dbahn-stations-mcp
v1.0.0
Published
The official MCP Server for the Dbahn Stations API
Readme
Dbahn Stations TypeScript MCP Server
It is generated with Stainless.
Installation
Direct invocation
You can run the MCP Server directly via npx:
export DBAHN_STATIONS_CLIENT_ID="My Client ID"
export DBAHN_STATIONS_CLIENT_SECRET="My Client Secret"
npx -y dbahn-stations-mcp@latestVia MCP Client
There is a partial list of existing clients at modelcontextprotocol.io. If you already have a client, consult their documentation to install the MCP server.
For clients with a configuration JSON, it might look something like this:
{
"mcpServers": {
"dbahn_stations_api": {
"command": "npx",
"args": ["-y", "dbahn-stations-mcp", "--client=claude", "--tools=all"],
"env": {
"DBAHN_STATIONS_CLIENT_ID": "My Client ID",
"DBAHN_STATIONS_CLIENT_SECRET": "My Client Secret"
}
}
}
}Cursor
If you use Cursor, you can install the MCP server by using the button below. You will need to set your environment variables
in Cursor's mcp.json, which can be found in Cursor Settings > Tools & MCP > New MCP Server.
VS Code
If you use MCP, you can install the MCP server by clicking the link below. You will need to set your environment variables
in VS Code's mcp.json, which can be found via Command Palette > MCP: Open User Configuration.
Claude Code
If you use Claude Code, you can install the MCP server by running the command below in your terminal. You will need to set your
environment variables in Claude Code's .claude.json, which can be found in your home directory.
claude mcp add --transport stdio dbahn_stations_api --env DBAHN_STATIONS_CLIENT_ID="Your DBAHN_STATIONS_CLIENT_ID here." DBAHN_STATIONS_CLIENT_SECRET="Your DBAHN_STATIONS_CLIENT_SECRET here." -- npx -y dbahn-stations-mcpExposing endpoints to your MCP Client
There are three ways to expose endpoints as tools in the MCP server:
- Exposing one tool per endpoint, and filtering as necessary
- Exposing a set of tools to dynamically discover and invoke endpoints from the API
- Exposing a docs search tool and a code execution tool, allowing the client to write code to be executed against the TypeScript client
Filtering endpoints and tools
You can run the package on the command line to discover and filter the set of tools that are exposed by the MCP Server. This can be helpful for large APIs where including all endpoints at once is too much for your AI's context window.
You can filter by multiple aspects:
--toolincludes a specific tool by name--resourceincludes all tools under a specific resource, and can have wildcards, e.g.my.resource*--operationincludes just read (get/list) or just write operations
Dynamic tools
If you specify --tools=dynamic to the MCP server, instead of exposing one tool per endpoint in the API, it will
expose the following tools:
list_api_endpoints- Discovers available endpoints, with optional filtering by search queryget_api_endpoint_schema- Gets detailed schema information for a specific endpointinvoke_api_endpoint- Executes any endpoint with the appropriate parameters
This allows you to have the full set of API endpoints available to your MCP Client, while not requiring that all of their schemas be loaded into context at once. Instead, the LLM will automatically use these tools together to search for, look up, and invoke endpoints dynamically. However, due to the indirect nature of the schemas, it can struggle to provide the correct properties a bit more than when tools are imported explicitly. Therefore, you can opt-in to explicit tools, the dynamic tools, or both.
See more information with --help.
All of these command-line options can be repeated, combined together, and have corresponding exclusion versions (e.g. --no-tool).
Use --list to see the list of available tools, or see below.
Code execution
If you specify --tools=code to the MCP server, it will expose just two tools:
search_docs- Searches the API documentation and returns a list of markdown resultsexecute- Runs code against the TypeScript client
This allows the LLM to implement more complex logic by chaining together many API calls without loading intermediary results into its context window.
The code execution itself happens in a Deno sandbox that has network access only to the base URL for the API.
Specifying the MCP Client
Different clients have varying abilities to handle arbitrary tools and schemas.
You can specify the client you are using with the --client argument, and the MCP server will automatically
serve tools and schemas that are more compatible with that client.
