MCP (Model Context Protocol) Server
@DrFloflo
About MCP (Model Context Protocol) Server
Omni MCP protocol, chose the right tools for you.
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"MCPo-Server": {
"command": "python",
"args": [
"server.py"
]
}
}
}Tools
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Overview
What is MCP (Model Context Protocol) Server?
This server provides a unified interface for interacting with multiple services including GitHub, Azure Log Analytics, Google, Azure OpenAI, Azure Vision, and PostgreSQL. It is designed for developers who need a single MCP endpoint to access diverse APIs and data sources.
How to use MCP (Model Context Protocol) Server?
Install dependencies via pip install -r requirements.txt, create a .env file with required tokens (GitHub PAT, Azure credentials, etc.), then run python server.py. The server starts on http://0.0.0.0:6277 by default. Docker is also supported: build with docker build -t mcp-server . and run with docker run -p 6277:6277 --env-file .env mcp-server.
Key features of MCP (Model Context Protocol) Server
- Retrieve files and directory listings from GitHub repositories
- Monitor GitHub workflow runs and code search
- Run Kusto Query Language (KQL) queries on Azure Log Analytics
- Read PostgreSQL databases with read-only user support
- Search Google and YouTube, get YouTube video transcripts
- Analyze images via Azure Vision and generate responses via Azure OpenAI
Use cases of MCP (Model Context Protocol) Server
- Search code across GitHub repositories and inspect commit diffs
- Query Azure Log Analytics for operational insights or security logs
- Get structured content from websites in Markdown format
- Retrieve YouTube video transcripts for analysis or summarization
- Execute read-only queries on PostgreSQL databases
FAQ from MCP (Model Context Protocol) Server
What prerequisites are needed?
Python 3.8+, optional Docker, and service-specific tokens: GitHub PAT (repo scope), Azure AD client ID/secret/tenant, Azure OpenAI key/endpoint, Azure Vision key/endpoint, and PostgreSQL credentials.
How do I set up tokens?
Create a .env file with the required variables as described in the README (e.g., GITHUB_TOKEN, AZURE_CLIENT_ID, etc.). Each service’s token setup is detailed in the respective section.
Can I run the server in Docker?
Yes. Build the Docker image with docker build -t mcp-server . and run it with docker run -p 6277:6277 --env-file .env mcp-server. Ensure your .env file is present.
Does the PostgreSQL access allow write operations?
No. The recommended practice is to use a database user with SELECT-only privileges. The read_db tool is designed for read-only queries.
What transports or authentication does the server use?
The server listens on HTTP (0.0.0.0:6277). Authentication for each external service is handled via tokens/credentials stored in the .env file; no additional transport-level security is described.
Frequently asked questions
What prerequisites are needed?
Python 3.8+, optional Docker, and service-specific tokens: GitHub PAT (`repo` scope), Azure AD client ID/secret/tenant, Azure OpenAI key/endpoint, Azure Vision key/endpoint, and PostgreSQL credentials.
How do I set up tokens?
Create a `.env` file with the required variables as described in the README (e.g., `GITHUB_TOKEN`, `AZURE_CLIENT_ID`, etc.). Each service’s token setup is detailed in the respective section.
Can I run the server in Docker?
Yes. Build the Docker image with `docker build -t mcp-server .` and run it with `docker run -p 6277:6277 --env-file .env mcp-server`. Ensure your `.env` file is present.
Does the PostgreSQL access allow write operations?
No. The recommended practice is to use a database user with `SELECT`-only privileges. The `read_db` tool is designed for read-only queries.
What transports or authentication does the server use?
The server listens on HTTP (`0.0.0.0:6277`). Authentication for each external service is handled via tokens/credentials stored in the `.env` file; no additional transport-level security is described.
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