API key for Exa AI neural search. Get key at dashboard.exa.ai.
SEARCH_PROVIDER	auto	Search provider: exa (Exa only), searxng (SearXNG only), or auto (try Exa first, fallback to SearXNG).
MCP_USAGE_LOG	~/.config/web-research-assistant/usage.json	Location for usage analytics data.

Development

The codebase is intentionally modular and organized:

web-research-assistant/
├── src/searxng_mcp/     # Source code
│   ├── config.py        # Configuration and environment
│   ├── search.py        # SearXNG integration
│   ├── exa.py           # Exa AI neural search client
│   ├── crawler.py       # Crawl4AI wrapper
│   ├── images.py        # Pixabay client
│   ├── registry.py      # Package registries (npm, PyPI, crates, Go)
│   ├── github.py        # GitHub API client
│   ├── errors.py        # Error parser (language/framework detection)
│   ├── api_docs.py      # API docs discovery (NO hardcoded URLs)
│   ├── tracking.py      # Usage analytics
│   └── server.py        # MCP server + 13 tools
├── docs/                # Documentation (27 files)
└── [config files]

Each module is well under 400 lines, making the codebase easy to understand and extend.

Usage Analytics

All tools automatically track usage metrics including:

• Tool invocation counts and success rates
• Response times and performance trends
• Common use case patterns (via the reasoning parameter)
• Error frequencies and types

Analytics data is stored in ~/.config/web-research-assistant/usage.json and can be analyzed to optimize tool usage and identify patterns. Each tool requires a reasoning parameter that helps categorize why tools are being used, enabling better analytics and insights.

Note: As of the latest update, the reasoning parameter is required for all tools (previously optional with defaults). This ensures meaningful analytics data collection.

Documentation

Comprehensive documentation is available in the docs/ directory:

• Project Status - Current status, metrics, roadmap
• API Docs Implementation - NEW tool documentation
• Error Translator Design - Error translator details
• Tool Ideas Ranked - Prioritization and progress
• SearXNG Configuration - Recommended setup
• Quick Start Examples - Usage examples

See the docs README for a complete index.