Install
$ agentstack add mcp-cr7258-higress-ai-search-mcp-server ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
[](https://mseep.ai/app/cr7258-higress-ai-search-mcp-server)
Higress AI-Search MCP Server
Overview
A Model Context Protocol (MCP) server that provides an AI search tool to enhance AI model responses with real-time search results from various search engines through Higress ai-search feature.
Demo
Cline
https://github.com/user-attachments/assets/60a06d99-a46c-40fc-b156-793e395542bb
Claude Desktop
https://github.com/user-attachments/assets/5c9e639f-c21c-4738-ad71-1a88cc0bcb46
Features
- Internet Search: Google, Bing, Quark - for general web information
- Academic Search: Arxiv - for scientific papers and research
- Internal Knowledge Search
Prerequisites
Configuration
The server can be configured using environment variables:
HIGRESS_URL(optional): URL for the Higress service (default:http://localhost:8080/v1/chat/completions).MODEL(required): LLM model to use for generating responses.INTERNAL_KNOWLEDGE_BASES(optional): Description of internal knowledge bases.
Option 1: Using uvx
Using uvx will automatically install the package from PyPI, no need to clone the repository locally.
{
"mcpServers": {
"higress-ai-search-mcp-server": {
"command": "uvx",
"args": [
"higress-ai-search-mcp-server"
],
"env": {
"HIGRESS_URL": "http://localhost:8080/v1/chat/completions",
"MODEL": "qwen-turbo",
"INTERNAL_KNOWLEDGE_BASES": "Employee handbook, company policies, internal process documents"
}
}
}
}
Option 2: Using uv with local development
Using uv requires cloning the repository locally and specifying the path to the source code.
{
"mcpServers": {
"higress-ai-search-mcp-server": {
"command": "uv",
"args": [
"--directory",
"path/to/src/higress-ai-search-mcp-server",
"run",
"higress-ai-search-mcp-server"
],
"env": {
"HIGRESS_URL": "http://localhost:8080/v1/chat/completions",
"MODEL": "qwen-turbo",
"INTERNAL_KNOWLEDGE_BASES": "Employee handbook, company policies, internal process documents"
}
}
}
}
License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
Source & license
This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: cr7258
- Source: cr7258/higress-ai-search-mcp-server
- License: Apache-2.0
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.