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MCP-Server-Truerag
模型上下文协议(MCP)服务器以访问Truerag实例
3 years
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Model Context Protocol (MCP) Server for GraphQL Policies API
This repository contains a Model Context Protocol (MCP) server implementation for a GraphQL API that provides access to policies.
The server is built using the python SDK for MCP and uses the GQL library to interact with the GraphQL API.
Getting Started
Clone the repository
git clone https://github.com/Ad-Veritas/mcp-server-trueRAG.git
cd mcp-server-trueRAG
Make sure you have uv installed
uv --version
If not, you can install it using:
# On macOS and Linux.
curl -LsSf https://astral.sh/uv/install.sh | sh
# On Windows.
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
Define the environment variables
The server is configured to work against a GraphQL API for one of the TrueRag systems. Once you created the TrueRAG environment, copy the API key and endpoint from the environment variables.
Create a .env
file in the root directory of the repository and add the following lines:
GRAPHQL_API_KEY = "{your_api_key}"
GRAPHQL_ENDPOINT = "{your_graphql_endpoint}"
Add to the MCP Client, such as Claude Desktop
Add the following lines to the Claude configuration file (~/Library/Application Support/Claude/claude_desktop_config.json
):
"shipping-policies": {
"command": "uv",
"args": [
"--directory",
"{path_to_mcp_server}/mcp-server-trueRAG",
"run",
"fastmcp",
"run",
"server.py"
]
}
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Reviews

user_A06VnBBV
Food Data Central MCP Server by jlfwong is a fantastic tool for anyone needing accurate and comprehensive food data. It’s reliable, fast, and integrates seamlessly into our existing systems. Whether you’re building a nutrition app or simply need extensive food datasets, this server has you covered. Highly recommend! Check it out: https://mcp.so/server/food-data-central-mcp-server/jlfwong