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maccam912
by maccam912

Сервер MCP SearXNG

Сервер протокола управления моделью (MCP) для SearXNG , позволяющий помощникам на основе искусственного интеллекта выполнять поиск в Интернете через экземпляр SearXNG.

Функции

  • Поиск в Интернете с помощью SearXNG посредством простых вызовов API

  • Получить информацию о доступных поисковых системах

  • Настройте параметры поиска, включая категории, языки и параметры безопасного поиска.

Related MCP server: Notes MCP Server

Использование в конфигурации MCP

 "searxng-mcp-server": {
      "command": "uv",
      "args": [
        "run",
        "https://raw.githubusercontent.com/maccam912/searxng-mcp-server/refs/heads/main/server.py",
        "--url",
        "https://searxng.example.com"
      ]
    }

Использование Докера

Вы можете запустить этот сервер MCP с помощью Docker:

# Build the Docker image
docker build -t searxng-mcp-server .

# Run the container
# Replace https://searxng.example.com with your actual SearXNG instance URL
docker run -p 8080:8080 searxng-mcp-server

API-инструменты

Поиск

def search(query: str, categories: Optional[str] = None, engines: Optional[str] = None, 
           language: Optional[str] = None, page: int = 1, time_range: Optional[str] = None,
           safe_search: int = 1)

Получить доступные двигатели

def get_available_engines()

Местное развитие

Требования:

  • Питон 3.11+

  • uv (менеджер пакетов Python)

# Install dependencies
uv sync

# Run the server
uv run server.py --url https://searxng.example.com

Available Tools

2 tools
get_available_enginesB

Get information about available search engines

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

B3.1/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full disclosure burden. While 'Get' implies read-only behavior, description omits details on caching, authentication requirements, whether results are user-specific or global, and what the output structure contains (though output schema exists).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single 6-word sentence with no redundancy. Efficiently front-loaded but arguably too minimal given lack of annotations and contextual guidelines that could have been included without sacrificing clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Adequate for a simple discovery tool with existing output schema (which handles return value documentation). However, misses opportunity to explain relationship to 'search' sibling or define what makes an engine 'available'. Minimal viable description.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Zero input parameters with 100% schema coverage (empty object). Per rubric, baseline score is 4 for zero-parameter tools since there are no semantics to clarify beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States specific verb ('Get') and resource ('available search engines'), distinguishing it from sibling 'search' (which performs searches vs. this which discovers them). However, 'information' is vague regarding what specific data is returned (names, capabilities, endpoints?).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides no guidance on when to use this tool versus the 'search' sibling, nor prerequisites for calling it. Description states what it does but not why or when an agent should invoke it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 2 tool updatesv0.1.0
    • First observedget_available_engines
    • First observedsearch

TDQS

B3.1/5.0

Scored across 2 tools

Disambiguation5/5

The two tools have clearly distinct purposes: get_available_engines retrieves metadata about search engines, while search performs actual searches. There is no overlap or ambiguity between these functions.

Naming Consistency5/5

Both tools follow a consistent verb_noun naming pattern (get_available_engines and search). The naming is straightforward and predictable across the toolset.

Tool Count2/5

With only two tools, the server feels under-scoped for a search functionality domain. While the core search operation is present, typical search-related operations like managing preferences, saving searches, or advanced filtering are missing, making the toolset feel thin.

Completeness2/5

The toolset is severely incomplete for a search server. It lacks essential operations such as configuring search settings, handling search history, or integrating with other data sources. The surface is minimal and does not cover the expected lifecycle of search interactions.

Maintenance

ActivityInactive
ResponsivenessNo issues

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