Frankfurter MCP

Frankfurter is a useful API for latest currency exchange rates, historical data, or time series published by sources such as the European Central Bank. Should you have to access the Frankfurter API as tools for language model agents exposed over the Model Context Protocol (MCP), Frankfurter MCP is what you need.

Installation

If your objective is to use the tools available on this MCP server, please refer to the usage > client sub-section below.

The directory where you clone this repository will be referred to as the working directory or WD hereinafter.

Install uv. To install the project with its minimal dependencies in a virtual environment, run the following in the WD. To install all non-essential dependencies (which are required for developing and testing), replace the --no-dev with the --all-groups flag in the following command.

uv sync --no-dev

Environment variables

Following is a list of environment variables that can be used to configure the application. A template of environment variables is provided in the file .env.template. Note that the default values listed in the table below are not always the same as those in the .env.template file.

The following environment variables can be specified, prefixed with FASTMCP_: HOST, PORT, DEBUG and LOG_LEVEL. See global configuration options for FastMCP. Note that on_duplicate_ prefixed options specified as environment variables will be ignored.

The underlying HTTP client also respects some environment variables, as documented in the HTTPX library. In addition, SSL_CERT_FILE and SSL_CERT_DIR can be configured to use self-signed certificates of hosted API endpoint or intermediate HTTP(S) proxy server(s).

Variable	[Default value] and description
LOG_LEVEL	[INFO] The level for logging. Changing this level also affects the log output of other dependent libraries that may use the same environment variable. See valid values at Python logging documentation.
HTTPX_TIMEOUT	[5.0] The time for the underlying HTTP client to wait, in seconds, for a response from the Frankfurter API.
HTTPX_VERIFY_SSL	[True] This variable can be set to False to turn off SSL certificate verification, if, for instance, you are using a proxy server with a self-signed certificate. However, setting this to False is advised against: instead, use the SSL_CERT_FILE and SSL_CERT_DIR variables to properly configure self-signed certificates.
FAST_MCP_HOST	[localhost] This variable specifies which host the MCP server must bind to unless the server transport (see below) is set to stdio.
FAST_MCP_PORT	[8000] This variable specifies which port the MCP server must listen on unless the server transport (see below) is set to stdio.
MCP_SERVER_TRANSPORT	[stdio] The acceptable options are stdio, sse or streamable-http. However, in the .env.template, the default value is set to stdio.
MCP_SERVER_INCLUDE_METADATA_IN_RESPONSE	[True] This specifies if additional metadata will be included with the MCP type TextContent that wraps the response data from each tool call. The additional metadata, for example, will include the API URL of the Frankfurter server, amongst others, that is used to obtain the responses.
FRANKFURTER_API_URL	[https://api.frankfurter.dev/v1] If you are self-hosting the Frankfurter API, you should change this to the API endpoint address of your deployment.

Usage

The following sub-sections illustrate how to run the Frankfurter MCP as a server and how to access it from MCP clients.

Server

While running the server, you have the choice to use stdio transport or HTTP options (sse or the newer streamable-http).

Using default settings and MCP_SERVER_TRANSPORT set to sse or streamable-http, the MCP endpoint will be available over HTTP at http://localhost:8000/sse for the Server Sent Events (SSE) transport, or http://localhost:8000/mcp for the streamable HTTP transport.

If you want to run Frankfurter MCP with stdio transport and the default parameters, execute the commands below without using the .env.template file.

Server with uv

Optional: Copy the .env.template file to a .env file in the WD, to modify the aforementioned environment variables, if you want to use anything other than the default settings. Or, on your shell, you can export the environment variables that you wish to modify.

Run the following in the WD to start the MCP server.

uv run frankfurtermcp

Server with pip from PyPI package

Add this package from PyPI using pip in a virtual environment (possibly managed by uv, pyenv or conda) and then start the server by running the following.

Optional: Add a .env file with the contents of the .env.template file if you wish to modify the default values of the aforementioned environment variables. Or, on your shell, you can export the environment variables that you wish to modify.

pip install frankfurtermcp
python -m frankfurtermcp.server

Server using Docker

There are two Dockerfiles provided in this repository.

• local.dockerfile for containerising the Frankfurter MCP server.
• smithery.dockerfile for deploying to Smithery AI, which you do not have to use.

To build the image, create the container and start it, run the following in WD. Choose shorter names for the image and container if you prefer.

