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TG_MCP

Expose TigerGraph graph database operations as structured tools and URI-based resources for MCP agents, facilitating schema introspection, query execution, and vertex/edge upsert through a Python interface.

Author

TG_MCP logo

Muzain187

MIT License

Quick Info

GitHub GitHub Stars 5
NPM Weekly Downloads 0
Tools 1
Last Updated 2026-02-19

Tags

tigergraphanalyticsgraphtigergraph graphgraph databaseexpose tigergraph

TG_MCP

Integration

A lightweight Python interface that exposes TigerGraph operations (queries, schema, vertices, edges, UDFs) as structured tools and URI-based resources for MCP agents.

Table of Contents

  1. Features
  2. Project Structure
  3. Installation
  4. Configuration
  5. Connecting to Claude
  6. Examples
  7. Contributing
  8. License

Features

  • Schema Introspection
    Retrieve full graph schema (vertex & edge types).

  • Query Execution
    Run installed GSQL queries or raw GSQL strings with parameters.

  • Vertex & Edge Upsert
    Create or update vertices and edges programmatically.

  • Resource URIs
    Access graph objects through tgraph://vertex/... and tgraph://query/... URIs.

  • UDF & Algorithm Listing
    Fetch installed user-defined functions and GDS algorithm catalogs.

Project Structure

TG_MCP/
├── config.py            # Environment config (HOST, GRAPH, SECRET)
├── tg_client.py         # Encapsulates TigerGraphConnection and core operations
├── tg_tools.py          # `@mcp.tool` definitions exposing client methods
├── tg_resources.py      # `@mcp.resource` URI handlers
├── main.py              # MCP app bootstrap (`mcp.run()`)
├── pyproject.toml       # Project metadata & dependencies
├── LICENSE              # MIT License
└── .gitignore           # OS/Python ignore rules

Installation

  1. Clone the repo
    bash git clone https://github.com/Muzain187/TG_MCP.git cd TG_MCP

  2. Create & activate a virtual environment
    bash python3 -m venv venv source venv/bin/activate

  3. Install dependencies
    bash pip install .

    Requires mcp[cli]>=1.6.0 and pyTigerGraph>=1.8.6.

Configuration

Set the following environment variables before running:

export TG_HOST=https://<your-tigergraph-host>
export TG_GRAPH=<your-graph-name>
export TG_SECRET=<your-api-secret>

These are read by config.py.

Connecting to Claude

This MCP server can be installed into the Claude Desktop client so that Claude can invoke your TigerGraph tools directly:

uv run mcp install main.py

After running the above, restart Claude Desktop and you’ll see your MCP tools available via the hammer 🛠 icon.

Examples:

image

image

Contributing

  1. Fork the repository
  2. Create a feature branch
    bash git checkout -b feature/YourFeature
  3. Commit your changes
    bash git commit -m "Add YourFeature"
  4. Push to branch
    bash git push origin feature/YourFeature
  5. Open a Pull Request

Please ensure all new code is covered by tests and follows PEP-8 style.

License

This project is licensed under the MIT License.

See Also

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