Provides tools for CrewAI multi-agent frameworks to perform multi-file AST dependency graph parsing and minimum context slicing for coding tasks.
Provides tools for LangGraph multi-agent frameworks to perform multi-file AST dependency graph parsing and minimum context slicing for coding tasks.
Allows integration with OpenAI Swarm multi-agent framework for AST dependency slicing and context extraction.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@genpark-agent-codebase-ast-dependency-slicer-skill slice the call tree for process_order in src/orders.py"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
🌐 GenPark MCP Hub • 📦 GenPark Official • 📖 Documentation
genpark-agent-codebase-ast-dependency-slicer-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: Multi-file AST dependency graph parser & minimum context slicer extracting symbol call-trees for coding agents.
🐍 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: Graft
graph LR
Agent([🤖 Autonomous Agent / IDE]) -->|MCP Protocol / JSON-RPC| Server[⚡ genpark-agent-codebase-ast-dependency-slicer-skill Server]
Server --> Core[🧠 Deterministic Processing Core]
Core --> Out[📊 Actionable Result & Telemetry]
Out --> Agentpython example_usage.pyfrom client import CodebaseASTDependencySlicer
client = CodebaseASTDependencySlicer()
result = client.run_benchmark_ast_slicing()
print(result)Connect this skill to Claude Desktop, Cursor, or any MCP-compliant client:
claude_desktop_config.json{
"mcpServers": {
"genpark-agent-codebase-ast-dependency-slicer-skill": {
"command": "python",
"args": ["/path/to/genpark-agent-codebase-ast-dependency-slicer-skill/mcp_server.py"]
}
}
}python mcp_server.py --testParameter | Type | Required | Description |
|
| Yes | Primary context, code, schema, or content input |
|
| No | Execution flags, compression ratios, or risk bounds |
This server cannot be deployed
Deterministic context layer for your codebase: change impact, blast radius, answers with receipts.
Stateless TS/JS compiler facts for agents: references, imports, impact. No repo index or OAuth.
Codebase graphs, caller impact analysis, and recorded project context for AI coding agents.
Ask a codebase what calls what: search, blast radius, paths between symbols, and diffs.
