Web Search Prime Plugin

Web Search Prime Plugin is an MCP server that brings Z.AI's advanced web search capabilities to AI assistants through the Model Context Protocol, providing real-time information retrieval, search result aggregation, and web intelligence features. This MCP bridge connects language models to Z.AI's search infrastructure via a hosted HTTP endpoint, enabling AI assistants to perform web searches, retrieve up-to-date information, and access real-time data that extends beyond the model's training knowledge cutoff.

When to Use This MCP Server

Connect this server when...

• You need AI assistants to access real-time web information and current events beyond their training data
• Your workflow requires up-to-date search results for research, fact-checking, or competitive analysis
• You want to enrich AI conversations with live data from web sources, news articles, and online databases
• You are building research workflows that need to aggregate information from multiple web search results
• You need the AI to verify claims, check current prices, or look up recent developments in any field

Consider alternatives when...

• You only need to fetch specific known URLs rather than performing search queries (use a fetch MCP server)
• Your search needs are limited to a specific platform like GitHub or Stack Overflow with dedicated MCP servers
• You require access to paywalled or subscription-only content that search engines cannot access

Quick Start

Copy
# .mcp.json configuration
{
  "mcpServers": {
    "web-search-prime": {
      "type": "http",
      "url": "https://api.z.ai/api/mcp/web_search_prime/mcp",
      "headers": {
        "Authorization": "Bearer your_api_key"
      }
    }
  }
}

Connection setup:

1. Sign up for a Z.AI account and obtain an API key from the developer portal
2. Add the configuration above to your .mcp.json file with your API key
3. No local server installation needed - connects to the hosted Z.AI endpoint
4. Restart your MCP client to activate web search capabilities

Example tool usage:

# Research a topic
> Search for the latest developments in quantum computing in 2026

# Fact-check information
> Verify whether Company X announced a merger this week

# Competitive analysis
> Search for recent reviews and comparisons of project management tools

Core Concepts

Concept	Purpose	Details
Web Search	Information retrieval	Comprehensive web search across indexed pages returning relevant results with snippets
Real-time Data	Current information	Access to recently published and updated web content beyond the AI model's training cutoff
Result Aggregation	Multi-source synthesis	Combining results from multiple search queries to build comprehensive topic coverage
Hosted Endpoint	Zero-maintenance access	Cloud-hosted MCP server at api.z.ai requiring no local installation or server management
Bearer Auth	API key security	HTTP Authorization header with Bearer token for authenticated access to the search API

Architecture:

+------------------+       +------------------+       +------------------+
|  Z.AI Search     |       |  Web Search MCP  |       |  AI Assistant    |
|  Infrastructure  |<----->|  Hosted Endpoint  |<----->|  (Claude, etc.)  |
|  Web Index       | API   |  api.z.ai        | HTTP  |                  |
+------------------+       +------------------+       +------------------+
        |
        v
+------------------------------------------------------+
|  Search > Results > Snippets > URLs > Real-time Data  |
+------------------------------------------------------+

Configuration

Parameter	Type	Default	Description
Authorization	string	(required)	Bearer token with your Z.AI API key for authenticated search access
url	string	(required)	Z.AI MCP endpoint URL for the web search prime service
max_results	integer	10	Maximum number of search results to return per query
search_region	string	global	Geographic region for search result relevance (global, us, eu, asia)
safe_search	boolean	true	Enable safe search filtering to exclude explicit content from results

Best Practices

1. Craft specific search queries for better results. Rather than using vague search terms, construct targeted queries with relevant keywords, date ranges, and domain specifics. "React 19 server components performance benchmarks 2026" produces better results than "React performance."

2. Cross-reference multiple search results. Do not rely on a single search result for important information. Ask the AI to search from multiple angles and cross-reference findings to establish accuracy. This is especially important for time-sensitive or controversial topics.

3. Use search for verification rather than sole truth. Web search results can contain outdated, biased, or incorrect information. Use search to verify and supplement the AI's existing knowledge rather than treating every search result as authoritative fact.

4. Specify time context in queries when relevant. For rapidly evolving topics, include the year or "latest" in your search queries to prioritize recent content. Without temporal context, search results may include outdated information from older but highly-ranked pages.

5. Monitor API usage to manage costs. Each search query consumes API quota. Structure your research workflow to make efficient use of searches by planning queries upfront rather than performing many incremental searches. Aggregate related questions into comprehensive queries when possible.

Common Issues

Search results appear outdated or irrelevant. The search index may not have crawled the most recent content. Try rephrasing your query with more specific terms or include temporal markers like the current year. For very recent events (within hours), results may not yet be available.

"Unauthorized" error when connecting. Verify your Z.AI API key is correctly set in the Authorization header with the "Bearer " prefix. Check that the key is active and has sufficient quota in your Z.AI developer portal.

Results limited to a small number of sources. The default result count may be conservative. Increase max_results for more comprehensive search coverage. For research-heavy workflows, perform multiple targeted searches with different query angles rather than relying on a single broad search.