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kirill-markin

Weaviate MCP Server

by kirill-markin
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

MCP Server Template for Cursor IDE

一个用于使用模型上下文协议（MCP）为 Cursor IDE 创建自定义工具的简单模板。从该模板创建你自己的仓库，修改工具，并将其连接到你的 Cursor IDE。

服务器心情响应

快速开始

  1. 点击“部署到 Heroku”按钮

    部署到 Heroku

  2. 部署后，配置 Cursor：

    • 打开 Cursor 设置 → 功能

    • 添加新的 MCP 服务器

    • 使用你的 Heroku URL，路径为 /sse（例如 https://<your-app-name>.herokuapp.com/sse）

  3. 在 Cursor 中测试你的代理的心情：

    • 询问你的代理“请询问我们服务器的心情并告诉我它怎么样。”

    • 服务器将回复一条愉快的消息和一个心形 ❤️

Related MCP server: pure.md MCP server

其他设置方法

你可以通过三种方式运行服务器：使用 Docker、传统的 Python 设置，或直接在 Cursor IDE 中运行。

Docker 设置

项目包含 Docker 支持，便于部署：

  1. 初始设置：

# Clone the repository
git clone https://github.com/kirill-markin/weaviate-mcp-server.git
cd weaviate-mcp-server

# Create environment file
cp .env.example .env

  1. 使用 Docker Compose 构建并运行：

# Build and start the server
docker compose up --build -d

# View logs
docker compose logs -f

# Check server status
docker compose ps

# Stop the server
docker compose down

  1. 服务器将在以下地址可用：

  2. 快速测试：

# Test the server endpoint
curl -i http://localhost:8000/sse

  1. 连接到 Cursor IDE：

    • 打开 Cursor 设置 → 功能

    • 添加新的 MCP 服务器

    • 类型：选择“sse”

    • URL：输入 http://localhost:8000/sse

传统设置

首先，安装 uv 包管理器：

# Install uv on macOS
brew install uv
# Or install via pip (any OS)
pip install uv

使用 stdio（默认）或 SSE 传输启动服务器：

# Install the package with development dependencies
uv pip install -e ".[dev]"

# Using stdio transport (default)
uv run mcp-simple-tool

# Using SSE transport on custom port
uv run mcp-simple-tool --transport sse --port 8000

# Run tests
uv run pytest -v

安装后，你可以直接将服务器连接到 Cursor IDE：

  1. 在 Cursor 中右键单击 cursor-run-mcp-server.sh 文件

  2. 选择“复制路径”以复制绝对路径

  3. 打开 Cursor 设置（齿轮图标）

  4. 导航到“功能”选项卡

  5. 向下滚动到“MCP 服务器”

  6. 点击“添加新的 MCP 服务器”

  7. 填写表单：

    • 名称：选择任意名称（例如“my-mcp-server-1”）

    • 类型：选择“stdio”（不是“sse”，因为我们在本地运行服务器）

    • 命令：粘贴你之前复制的 cursor-run-mcp-server.sh 的绝对路径。例如：/Users/yourname/weaviate-mcp-server/cursor-run-mcp-server.sh

环境变量

可用的环境变量（可以在 .env 中设置）：

  • MCP_SERVER_PORT（默认值：8000）- 服务器运行的端口

  • MCP_SERVER_HOST（默认值：0.0.0.0）- 服务器绑定的主机

  • DEBUG（默认值：false）- 启用调试模式

  • MCP_USER_AGENT - 用于网站抓取的自定义用户代理

其他选项

通过 Smithery 安装

要通过 Smithery 自动为 Claude Desktop 安装 MCP Server Template for Cursor IDE：

npx -y @smithery/cli install @kirill-markin/example-mcp-server --client claude

Glama 服务器审查

Available Tools

2 tools
mcp_fetchC

Fetches a website and returns its content

NameRequiredDescriptionDefault
urlYesURL to fetch

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool fetches and returns content, but lacks details on error handling, rate limits, authentication needs, or response format. For a tool with no annotations, this is a significant gap in transparency about its operational behavior.

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?

The description is extremely concise and front-loaded, consisting of a single, clear sentence: 'Fetches a website and returns its content'. Every word earns its place, with no redundant or unnecessary information, making it efficient and easy to parse.

