UUIDv7 Generator
Generates UUIDv7 strings either individually or in batches, providing time-sortable universally unique identifiers through the Model Context Protocol.
README
mcp-uuidv7-generator
A Model Context Protocol (MCP) server for generating UUIDv7 strings.
Created with vibe-coding using trae.ai
Features
- Get a single UUIDv7 string.
- Get a batch of UUIDv7 strings.
Usage
To use this server with an MCP client like Claude Desktop, you can configure it as follows. This example assumes you are running the server directly from its source code.
First, ensure you have Python installed and the necessary dependencies (see Development section).
Then, in your MCP client configuration (e.g., claude-desktop-settings.json):
{
"mcpServers": {
"uuid_v7_generator": {
"command": "python",
"args": ["/path/to/your/mcp-uuid-server/mcp_uuid_server/server.py"],
// Optional: specify the working directory if needed
// "cwd": "/path/to/your/mcp-uuid-server/"
}
}
}
Replace /path/to/your/mcp-uuid-server/ with the actual path to where you have cloned or placed the server code.
If the server were packaged and published in a way that uvx could run it (like some official MCP servers), the configuration might look like this (this is a hypothetical example as this server is not currently published this way):
{
"mcpServers": {
"uuid_v7_generator": {
"command": "uvx",
"args": ["mcp-uuid-server"]
}
}
}
Running the Server Directly
You can run the server directly for development or local use:
python /path/to/your/mcp-uuid-server/mcp_uuid_server/server.py
The server will start and listen for MCP client connections on stdin/stdout.
Available Tools
-
get_uuidv7:- Description: Generates and returns a single UUIDv7 string.
- Arguments: None
- Returns: A string representing a UUIDv7.
-
get_uuidv7_batch:- Description: Generates and returns a list of UUIDv7 strings.
- Arguments:
count(integer): The number of UUIDv7 strings to generate. Must be a positive integer.
- Returns: A list of strings, where each string is a UUIDv7.
Development
To set up the development environment:
-
Clone the repository.
-
It's recommended to create and activate a virtual environment:
python -m venv .venv source .venv/bin/activate # On Windows use .venv\Scripts\activate -
Install the dependencies from
pyproject.toml(which includesmcpanduuid6):pip install .For editable mode, which is useful during development as changes to the source code are immediately reflected without needing to reinstall:
pip install -e . -
Run the server directly for testing:
python mcp_uuid_server/server.py
Troubleshooting
JSON Parse Error
If you encounter an error message similar to MCP ERROR (uuid_v7_generator): SyntaxError: JSON Parse error: Unable to parse JSON string, this typically indicates that the MCP client (e.g., Claude Desktop) sent a malformed JSON request to this server.
To resolve this:
- Verify Client Requests: Check the JSON requests being formulated and sent by your MCP client. Ensure they are syntactically correct JSON.
- Check Encoding: Ensure that the JSON requests are UTF-8 encoded, as this is the standard for JSON.
- Tool Arguments:
- For
get_uuidv7, the client should send a request indicating the tool name, usually with no parameters or an empty parameter object. - For
get_uuidv7_batch, the client must send parameters as a JSON object with an integercountfield, for example:{"count": 10}. Sending a string for count (e.g.{"count": "10"}) or other malformations in the request structure can lead to parsing issues.
- For
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.