Skip to main content
Glama
Sign In
genpark-personal-knowledge-vault-graph-compiler-skill

genpark-personal-knowledge-vault-graph-compiler-skill

by alphaparkinc
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

genpark-personal-knowledge-vault-graph-compiler-skill

Python 3.9+ License MIT MCP Compatible GenPark AI Zero Dependencies

🌐 GenPark MCP Hub • 📦 GenPark Official • 📖 Documentation

📌 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).

⚡ 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-personal-knowledge-vault-graph-compiler-skill

🏗️ Architecture

graph LR
    Agent([🤖 Autonomous Agent / IDE]) -->|MCP Protocol / JSON-RPC| Server[⚡ genpark-personal-knowledge-vault-graph-compiler-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 PersonalKnowledgeVaultGraphCompiler

client = PersonalKnowledgeVaultGraphCompiler()
result = client.run_vault_benchmark()
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-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 --test

📊 Technical Specifications

Parameter

Type

Required

Description

payload

string / dict

Yes

Primary context, text, or task input

options

dict

No

Execution flags, thresholds, or sensitivity bounds

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    This server cannot be deployed

    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    Resources

    Related MCP Connectors

    Related MCP Servers

    • Zero Brain MCP Server

      miru-zero
      A
      license
      A
      quality
      C
      maintenance
      MCP server for managing a local, domain-agnostic knowledge base using Markdown notes with frontmatter. Enables AI agents to capture, read, search, link, and maintain notes with atomic writes and privacy controls.
      13
      MIT
    • genpark-personal-knowledge-vault-graph-compiler-skill

      genpark-personal-knowledgeofficial

      Alpha-Park
      F
      license
      Not graded
      quality
      Not graded
      maintenance
      Enables agents to compile a personal knowledge vault into a linked graph by indexing bi-directional links and parsing [[wikilinks]], tags, and unlinked mentions across notes. It runs deterministically over MCP without external dependencies, turning raw note collections into navigable, queryable knowledge structures.
      -

    • epsilongraph

      silverenternal
      A
      license
      A
      quality
      B
      maintenance
      Exposes a typed, provenance-aware knowledge graph over an Obsidian vault to coding agents over MCP, so they can trace what grounds a claim, compute which other notes a change makes wrong, surface contradictions and admitted gaps, and assemble a task-specific token-budgeted subset of the vault. Indexing, retrieval, and impact analysis run with zero third-party runtime dependencies beyond the Python standard library.
      10
      MIT

    • Zettelkasten MCP Server

      claudiagunduz3448
      F
      license
      Not graded
      quality
      A
      maintenance
      Enables creating, linking, searching, exploring, and synthesizing atomic notes as a knowledge graph through MCP-compatible clients such as Claude. Supports tags, note types, semantic relationships, Markdown storage, and an SQLite index for efficient traversal.
      -