Skip to main content
Glama
alphaparkinc

genpark-agent-context-dynamic-compressor-skill

Official
by alphaparkinc
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

genpark-agent-context-dynamic-compressor-skill

Python 3.9+ License MIT MCP Compatible GenPark AI Zero Dependencies

🌐 GenPark MCP Hub • 📦 GenPark Official • 📖 Documentation

📌 Overview & Capability

genpark-agent-context-dynamic-compressor-skill is a deterministic, high-performance, zero-dependency Python tool and native Model Context Protocol (MCP) server designed for autonomous AI agents, multi-agent frameworks (LangGraph, CrewAI, AutoGen, OpenAI Swarm), and developer environments (Cursor, Windsurf, Claude Desktop).

Executive Capability: Dynamic long-horizon context window compression engine pruning verbose tool outputs, HTML boilerplate & semantic redundancy by 40-70%.

⚡ Key Highlights

  • 🐍 Zero External pip Dependencies: Implemented entirely with pure Python standard library for instant zero-overhead execution.

  • 🔌 Native Model Context Protocol (MCP): Plugs directly into any MCP-compliant client via JSON-RPC 2.0 stdio.

  • ⚡ Sub-Millisecond Execution: Slashes token burn and latency by resolving routine agent tasks deterministically without frontier LLM round-trips.

  • 🛡️ Production-Hardened: Comprehensive error handling, boundary validation, and telemetry.

Related MCP server: genpark-contextual-compression-filter-skill

🏗️ Architecture

graph LR
    Agent([🤖 Autonomous Agent / IDE]) -->|MCP Protocol / JSON-RPC| Server[⚡ genpark-agent-context-dynamic-compressor-skill Server]
    Server --> Core[🧠 Deterministic Processing Core]
    Core --> Out[📊 Actionable Result & Telemetry]
    Out --> Agent

🚀 Quickstart & Usage

1. Direct Python Client Execution

python example_usage.py

2. Programmatic Integration

from client import AgentContextDynamicCompressor

client = AgentContextDynamicCompressor()
result = client.run_benchmark_compression()
print(result)

🔌 Model Context Protocol (MCP) Setup

Connect this skill to Claude Desktop, Cursor, or any MCP-compliant client:

claude_desktop_config.json

{
  "mcpServers": {
    "genpark-agent-context-dynamic-compressor-skill": {
      "command": "python",
      "args": ["/path/to/genpark-agent-context-dynamic-compressor-skill/mcp_server.py"]
    }
  }
}

Direct MCP Testing

python mcp_server.py --test

📊 Technical Specifications

Parameter

Type

Required

Description

payload

string / dict

Yes

Primary context, code, schema, or content input

options

dict

No

Execution flags, compression ratios, or risk bounds

This server cannot be deployed

Context Every Agent Can ShareAgents share what they learn, hand off work, and keep it when you switch models. Start with 5 GB free.fulcradynamics.comAd

Maintenance

ActivityMaintained
ResponsivenessNo issues

Resources

Related MCP Connectors

Related MCP Servers

  • Context Engine

    melonelish
    A
    license
    Not graded
    quality
    D
    maintenance
    A task-aware context compression layer for Agent workflows, RAG pipelines, and AI Coding assistants, reducing noisy logs, retrieval chunks, and code context into high-signal LLM inputs via CLI, Python SDK, and MCP.
    328
    MIT
  • genpark-agent-context-dynamic-compressor-skill by Alpha-Park

    genpark-agent-context-dynamicofficial

    Alpha-Park
    F
    license
    Not graded
    quality
    B
    maintenance
    Enables MCP-compatible clients and autonomous agents to dynamically compress long-horizon context by pruning verbose tool outputs, HTML boilerplate, and semantic redundancy by 40-70%. It reduces token burn and latency through deterministic, zero-dependency processing.
    7
    -

  • Compressor Reflex MCP

    ericmaddox
    A
    license
    Not graded
    quality
    A
    maintenance
    Enables MCP-compatible developer environments to shrink verbose tool outputs—test logs, git diffs, directory listings, and file dumps—before they reach the context window, preserving compiler errors, failure signatures, and decisive anchors. It runs either as direct callable tools or as a transparent proxy wrapping other MCP servers such as filesystem, git, or terminal providers.
    31 PyPI
    1
    MIT