--client=<type>: Set all capabilities based on a known MCP client- Valid values:
openai-agents,claude,claude-code,cursor - Example:
--client=cursor
- Valid values:
Additionally, if you have a client not on the above list, or the client has gotten better over time, you can manually enable or disable certain capabilities:
--capability=<name>: Specify individual client capabilities- Available capabilities:
top-level-unions: Enable support for top-level unions in tool schemasvalid-json: Enable JSON string parsing for argumentsrefs: Enable support for $ref pointers in schemasunions: Enable support for union types (anyOf) in schemasformats: Enable support for format validations in schemas (e.g. date-time, email)tool-name-length=N: Set maximum tool name length to N characters
- Example:
--capability=top-level-unions --capability=tool-name-length=40 - Example:
--capability=top-level-unions,tool-name-length=40
- Available capabilities:
Examples
- Filter for read operations on cards:
--resource=cards --operation=read- Exclude specific tools while including others:
--resource=cards --no-tool=create_cards- Configure for Cursor client with custom max tool name length:
--client=cursor --capability=tool-name-length=40- Complex filtering with multiple criteria:
--resource=cards,accounts --operation=read --tag=kyc --no-tool=create_cardsRunning remotely
Launching the client with --transport=http launches the server as a remote server using Streamable HTTP transport. The --port setting can choose the port it will run on, and the --socket setting allows it to run on a Unix socket.
Authorization can be provided via the following headers:
| Header | Equivalent client option | Security scheme |
| -------------- | ------------------------ | --------------- |
| DB-Client-ID | clientID | ClientID |
| DB-Api-Key | clientSecret | ClientSecret |
A configuration JSON for this server might look like this, assuming the server is hosted at http://localhost:3000:
{
"mcpServers": {
"dbahn_stations_api": {
"url": "http://localhost:3000",
"headers": {
"DB-Client-ID": "My Client ID"
}
}
}
}The command-line arguments for filtering tools and specifying clients can also be used as query parameters in the URL. For example, to exclude specific tools while including others, use the URL:
http://localhost:3000?resource=cards&resource=accounts&no_tool=create_cardsOr, to configure for the Cursor client, with a custom max tool name length, use the URL:
http://localhost:3000?client=cursor&capability=tool-name-length%3D40Importing the tools and server individually
// Import the server, generated endpoints, or the init function
import { server, endpoints, init } from "dbahn-stations-mcp/server";
// import a specific tool
import retrieveStations from "dbahn-stations-mcp/tools/stations/retrieve-stations";
// initialize the server and all endpoints
init({ server, endpoints });
// manually start server
const transport = new StdioServerTransport();
await server.connect(transport);
// or initialize your own server with specific tools
const myServer = new McpServer(...);
// define your own endpoint
const myCustomEndpoint = {
tool: {
name: 'my_custom_tool',
description: 'My custom tool',
inputSchema: zodToJsonSchema(z.object({ a_property: z.string() })),
},
handler: async (client: client, args: any) => {
return { myResponse: 'Hello world!' };
})
};
// initialize the server with your custom endpoints
init({ server: myServer, endpoints: [retrieveStations, myCustomEndpoint] });Available Tools
The following tools are available in this MCP server.
Resource stations:
retrieve_stations(read): Get a QueryResult object containing one station object specified by its id.list_stations(read): Get a QueryResult object containing station objects from the database applying to the parameters described below.QueryResult is a container providing the following information about the query result.
- the total number of hits
- the maximum number of hits to be returned in that QueryResult object
- the offset of the first hit returned in that QueryResult object with respect to all hits returned by the query
- the result objects
The parameters described below work as filters to reduce the number of hits returned. Some of these parameters must be used only once, others are allowed to be used multiple times. Valid parameters that are allowed to be used only once are offset, limit and logicaloperator.
All other parameters described below may be used multiple times.
If a parameter is given more than once, the result will contain all hits that match all given parameter values.
E.g. federalstate=berlin&federalstate=saarland returns all stations in Berlin and Saarland.
If more than one filter criterion is used at the same time, the different filter criteria are interpreted as if they are combined by a logical AND operator, unless the parameter logicaloperator is set to or.
E.g. category=1-2&federalstate=hamburg returns all stations in Hamburg having category 1 or 2.
category=1-2&federalstate=hamburg&federalsate=hessen returns all stations in Hamburg and Hessen having category 1 or 2, while
searchstring=berlin*&federalstate=hamburg&federalsate=hessen&logicaloperator=or will return all stations with a name starting with 'berlin' as well as all stations in Hamburg and Hessen.
If no 'limit' parameter is given, the number of hits (stations) is set to its maximum value of 10000.
To specify parameter values containing German umlauts, the following encoding has to be used
- ä => %C3%A4
- ö => %C3%B6
- ü => %C3%BC
- Ä => %C3%84
- Ö => %C3%96
- Ü => %C3%9C
- ß => %C3%9F
Resource szentralen:
retrieve_szentralen(read): Get a QueryResult object containing one SZentralen object specified by its id.list_szentralen(read): Get a QueryResult object containing SZentralen objects from the database applying to the parameters described below. QueryResult is a container providing the following information about the query result.- the total number of hits
- the maximum number of hits to be returned in that QueryResult object
- the offset of the first hit returned in that QueryResult object with respect to all hits returned by the query
- the result objects
