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kirill-markin

Weaviate MCP Server

by kirill-markin
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

MCP Server Template for Cursor IDE

A simple template for creating custom tools for Cursor IDE using Model Context Protocol (MCP). Create your own repository from this template, modify the tools, and connect them to your Cursor IDE.

Server Mood Response

Quick Start

  1. Click "Deploy to Heroku" button

    Deploy to Heroku

  2. After deployment, configure Cursor:

    • Open Cursor Settings → Features

    • Add new MCP server

    • Use your Heroku URL with /sse path (e.g., https://<your-app-name>.herokuapp.com/sse)

  3. Test your agent's mood in Cursor:

    • Ask your agent "Please ask about our server mood and let me know how it is."

    • The server will respond with a cheerful message and a heart ❤️

Related MCP server: pure.md MCP server

Alternative Setup Methods

You can run the server in three ways: using Docker, traditional Python setup, or directly in Cursor IDE.

Docker Setup

The project includes Docker support for easy deployment:

  1. Initial setup:

# 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. Build and run using Docker Compose:

# 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. The server will be available at:

  2. Quick test:

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

  1. Connect to Cursor IDE:

    • Open Cursor Settings → Features

    • Add new MCP server

    • Type: Select "sse"

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

Traditional Setup

First, install the uv package manager:

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

Start the server using either stdio (default) or SSE transport:

# 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

After installation, you can connect the server directly to Cursor IDE:

  1. Right-click on the cursor-run-mcp-server.sh file in Cursor

  2. Select "Copy Path" to copy the absolute path

  3. Open Cursor Settings (gear icon)

  4. Navigate to Features tab

  5. Scroll down to "MCP Servers"

  6. Click "Add new MCP server"

  7. Fill in the form:

    • Name: Choose any name (e.g., "my-mcp-server-1")

    • Type: Select "stdio" (not "sse" because we run the server locally)

    • Command: Paste the absolute path to cursor-run-mcp-server.sh that you copied earlier. For example: /Users/yourname/weaviate-mcp-server/cursor-run-mcp-server.sh

Environment Variables

Available environment variables (can be set in .env):

  • MCP_SERVER_PORT (default: 8000) - Port to run the server on

  • MCP_SERVER_HOST (default: 0.0.0.0) - Host to bind the server to

  • DEBUG (default: false) - Enable debug mode

  • MCP_USER_AGENT - Custom User-Agent for website fetching

Additional options

Installing via Smithery

To install MCP Server Template for Cursor IDE for Claude Desktop automatically via Smithery:

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

Glama server review

Available Tools

2 tools
mcp_fetchC

Fetches a website and returns its content

ParametersJSON Schema
NameRequiredDescriptionDefault
urlYesURL to fetch

TDQS

C2.9/5.0
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 behavioral disclosure. It mentions fetching and returning content, but doesn't cover important aspects like error handling, rate limits, authentication needs, timeouts, or what happens with invalid URLs. This leaves significant gaps for a tool that interacts with external resources.

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 - a single sentence that directly states the tool's function. Every word earns its place, with no unnecessary elaboration or repetition. It's front-loaded with the core functionality.

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?

For a tool that fetches external websites with no annotations and no output schema, the description is insufficient. It doesn't explain what format the content is returned in (HTML, text, etc.), potential limitations, error conditions, or security considerations. The lack of output schema means the description should compensate by explaining return values, which it doesn't do.

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%, with the single parameter 'url' clearly documented in the schema. The description doesn't add any meaningful parameter information beyond what's already in the schema, so it meets the baseline for high schema coverage but doesn't provide additional value.

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 with a specific verb ('fetches') and resource ('website'), and specifies the outcome ('returns its content'). However, it doesn't differentiate from the sibling tool 'mood', which appears unrelated but could have overlapping functionality in some contexts.

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 is provided on when to use this tool versus alternatives or in what context it should be applied. The description only states what it does, not when it's appropriate or when other tools might be better suited.

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

moodB

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

ParametersJSON Schema
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

B3.3/5.0
Behavior3/5

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 reveals the server will 'always respond with a cheerful message and a heart ❤️' which indicates predictable, positive output. However, it doesn't disclose other behavioral traits like response format details, potential errors, or interaction patterns beyond the basic promise.

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 at just one sentence, with zero wasted words. It's front-loaded with the core purpose and includes the behavioral promise efficiently. Every part of the single sentence earns its place by conveying essential 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?

Given the tool's low complexity (single parameter, no output schema, no annotations), the description is minimally complete. It states what the tool does and the expected response behavior. However, it lacks context about why this tool exists alongside 'mcp_fetch' or what use cases it serves, leaving gaps in overall understanding.

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 the schema already fully documents the single 'question' parameter with examples. The description adds no additional parameter semantics beyond what's in the schema. The baseline score of 3 is appropriate when the schema does all the parameter documentation work.

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: 'Ask the server about its mood' which is a specific verb+resource combination. It distinguishes from the sibling tool 'mcp_fetch' by focusing on mood inquiry rather than data fetching. However, it doesn't fully specify what 'mood' means in this context beyond 'always happy'.

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 mentions the server's mood is 'always happy,' it doesn't explain when this inquiry is appropriate or what scenarios warrant using this tool over 'mcp_fetch' or other potential tools. No explicit when/when-not instructions are provided.

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. 2 tool updates
    • First observedmcp_fetch
    • First observedmood
Install Server
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TDQS

C2.8/5.0
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

Unclaimed servers have limited discoverability.

Looking for Admin?

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

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