Web search

Overview

Web search tools allow your agents to access real-time information from the internet. While agents have extensive knowledge from their training data, that knowledge has a cutoff date. Web search bridges the gap, enabling agents to:

• Find current information about companies, people, and events
• Retrieve the latest news and trends
• Verify facts against up-to-date sources
• Research topics not covered in training data

Web search is most effective when combined with agent reasoning. The agent decides what to search for, interprets results, and synthesizes information from multiple sources.

How it works

Web search in MagOneAI is provided by the web-search MCP server, not a proprietary search engine. The MCP server is multi-provider: it defaults to DuckDuckGo (no API key required) and can be configured with keys for higher-quality or higher-volume providers. The providers wired up today are:

• DuckDuckGo — works out of the box, no API key needed
• Tavily — a search API built for AI agents
• Google Serper — Google results via the Serper API
• Google CSE — Google Custom Search Engine
• Parallel AI — search API built for AI agents

Because search is MCP-backed, the same tooling model applies as for any other tool: agents discover the search tools, call them during reasoning, and the platform handles execution. Each keyed provider has its own API quotas and rate limits, set by your provider plan and API key.

Capabilities

The web-search MCP server exposes two tools to agents:

Search the web

Execute web searches and retrieve ranked results with titles, snippets, and URLs.

Parameters:

• query — search query string
• num_results (optional) — number of results to return (default: 10)
• region (optional) — regional search preference (e.g., "us", "uk", "de")
• language (optional) — language code for results (e.g., "en", "es", "fr")
• safe_search (optional) — content filtering level

Returns: List of search results with title, URL, snippet, and ranking.

Example use case: "Find the latest news about artificial intelligence regulation in the EU."

Retrieve web page content

Fetch and parse the full content of a web page.

Parameters:

• url — web page URL to retrieve
• format (optional) — return format (text, markdown, html)

Returns: Page content with title, body text, and metadata.

Example use case: After finding relevant URLs through search, retrieve full article content for deeper analysis.

Configuration

Web search is set up like any external MCP integration: an operator connects the web-search MCP server and configures it with a search provider and API key.

Use cases

Web search unlocks powerful capabilities across many domains. Here are common patterns and use cases.

Sales intelligence

Research companies and contacts before meetings.

Example workflow:

Agent system prompt:
You are a sales research assistant. Before meetings, you research
the prospect's company, recent news, and key contacts.

For each company, find:
1. Recent press releases or news articles
2. Company size, funding, and growth trajectory
3. Key decision makers in the target department
4. Recent product launches or initiatives
5. Potential pain points we can address

Synthesize this into a pre-meeting brief.

Agent actions:

1. Search for company news: "Acme Corp press releases 2024"
2. Search for funding information: "Acme Corp Series B funding"
3. Search for decision makers: "Acme Corp VP Engineering"
4. Retrieve and parse relevant articles
5. Synthesize findings into a structured brief

Market analysis

Monitor market trends, competitors, and industry developments.

Example workflow:

• Agent searches for industry trend reports
• Retrieves competitor product pages and pricing
• Finds analyst opinions and market forecasts
• Synthesizes information into a market intelligence report

Competitive intelligence

Track competitor activities and announcements.

Example workflow:

• Agent monitors competitor websites for changes
• Searches for competitor mentions in news
• Fetches competitor pages and reads off product features
• Compares against your product offerings
• Generates competitive analysis report

Fact checking

Verify claims against current, authoritative sources.

Example workflow:

• Agent receives a claim to verify
• Searches for authoritative sources on the topic
• Retrieves full articles from credible publications
• Cross-references information across multiple sources
• Returns verification result with source citations

When an agent uses results from the web in a chat response, the sources surface as citations so users can trace each claim back to the page it came from.

Combining with other tools

Web search becomes more powerful when combined with other MagOneAI capabilities.

Web search + RAG

Use web search to supplement internal knowledge bases.

Pattern:

1. Agent searches internal documents via RAG (Retrieval Augmented Generation)
2. If information is missing or outdated, agent searches the web
3. Agent cross-references external information with internal policies
4. Agent synthesizes both sources into a comprehensive answer

Example: "What's our company policy on AI tool usage?" → search internal docs → policy found but mentions specific tools → search web for current tool capabilities → compare with policy → provide informed answer.

Web search + Email

Research topics and send summary reports.

Pattern:

1. Agent receives a research request via email or workflow trigger
2. Agent searches the web for relevant information
3. Agent retrieves and analyzes source pages
4. Agent composes email summary with key findings and citations
5. Agent sends report to stakeholders

Example: Daily competitor monitoring workflow that emails a digest of competitor news each morning.

Web search + Database

Enrich database records with external information.

Pattern:

1. Agent queries database for records needing enrichment
2. For each record, agent searches the web for additional data
3. Agent fetches the relevant pages and reads the information it needs from them
4. Agent updates database with enriched data

Example: CRM enrichment workflow that finds company size, industry, and key contacts for new leads.

Best practices

When you receive search results:
1. Identify the most relevant and recent results
2. Prioritize authoritative sources (company websites, major news outlets)
3. Retrieve full content from top 3-5 results
4. Cross-reference information across sources
5. Synthesize findings, noting any conflicting information

Privacy and compliance

Web search accesses public internet data. Consider these privacy and compliance aspects:

Data handling

• Search queries are sent to the search API provider
• Retrieved content is processed by the agent (LLM provider sees this content)
• Search results are not permanently stored by MagOneAI (unless you explicitly log them)

Sensitive information

Compliance considerations

• GDPR: Web search retrieves publicly available data, but be mindful of how you use personal information found online
• Copyright: Retrieved content is subject to copyright. Don't republish scraped content without permission
• Terms of Service: Respect the terms of service of websites you scrape or retrieve content from

Rate limiting and robots.txt

MagOneAI's web retrieval respects:

• Standard rate limits to avoid overwhelming target websites
• robots.txt directives where appropriate
• HTTP status codes and retry-after headers

Troubleshooting

Next steps