iflow-mcp_tg-mcp

# TG_MCP  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](#features) 2. [Project Structure](#project-structure) 3. [Installation](#installation) 4. [Configuration](#configuration) 5. [Connecting to Claude](#connecting-to-claude) 6. [Examples](#examples) 7. [Contributing](#contributing) 8. [License](#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 environm…