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GenPark JSON Pointer Patch Delta

GenPark JSON Pointer Patch Delta

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genpark.aiDeveloper Tools7Updated 4d ago

About GenPark JSON Pointer Patch Delta

A JSON Pointer and JSON Patch delta engine for incremental state synchronization, compliant with RFC 6901 and RFC 6902. It can run as an MCP server or be used as a Python library.

Key features

  1. 01Compute JSON deltas
  2. 02Support JSON Pointer
  3. 03Support JSON Patch
  4. 04Comply with RFC 6901 and RFC 6902

Use cases

  1. 01Compute incremental state updates
  2. 02Synchronize JSON changes

MCP support

Runs as an MCP server that provides JSON Pointer and JSON Patch delta computation to clients.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository
Packages
mcpbgenpark-json-pointer-patch-delta-skill-v1.0.1.mcpb

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

GenPark JSON Pointer Patch Delta

License: MIT Python Standard Library Model Context Protocol GenPark

RFC 6901 / RFC 6902 compliant JSON Pointer and JSON Patch delta computation engine for incremental state sync.

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:

python mcp_server.py

Use directly as a library:

from client import *

See example_usage.py for comprehensive integration demonstrations.

📄 License

MIT License. Maintained by GenPark AI.

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.