GenPark JSON-RPC Batch Pipelining Dispatcher

io.github.alphaparkincPublished by GitHub account alphaparkincv1.0.1Updated Oct 26, 2026

High-throughput JSON-RPC 2.0 batch pipelining and inter-tool parameter dependency resolver for Model

VerifiedSTDIODesktop onlyDeveloper ToolsAI & ML

Overview

AI-generated overview

A local MCP server that batches JSON-RPC 2.0 calls and resolves parameter dependencies between tool calls for high-throughput pipelines.

What you can do
  • Batch and pipeline JSON-RPC 2.0 requests for high-throughput dispatch
  • Resolve parameter dependencies between tool calls so one call can feed another
  • Run as a local MCP server over stdio, or be imported as a Python library
  • Use it inside agent DAGs and desktop MCP clients such as Claude Desktop, Cursor or LobeChat
When to use it
Worth adding when an assistant or agent needs to issue many JSON-RPC or tool calls efficiently and chain results between them, rather than sending requests one at a time.
Requirements
Runs as a local process on the user's machine, started with Python (the README shows running mcp_server.py); desktop only. The README states it uses only the Python standard library, with no third-party runtime dependencies. No authentication, environment variables or headers are declared.
Before you install
The README makes broad claims (strict schema conformance, zero data loss, enterprise hardened) that are not backed by detail in the supplied material. No tools are listed in the manifest, so the exact operations it exposes are unclear before installing. It dispatches batches of calls, so review what it forwards and to which endpoints.

Installation

In SourceWeft

  1. Open GenPark JSON-RPC Batch Pipelining Dispatcher 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 JSON-RPC Batch Pipelining Dispatcher

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

High-throughput JSON-RPC 2.0 batch pipelining and inter-tool parameter dependency resolver for Model Context Protocol.

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 c9955ae

Tools

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

1
  1. v1.0.1LatestOct 20, 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.