home / mcp / account and transaction api mcp server
MCP Server generated by mcp.ag2.ai
Configuration
View docs{
"mcpServers": {
"ag2-mcp-servers-account-and-transaction-api-specification": {
"url": "https://api.apis.guru/v2/specs/openbanking.org.uk/account-info-openapi/3.1.7/openapi.json",
"headers": {
"CONFIG": "YOUR_CONFIG_JSON_STRING",
"SECURITY": "YOUR_SECURITY_VARS",
"CONFIG_PATH": "YOUR_CONFIG_PATH"
}
}
}
}You can use this MCP Server to bridge your client with the Open Banking account-info API by exposing a dedicated MCP interface. It lets you connect, query, and operate on the OpenAPI-defined endpoints through standardized MCP requests, enabling consistent context-aware data access across your applications.
Start the MCP server in stdio mode and connect your MCP client to it using the provided MCP URL or the local stdio channel. Use the HTTP configuration when you want to point to a remote MCP instance, or run the server locally via the stdio entry to keep all processing in-process. Your client will be able to request account information endpoints defined by the OpenAPI specification and receive responses that include the modeled context data.
Prerequisites: you need Python 3.9 or later, plus pip and uv to run the server.
Clone the MCP server repository and navigate into it.
git clone <repository-url>
cd mcp_serverInstall dependencies. You can use the development environment setup script or install manually.
pip install -e ".[dev]"
```
Alternatively, you can use uv to install in editable mode via the same path.Run the server in stdio mode using Python. This starts the MCP server process and wires the MCP protocol to the local Python process.
python mcp_server/main.py stdioYou can configure the server with environment variables to customize how it loads configuration and security parameters.
CONFIG_PATH=/path/to/mcp_config.json
CONFIG='{"openapi":"https://api.apis.guru/v2/specs/openbanking.org.uk/account-info-openapi/3.1.7/openapi.json"}'
SECURITY={"API_KEY":"YOUR_API_KEY"}Check code quality and formatting using linter rules (ruff) to ensure consistent style and catch potential issues.
Automatically format the codebase to maintain a consistent coding style using the formatter (ruff).
Run static analysis including type checks (mypy), security checks (bandit), and semantic analysis (semgrep) to improve reliability.
Execute unit tests with coverage to verify the MCP server behavior and to catch regressions.
Build and publish artifacts with the project toolchain (hatch) for distribution.