MCP Model Explorer¶

The Model Explorer is the HTTP/SSE MCP server that lets AI assistants discover, inspect, and operate on your AMSDAL models via natural language.

Available Tools¶

list_available_models¶

Discover all registered AMSDAL models with their fields and relationships.

Parameters:

Parameter	Type	Description
`scope`	`str \\| None`	Optional filter by scope: `core`, `contrib`, or `user`

Returns a list of models with: - Model name - Field names - Foreign key relationships

list_available_transactions¶

Lists all available AMSDAL transactions. Use this to discover executable transactions before running one.

Parameters:

Parameter	Type	Description
`scope`	`str`	Filter by scope: `all` (default), `user` (custom user-defined), or `contrib` (system-level/shared)

Returns a catalog of transactions with their name, description, scope, and parameter types.

list_available_skills¶

Lists registered AMSDAL Skills (reusable, named instructions). In the MCP/agent chat flow this tool is called first so the assistant knows which skills apply to the request. See Skills.

Returns each skill's name, description, use_when, and requires_user_approval.

get_model_schema¶

Get the object schema for a specific model.

Parameters:

Parameter	Type	Description
`model_name`	`str`	Name of the AMSDAL model

Returns the model's object schema with field types, constraints, and defaults.

get_model_relationships¶

Inspect a model's foreign key graph — both outgoing (many-to-one) and incoming (one-to-many) relationships.

Parameters:

Parameter	Type	Description
`model_name`	`str`	Name of the AMSDAL model

Returns outgoing and incoming relationship details with field names, target models, and cardinality.

perform_crud_operation¶

Execute CRUD operations using natural language with a two-step confirmation flow.

Parameters:

Parameter	Type	Description
`model_name`	`str`	Name of the AMSDAL model
`operation`	`str`	One of: `read`, `create`, `update`, `delete`
`query`	`str`	Natural language description of the operation
`confirm`	`bool`	Set to `true` to execute after preview (default `false`)
`preview_limit`	`int`	Max records to show in preview (default `5`)
`limit`	`int \\| None`	Max records to return (default `30`)
`analysis`	`dict \\| None`	Analysis from step 1, passed back in step 2 (default `None`)

Two-step flow:

First call with confirm=false — returns a preview with an analysis dict
Second call with confirm=true and the analysis from step 1 — executes the operation

This prevents accidental data modifications through AI assistants.

perform_transaction_operation¶

Executes AMSDAL transactions from natural language descriptions using a mandatory two-step confirmation flow. The raw query is passed to an AI planner that maps arguments (primitives, model references, or new objects) to the expected transaction parameters.

Parameters:

Parameter	Type	Description
`transaction_name`	`str`	Name of the AMSDAL transaction
`query`	`str`	Raw natural language description of the operation exactly as typed by the user
`confirm`	`bool`	Set to `true` to execute after preview (default `false`)
`preview_limit`	`int`	Max records to show in preview for reference searches (default `5`)
`analysis`	`dict \\| None`	Analysis from step 1, passed back in step 2 (default `None`)

Two-step flow:

First call with confirm=false — returns a preview mapping with an analysis dict showing how arguments were parsed.
Second call with confirm=true and the analysis from step 1 — executes the transaction.

Example Conversation¶

A typical conversation with an AI assistant connected via MCP:

User: What models are available?

Assistant calls list_available_models

Assistant: You have Customer, Order, Product, and Invoice models.

User: Update John Doe's email to john@new.com

Assistant calls perform_crud_operation(model_name='Customer', operation='update', query='update John Doe email to john@new.com', confirm=false)

Assistant: This will change John Doe's email from john@old.com to john@new.com. Confirm?

User: Yes

Assistant calls with confirm=true

User: Are there any custom actions I can perform?

Assistant calls list_available_transactions(scope='user')

Assistant: Yes, you can run the apply_discount transaction.

User: Apply a 10% discount to John Doe's last order.

Assistant calls perform_transaction_operation(transaction_name='apply_discount', query='Apply a 10% discount to John Doe\\'s last order', confirm=false)

Assistant: This will run the apply_discount transaction mapping John Doe's last order to the order parameter and 10 to the percentage parameter. Confirm?

User: Yes

Assistant calls perform_transaction_operation(..., confirm=true, analysis=...)

Row-Level Filtering¶

The Model Explorer uses api_objects manager, which applies row-level permissions automatically. Users only see and modify records they're authorized to access.