A high-performance integration for Openclaw Skills designed to query, manage, and analyze large-scale distributed graph data using TigerGraph.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install tigergraph-connector
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install tigergraph-connector using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is TigerGraph Connector?
The TigerGraph Connector for Openclaw Skills provides a professional-grade interface to the TigerGraph distributed graph database platform. It is specifically engineered to handle enterprise-level graph analytics, allowing users to interact with high-performance datasets via GSQL and REST++ APIs. This skill bridges the gap between AI agents and complex relational data structures, enabling real-time processing and deep relationship discovery within a knowledge graph environment.
By leveraging this addition to the Openclaw Skills ecosystem, developers can automate the management of vertices and edges, perform complex pattern matching, and execute Turing-complete graph queries. The connector is optimized for distributed computing, ensuring that even the most massive datasets remain accessible and actionable for graph-based AI workflows.
TigerGraph Connector Use Cases
- Running complex GSQL queries and pre-installed graph algorithms for deep data insights
- Loading massive datasets of vertices and edges into TigerGraph using REST++ APIs
- Implementing real-time graph analytics for fraud detection, recommendation engines, or supply chain mapping
- Executing community detection and PageRank algorithms within Openclaw Skills automated pipelines
- Finding shortest paths and hidden patterns across multi-hop traversals in a distributed environment
How TigerGraph Connector Works
- Initialize the connection by providing the TigerGraph host URL, REST++ port, and target graph name.
- Authenticate the session using an API token or username/password credentials for secure access.
- Define the graph schema or utilize existing vertex and edge types for data operations.
- Execute GSQL queries or built-in algorithms to extract relational insights from the database.
- Process and map the returned JSON results into Python objects for further analysis or reporting within Openclaw Skills.
TigerGraph Connector Setup
To begin using the TigerGraph Connector as part of your Openclaw Skills toolkit, install the required Python libraries:
pip install pyTigerGraph requests
Ensure your TigerGraph instance is reachable and configure your connection parameters:
{
"host": "http://your-tigergraph-server",
"restpp_port": 9000,
"graph_name": "YourGraphName",
"api_token": "your-secure-token"
}
TigerGraph Connector Data Schema & Taxonomy
The TigerGraph Connector manages data through a well-defined schema optimized for high-speed traversals. Openclaw Skills users can interact with the following data components:
| Component | Type | Function |
|---|---|---|
| Vertex Types | Entity | Defines nodes like Person, Product, or Company |
| Edge Types | Relation | Defines directional or undirected links between vertices |
| Properties | Attributes | Key-value pairs stored on vertices and edges for filtering |
| GSQL Queries | Logic | Compiled code blocks that define complex graph traversals |
Data is exchanged using standard JSON formats, supporting batch operations for both vertex and edge insertion.
TigerGraph Connector Advanced Features
- Support for complex multi-hop and variable-length traversal patterns in GSQL
- Access to a built-in library of algorithms including Louvain community detection and Centrality analysis
- Automated batch loading capabilities from CSV files with custom attribute mapping
- Real-time result streaming for handling large-scale datasets within Openclaw Skills
- Integrated error handling with exponential backoff for enterprise-grade reliability
- Support for custom GSQL query installation and high-performance pre-compiled execution
SKILL.md
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