If you change the port to anything other than 8000 in .env.template, do remember to change the port number references in the following command. Instead of passing all the environment variables using the --env-file option, you can also pass individual environment variables using the -e option.

docker build -t frankfurtermcp -f local.dockerfile .
docker create -p 8000:8000/tcp --env-file .env.template --expose 8000 --name frankfurtermcp-container frankfurtermcp
docker start frankfurtermcp-container

Upon successful build and container start, the MCP server will be available over HTTP at http://localhost:8000/sse for the Server Sent Events (SSE) transport, or http://localhost:8000/mcp for the streamable HTTP transport.

Cloud hosted servers

The currently available cloud hosted options are as follows.

• FastMCP Cloud: https://frankfurtermcp.fastmcp.app/mcp
• Glama.AI: https://glama.ai/mcp/servers/@anirbanbasu/frankfurtermcp
• Smithery.AI: https://smithery.ai/server/@anirbanbasu/frankfurtermcp

Client access

This sub-section explains ways for a client to connect and test the FrankfurterMCP server.

The official MCP visual inspector

The MCP Inspector is an official Model Context Protocol tool that can be used by developers to test and debug MCP servers. This is the most comprehensive way to explore the MCP server.

To use it, you must have Node.js installed. The best way to install and manage node as well as packages such as the MCP Inspector is to use the Node Version Manager (or, nvm). Once you have nvm installed, you can install and use the latest Long Term Release version of node by executing the following.

nvm install --lts
nvm use --lts

Following that (install and) run the MCP Inspector by executing the following in the WD.

npx @modelcontextprotocol/inspector uv run frankfurtermcp

This will create a local URL at port 6274 with an authentication token, which you can copy and browse to on your browser. Once on the MCP Inspector UI, press Connect to connect to the MCP server. Thereafter, you can explore the tools available on the server.

Claude Desktop, Visual Studio, and so on

The server entry to run with stdio transport that you can use with systems such as Claude Desktop, Visual Studio Code, and so on is as follows.

{
    "command": "uv",
    "args": [
        "run",
        "frankfurtermcp"
    ]
}

Instead of having frankfurtermcp as the last item in the list of args, you may need to specify the full path to the script, e.g., WD/.venv/bin/frankfurtermcp. Likewise, instead of using uv, you could also have the following JSON configuration with the path properly substituted for python3.12, for instance such as WD/.venv/bin/python3.12.

{
    "command": "python3.12",
    "args": [
        "-m",
        "frankfurtermcp.server"
    ]
}

List of available MCP features

FrankfurterMCP has the following MCP features.

Tools

The following table lists the names of the tools as exposed by the FrankfurterMCP server. The descriptions shown here are for documentation purposes, which may differ from the actual descriptions exposed over the model context protocol.

Name	Description
get_supported_currencies	Get a list of currencies supported by the Frankfurter API.
get_latest_exchange_rates	Get latest exchange rates in specific currencies for a given base currency.
convert_currency_latest	Convert an amount from one currency to another using the latest exchange rates.
get_historical_exchange_rates	Get historical exchange rates for a specific date or date range in specific currencies for a given base currency.
convert_currency_specific_date	Convert an amount from one currency to another using the exchange rates for a specific date.

The required and optional arguments for each tool are not listed in the following table for brevity but are available to the MCP client over the protocol.

Contributing

Install pre-commit for Git and ruff. Then enable pre-commit by running the following in the WD.

pre-commit install

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Testing and coverage

To run the provided test cases, execute the following. Add the flag --capture=tee-sys to the command to display further console output.

uv run --group test pytest tests/

There is a handy testing script WD/run-tests.sh, which will run all the tests and generate a coverage report as follows. It can also accept arguments and parameters to be passed to pytest, such as -k for filtering the tests to run. If all tests are run, the generated coverage report may look like the one below.

Name                             Stmts   Miss  Cover
----------------------------------------------------
src/frankfurtermcp/__init__.py      10      0   100%
src/frankfurtermcp/common.py        23      0   100%
src/frankfurtermcp/mixin.py         52      4    92%
src/frankfurtermcp/model.py         17      0   100%
src/frankfurtermcp/server.py       111     20    82%
tests/__init__.py                    0      0   100%
tests/test_data_models.py           60      0   100%
tests/test_server.py                71      0   100%
----------------------------------------------------
TOTAL                              344     24    93%

License

MIT.

Project status

Following is a table of some updates regarding the project status. Note that these do not correspond to specific commits or milestones.

Date	Status	Notes or observations
September 6, 2025	active	Code refactoring and cleanup.
June 27, 2025	active	Successful remote deployments on Glama.AI and Smithery.AI.
June 9, 2025	active	Added containerisation, support for self-signed proxies.
June 7, 2025	active	Project started. Added tools to cover all the functionalities of the Frankfurter API.