Jaquel

You can run this MCP server to connect to ASAM ODS, inspect schemas, validate and execute JAQueL queries, access timeseries data, and generate analysis visuals. It provides built-in ODS connection management and interactive workflows to explore measurement hierarchies and perform bulk data operations, all via the MCP protocol so you can integrate with compatible clients.

How to use

To start using the Jaquel MCP Server with your MCP client, install the server using one of the supported methods, then launch it and connect your client to the provided stdio endpoints. Once connected, you can establish an ODS connection, inspect schemas, validate and execute JAQueL queries, access submatrices of measurement data, and generate analysis artifacts like notebooks and visualization code.

How to install

Prerequisites: Python and a supported runtime are available on your system. You may also use a lightweight environment manager if you prefer isolating dependencies.

Choose one of the installation approaches below and follow the steps in order.

Using uvx (recommended for automatic installation and running)

uvx odsbox-jaquel-mcp@latest

Using pipx for a persistent installation

pipx install odsbox-jaquel-mcp
odsbox-jaquel-mcp

Traditional Python virtual environment with pip and the play extra (for data analysis dependencies)

python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
pip install odsbox-jaquel-mcp[play]

Starting the server

After installation, start the server using one of the supported runtime commands. The server runs on standard input and output, waiting for MCP messages from a client.

# Using uvx (auto-installs and runs)
uvx odsbox-jaquel-mcp@latest

# Using pipx (if installed)
odsbox-jaquel-mcp

# With a Python virtual environment
python -m odsbox_jaquel_mcp

Available tools

ods_connect

Establishes a connection to an ASAM ODS server, enabling subsequent operations against the ODS data source.

ods_disconnect

Closes the current ODS connection and cleans up related resources.

ods_get_connection_info

Retrieves the current status and details of the active ODS connection.

schema_get_entity

Fetches all fields and metadata for a specific entity within the ODS schema.

schema_list_entities

Lists all entities in the ODS schema along with their relationships.

schema_test_to_measurement_hierarchy

Maps ASAM ODS test hierarchy to measurement hierarchy for exploration.

query_validate

Validates JAQueL query syntax and structure before execution.

query_describe

Explains a JAQueL query in plain English to aid understanding.

query_execute

Executes a validated JAQueL query against the ODS server and returns results.

data_get_quantities

Lists measurement quantities available for a given submatrix.

data_read_submatrix

Reads timeseries data from a specified submatrix.

data_generate_fetcher_script

Generates Python scripts to fetch data from ODS according to a template.

query_generate_skeleton

Generates a basic query skeleton for a given entity.

query_get_pattern

Provides templates for common JAQueL query patterns.

query_list_patterns

Lists all available JAQueL query patterns.

query_get_operator_docs

Gives documentation on operators used in JAQueL queries.