MetaSearchMCP — security grade SAFE, quality 71/100

Security audit verdict: SAFE · quality 71/100

No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by gefsikatsinelou · MCP Server · ★ 56

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

🔒 Is MetaSearchMCP safe to install? View the security audit →

About MetaSearchMCP

MetaSearchMCP Open-source metasearch backend for MCP, AI agents, and LLM workflows. MetaSearchMCP aggregates results from multiple search providers, normalizes them into a stable JSON schema, and exposes both an HTTP API and an MCP server for agent tooling. Positioning MCP-first metasearch backend Structured search API for AI pipelines Multi-provider search orchestration with deduplication and fallback Python FastAPI alternative to browser-first metasearch projects Why It Exists Most search aggregators are designed around browser UX: HTML pages, pagination, and interactive result cards. Agents and LLM workflows need a different contract: predictable JSON, stable field names, partial-failure tolerance, and provider-level execution metadata. MetaSearchMCP is built for that machine-consumable workflow. The design is centered on search orchestration, normalized contracts, and MCP integration.

agent-toolsai-agentsgoogle-searchgoogle-search-apillmllm-toolsmcpmcp-servermetasearchmodel-context-protocol

Quick Facts

Stars56
Forks2
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score70.7208433527052/100
Open Issues2
Last Updated2026-09-20
Created2026-04-14
Platformsbrowser, mcp, python
Est. Tokens~16k

MetaSearchMCP alternative? Top 6 similar tools

Looking for a MetaSearchMCP alternative? If you're comparing MetaSearchMCP with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

  • webfetch by firish · ⭐ 54

    Own your LLM's web search: a local search->fetch->rank pipeline that replaces hosted web_search tools. Measure

  • claude-prompts by minipuft · ⭐ 182

    MCP server for reusable prompt templates, multi-step workflow chains, and quality gates — compose agentic work

  • gopher-mcp by GopherSecurity · ⭐ 147

    C++ MCP SDK - build Model Context Protocol (MCP) servers and clients in C++ / CPP. Enterprise-grade security,

  • agent-search-mcp by lennney · ⭐ 111

    Free-first Chinese and English web search MCP using zero-key sources and inspectable evidence.

  • oxylabs-mcp by oxylabs · ⭐ 104

    Official Oxylabs MCP integration

  • cortex-scout by cortex-works · ⭐ 69

    A unified web extraction and stateful automation engine for AI. Replaces heavy testing frameworks with token-o

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Frequently Asked Questions

What is MetaSearchMCP?

MetaSearchMCP is Open-source metasearch backend, MCP server, and AI search API for LLM agents. Python FastAPI search gateway with Google search via SerpBase and Serper, multi-engine search aggregation, structured JSON. It is categorized as a MCP Server with 56 GitHub stars.

What programming language is MetaSearchMCP written in?

MetaSearchMCP is primarily written in Python. It covers topics such as agent-tools, ai-agents, google-search.

How do I install or use MetaSearchMCP?

You can find installation instructions and usage details in the MetaSearchMCP GitHub repository at github.com/gefsikatsinelou/MetaSearchMCP. The project has 56 stars and 2 forks, indicating an active community.

What license does MetaSearchMCP use?

MetaSearchMCP is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to MetaSearchMCP?

The top alternatives to MetaSearchMCP on Agent Skills Hub include webfetch, claude-prompts, gopher-mcp. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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