GenPark HyperLogLog Cardinality Estimator

io.github.alphaparkincPublished by GitHub account alphaparkincv1.0.1Updated Oct 25, 2026

Pure Python 64-register HyperLogLog cardinality estimator for high-speed streaming distinct query es

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Overview

AI-generated overview

A local MCP server that gives an assistant a pure-Python HyperLogLog estimator for fast approximate distinct-count queries over streaming data.

What you can do
Estimate distinct cardinality of streaming data using a 64-register HyperLogLog implementation written only with the Python standard library, with no third-party runtime dependencies. Run it as a local MCP server so an assistant can call the estimator, or use the same code directly as a Python library. The README points to example usage scripts for integration demonstrations.
When to use it
Useful when you need quick approximate distinct counts over large or streaming datasets and want a lightweight, dependency-free estimator available to an assistant rather than a full database or analytics stack.
Requirements
Runs as a local process over stdio, started with the Python interpreter (python mcp_server.py). Requires a Python runtime; the README states it uses only the Python standard library. No authentication, environment variables or headers are declared. Desktop only.
Before you install
HyperLogLog returns approximate counts, not exact values, so results are unsuitable where exact distinct counts are required. The manifest lists no tools, so verify the actual exposed interface before relying on it. No credentials or write actions are declared.

Installation

In SourceWeft

  1. Open GenPark HyperLogLog Cardinality Estimator in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

GenPark HyperLogLog Cardinality Estimator

[License: MIT] [Python Standard Library] [Model Context Protocol] [GenPark]

Pure Python 64-register HyperLogLog cardinality estimator for high-speed streaming distinct query estimation.

Part of the GenPark AI Agent Skills Ecosystem.

🌟 Key Features

  • 100% Python Standard Library: Zero third-party runtime dependencies.
  • MCP Native: Plugs directly into Claude Desktop, Cursor, LobeChat, and autonomous agent DAGs.
  • Production Resilience: Strict schema conformance, zero data loss, enterprise hardened.

🚀 Installation & Usage

Run as an MCP server:

bash
python mcp_server.py

Use directly as a library:

python
from client import *

See example_usage.py for comprehensive integration demonstrations.

📄 License

MIT License. Maintained by GenPark AI.

Source: README.md at commit 38d6c58

Tools

0
SourceWeft started this package once in an isolated sandbox, without credentials, to list its tools. That failed: the package type cannot run in the sandbox.

Version history

1
  1. v1.0.1LatestOct 25, 2026

Score

40% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 days25 pts

    Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.

  • Auth declared10 pts

    Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.

  • Tools listed15 pts

    Answer tools/list without a credential, or ship a package that starts in a sandbox without one.

  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts

    Declare a license in the repository or the registry entry.