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yiGmMk

yiGmMk/mcp-server

by yiGmMk
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Python
Remote

mcp-server

学习写 mcp server

安装 (cline)

Installing via Smithery

To install mcp-server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @yiGmMk/mcp-server --client claude

前置依赖

• Python 3.12 or newer • uv package manager

没有安装uv的,请参考文档uv 安装文档

macos或linux可使用如下命令安装

curl -LsSf https://astral.sh/uv/install.sh | sh

windwos,在powershell下安装

powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

配置文件

优先使用下面这种配置方式

{
    "mcpServers": {
        "yiGmMk/mcp-server": {
            "command": "uv",
            "args": [
                "--directory",
                "/path/to/your/mcp-server",
                "run",
                "main.py"
            ],
            "env": {
                "JINA_API_KEY": "jina_api_key,请从https://jina.ai/reader获取",
                "GOOGLE_AI_STUDIO_KEY": "Google AI Studio api key,请从https://aistudio.google.com/apikey获取",
                "PYTHONIOENCODING": "utf-8"
            },
            "disabled": false,
            "autoApprove": []
        }
    }
}

或使用venv(增加环境变量配置)

{
    "mcpServers": {
        "yiGmMk/mcp-server": {
            "command": "uv",
            "args": [
                "run",
                "/path/to/your/mcp-server/main.py"
            ],
            "env": {
                "VIRTUAL_ENV": "/path/to/your/mcp-server/.venv",
                "JINA_API_KEY": "jina_api_key,请从https://jina.ai/reader获取",
                "GOOGLE_AI_STUDIO_KEY": "Google AI Studio api key,请从https://aistudio.google.com/apikey获取",
                "PYTHONIOENCODING": "utf-8"
            },
            "disabled": false,
            "autoApprove": []
        }
    }
}

Related MCP server: Eyes-MCP

jina.ai

jina.ai提供的各种工具,如搜索,读取网页...

TODO

Available Tools

4 tools
fetchB

使用 r.jina.ai 读取 URL 并获取其内容

ParametersJSON Schema
NameRequiredDescriptionDefault
urlYes需要抓取的网页url

TDQS

B3.3/5.0
Behavior2/5

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

No annotations; description only mentions using r.jina.ai but lacks disclosure on read-only nature, error handling, rate limits, or output format. Insufficient for safe invocation.

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

Conciseness5/5

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

Single sentence, front-loaded with purpose, no extraneous information.

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?

For a simple 1-param tool with no output schema, description is minimally sufficient but lacks details on expected output format or constraints.

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

Parameters3/5

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

Schema description coverage is 100% so parameter meaning is clear from schema. Description adds minimal value ('get content') beyond the parameter description.

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

Purpose5/5

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

The description clearly states the verb-resource-action: using r.jina.ai to read a URL and get its content. It distinguishes from siblings (search, translate) as a fetch operation.

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?

No guidance on when to use this tool vs alternatives (search, translate). No when-not or context provided.

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

translateB

使用 gemini 翻译文本，中英文互译

ParametersJSON Schema
NameRequiredDescriptionDefault
contentYes需要翻译的文本

TDQS

B3.3/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of disclosure. It only states the translation action and language pair, omitting behavioral traits such as authentication needs, rate limits, side effects, or what the output looks like. This is insufficient for a write-like tool.

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?

The description is a single, concise sentence that delivers the core purpose without fluff. However, it is slightly too brief, missing potentially valuable details, but the essential information is front-loaded.

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

Completeness2/5

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

Given the simplicity of the tool (1 parameter, no output schema, no annotations), the description still lacks completeness. It does not explain the return format, error conditions, or handle any edge cases, making it insufficient for an agent to fully understand the tool's behavior.

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

Parameters3/5

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

The only parameter 'content' is described in the input schema as '需要翻译的文本'. The tool description does not add any additional semantics beyond that, so baseline 3 is appropriate given 100% schema coverage.

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

Purpose5/5

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

The description clearly states the tool translates text using Gemini for Chinese-English bidirectional translation. It specifies the verb 'translate', the resource 'text', and the language pair, distinguishing it from the sibling tool 'translate_deepl'.

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

Usage Guidelines3/5

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

The description implies usage for Chinese-English translation with Gemini, but does not explicitly state when to use this tool over the sibling 'translate_deepl' or provide any exclusions or context about when not to use it.

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

translate_deeplB

使用 deepl 翻译,支持多种语言互译

ParametersJSON Schema
NameRequiredDescriptionDefault
contentYes需要翻译的文本
source_langYes当前语言,source language,支持: AR,BG,CS,DA,DE,EL,EN-GB,EN-US,ES,ET,FI,FR,HU,ID,IT,JA,KO,LT,LV,NB,NL,PL,PT-BR,PT-PT,RO,RU,SK,SL,SV,TR,UK,ZH,ZH-HANS,ZH-HANT
target_langYes目标语言,target language,支持:AR,BG,CS,DA,DE,EL,EN-GB,EN-US,ES,ET,FI,FR,HU,ID,IT,JA,KO,LT,LV,NB,NL,PL,PT-BR,PT-PT,RO,RU,SK,SL,SV,TR,UK,ZH,ZH-HANS,ZH-HANT

TDQS

B3.1/5.0
Behavior2/5

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

No annotations provided; the description does not disclose any behavioral traits such as authentication requirements, rate limits, or error handling.

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?

The description is a single clear sentence with no redundant information.

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

Completeness2/5

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

Lacks details about output format, usage context, or prerequisites, which is insufficient given no output schema and no annotations.

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

Parameters3/5

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

Schema coverage is 100%, but the description does not add meaning beyond what the schema already provides for the parameters.

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

Purpose5/5

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

The description clearly states it uses DeepL translation and supports multiple languages, distinguishing it from sibling tool 'translate' which may use a different engine.

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?

No guidance on when to use this tool versus alternatives like 'translate' or when not to use 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. Dates show when Glama detected each change.

  1. 4 tool updatesv0.1.0
    • First observedfetch
    • First observedsearch
    • First observedtranslate
    • First observedtranslate_deepl
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TDQS

A3.5/5.0
Disambiguation4/5

The tools fetch and search are clearly distinct. However, the two translation tools (translate and translate_deepl) have overlapping purposes, and agents may struggle to choose between them without strong preferences for Gemini vs. DeepL.

Naming Consistency5/5

All tool names are lowercase and follow a predictable verb pattern. 'translate_deepl' uses a suffix to specify the engine, which is consistent with the naming scheme.

Tool Count4/5

With 4 tools, the server is on the smaller side but covers its intended scope (fetch, search, translate). It is not overly sparse and could reasonably be expanded with additional utilities.

Completeness4/5

The server covers fetching URLs, searching the web, and translating with two engines. There is minor duplication in translation tools, and no summarization or extraction tools, but the core functionality is present.

Maintenance

ActivityInactive
ResponsivenessSyncing

Resources

Unclaimed servers have limited discoverability.

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If you are the server author, to access and configure the admin panel.

Related MCP Connectors

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  • brave-search-mcp

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    An MCP server that integrates with AI models to provide web search capabilities through a single, easy-to-use tool interface.
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