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 tool's complexity (a fetch operation with potential behavioral nuances), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what 'content' includes (e.g., HTML, text), error cases, or limitations, leaving gaps in understanding how the tool behaves in practice.

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 schema description coverage is 100%, with the parameter 'url' fully documented in the schema. The description adds no additional meaning beyond the schema, such as URL format constraints or examples. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't enhance parameter understanding.

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?

The description clearly states the action ('fetches') and resource ('a website'), specifying what the tool does. It distinguishes from most siblings (e.g., 'apply_prompt_' tools, 'mood') by focusing on web content retrieval, though it doesn't explicitly differentiate from 'fetch_railway_docs' tools. The purpose is specific but lacks sibling comparison.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention scenarios for usage, prerequisites, or exclusions, and offers no comparison to sibling tools like 'fetch_railway_docs' or 'fetch_railway_docs_optimized'. Usage is implied only by the action 'fetches', with no explicit context.

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

moodA

Ask the server about its mood - it's always happy!

NameRequiredDescriptionDefault
questionYesAsk this MCP server about its mood! You can phrase your question in any way you like - 'How are you?', 'What's your mood?', or even 'Are you having a good day?'. The server will always respond with a cheerful message and a heart ❤️

TDQS

A3.5/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key traits: the tool queries the server's mood, the server is 'always happy', and responses include 'a cheerful message and a heart ❤️'. This covers the interactive nature and predictable output style, though it lacks details like response format or error handling. No contradiction with annotations exists.

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?

The description is extremely concise (one sentence) and front-loaded with the core purpose. Every word earns its place: 'Ask the server about its mood' defines the action, and 'it's always happy!' adds essential behavioral context. There's zero redundancy or fluff, making it highly efficient for an agent to parse.

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?

Given the tool's low complexity (single parameter, no output schema, no annotations), the description is reasonably complete for its purpose. It explains what the tool does and the expected response behavior. However, it lacks output details (e.g., response structure) and doesn't address potential edge cases, leaving some gaps in full contextual understanding for an agent.

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 input schema has 100% description coverage, with the parameter 'question' fully documented in the schema itself (including examples like 'How are you?'). The description adds no additional parameter semantics beyond what the schema provides, such as formatting tips or constraints. According to rules, with high schema coverage (>80%), the baseline is 3 even without param info in the description.

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?

The description clearly states the tool's purpose: to ask the server about its mood, with the specific behavioral outcome that it 'always responds with a cheerful message and a heart ❤️'. It distinguishes from sibling tools (all related to prompt application or documentation fetching) by focusing on a conversational interaction rather than functional operations. However, it doesn't explicitly contrast with specific alternatives for mood-checking, keeping it at 4 rather than 5.

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?

The description provides no guidance on when to use this tool versus alternatives. While it implies usage for checking server mood, it doesn't specify contexts (e.g., after errors, during idle time) or exclusions (e.g., not for functional queries). With sibling tools focused on practical tasks, the lack of when/when-not guidance leaves the agent guessing about appropriate use cases.

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 updates
    • First observedmcp_fetch
    • First observedmood
Deploy Server
Shareable, User-Owned Context BackendPeople, applications, and agents read, write, and coordinate together in one context lake. Reach it over MCP, a CLI, a Python SDK, or REST.fulcradynamics.comAd

TDQS

C2.8/5.0

Scored across 2 tools

Disambiguation5/5

The two tools have completely distinct purposes: mcp_fetch is for fetching website content, while mood is a whimsical interaction unrelated to data operations. There is no overlap or ambiguity between them.

Naming Consistency2/5

The naming is inconsistent: mcp_fetch follows a verb_noun pattern, but mood is a noun with no action verb. This mixing of conventions reduces predictability and clarity in the tool set.

Tool Count2/5

With only 2 tools, the server feels severely under-scoped for a Weaviate MCP Server, which typically involves vector database operations like querying, indexing, or managing data. The tools provided do not align with the expected domain.

Completeness1/5

The tool surface is extremely incomplete for a Weaviate server. There are no tools for core vector database functions such as searching, adding data, or managing schemas, leaving significant gaps that would cause agent failures in this domain.

Maintenance

ActivityMaintained
ResponsivenessNo issues

Resources

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