genpark-personal-knowledge-vault-graph-compiler-skill
Compiles a personal knowledge vault graph and builds a bi-directional link index from Obsidian-style notes, parsing [[wikilinks]], tags, and unlinked mentions.
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-personal-knowledge-vault-graph-compiler-skillcompile my knowledge vault and show backlinks to [[Project Ideas]]"
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-personal-knowledge-vault-graph-compiler-skill
π GenPark MCP Hub β’ π¦ GenPark Official β’ π Documentation
π Overview & Capability
genpark-personal-knowledge-vault-graph-compiler-skill is a deterministic, high-performance, zero-dependency Python tool and native Model Context Protocol (MCP) server engineered for next-generation personal agents, multi-agent frameworks, and autonomous developer workflows.
Executive Capability: Personal knowledge vault graph compiler and bi-directional link indexer parsing [[wikilinks]], tags, and unlinked mentions across personal notes (inspired by Obsidian and Roam).
β‘ Key Highlights
π Zero External
pipDependencies: Implemented entirely with pure Python standard library for instant zero-overhead execution.π Native Model Context Protocol (MCP): Plugs directly into any MCP-compliant client via JSON-RPC 2.0 stdio.
β‘ Sub-Millisecond Execution: Slashes token burn and latency by resolving routine agent tasks deterministically without frontier LLM round-trips.
π‘οΈ Production-Hardened: Comprehensive error handling, boundary validation, and telemetry.
Related MCP server: Brainstem
ποΈ Architecture
graph LR
Agent([π€ Autonomous Agent / IDE]) -->|MCP Protocol / JSON-RPC| Server[β‘ genpark-personal-knowledge-vault-graph-compiler-skill Server]
Server --> Core[π§ Deterministic Processing Core]
Core --> Out[π Actionable Result & Telemetry]
Out --> Agentπ Quickstart & Usage
1. Direct Python Client Execution
python example_usage.py2. Programmatic Integration
from client import PersonalKnowledgeVaultGraphCompiler
client = PersonalKnowledgeVaultGraphCompiler()
result = client.run_vault_benchmark()
print(result)π Model Context Protocol (MCP) Setup
Connect this skill to Claude Desktop, Cursor, or any MCP-compliant client:
claude_desktop_config.json
{
"mcpServers": {
"genpark-personal-knowledge-vault-graph-compiler-skill": {
"command": "python",
"args": ["/path/to/genpark-personal-knowledge-vault-graph-compiler-skill/mcp_server.py"]
}
}
}Direct MCP Testing
python mcp_server.py --testπ Technical Specifications
Parameter | Type | Required | Description |
|
| Yes | Primary context, text, or task input |
|
| No | Execution flags, thresholds, or sensitivity bounds |
This server cannot be deployed
Maintenance
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