itasca-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| ITASCA_MCP_BRIDGE_URL | No | The URL of the active ITASCA bridge service (e.g., http://localhost:9002). This is required for execution tools to connect to a running PFC process. |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
| logging | {} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| extensions | {
"io.modelcontextprotocol/ui": {}
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| itasca_browse_commandsA | Browse Itasca command documentation by path (like glob + cat). Navigation levels:
When to use:
Related tools:
|
| itasca_browse_python_apiA | Browse Itasca Python SDK documentation by path (like glob + cat). |
| itasca_browse_referenceA | Browse ITASCA reference documentation (syntax elements, model properties). Works across engines via the required Navigation levels:
When to use:
Related tools:
|
| itasca_query_commandA | Search Itasca command documentation by keywords (like grep). Returns matching command paths. Use itasca_browse_commands for full documentation. When to use:
Related tools:
|
| itasca_query_python_apiA | Search Itasca Python SDK documentation by keywords (like grep). Returns matching API paths with signatures. Use itasca_browse_python_api for full documentation. When to use:
Related tools:
|
| itasca_execute_taskA | Submit a Python script file for asynchronous execution in the Itasca engine. Returns a task_id immediately; the script runs in the background. Companion tools manage the lifecycle:
While the task is cycling, itasca_execute_code shares the same main namespace in the engine's main thread, so you can inspect or modify simulation state live — probe progress, tune parameters mid-run, swap callbacks, or trigger early termination via a sentinel variable. Submit with reasonable starting values and refine as the task runs. Console output from itasca.command() inside the script (table dumps, list output, command summaries) is captured into the task log alongside Python prints, visible through itasca_check_task_status. Script-writing rules:
|
| itasca_check_task_statusA | Check status and paginated output for a submitted Itasca task. Output combines Python prints and Itasca console output from itasca.command() calls (table dumps, list output, command summaries) interleaved in execution order. Use skip_newest / limit to paginate, or filter to keep only matching lines. |
| itasca_list_tasksA | List tasks tracked by the bridge, newest first. Read-only. Each entry carries task_id, status (pending / running / completed / failed / interrupted), description, entry_script, start_time, end_time and elapsed_time; total_count gives the size of the full history for paging via skip_newest + limit. Task history is persisted in the engine working directory and survives GUI restarts. Use this to recover a task_id from an earlier session, to see what is running or recently finished, or as a cheap bridge-connectivity check. For a task's output and result use itasca_check_task_status; to submit a script use itasca_execute_task. |
| itasca_interrupt_taskA | Request interruption of a pending or running Itasca task. Returns as soon as the request is accepted; it does not wait for the task to stop. Confirm the stop and read the output produced so far with itasca_check_task_status. Only the script stops; the engine state is preserved, so you can inspect it with itasca_execute_code or continue from it with a new itasca_execute_task. Tasks already completed, failed or interrupted return an error. If the task_id is unknown, find it with itasca_list_tasks. |
| itasca_execute_codeA | Execute Python code synchronously in the running Itasca engine process. Returns stdout and an optional result variable immediately. Code runs in the engine's main thread, sharing the same main namespace as any running task — side effects persist and are immediately visible to the task on its next cycle. The tool stays responsive while a task submitted via itasca_execute_task is cycling (calls interleave at cycle gaps), so use it as a live REPL — nothing has to be pre-scripted into the task up front. Typical uses:
Environment: the engine's embedded Python interpreter (Itasca 9+ → Python 3.10, pre-9 → Python 3.6 or older; the product+version is encoded in sys.executable, e.g. PFC900). When unsure, check sys.version_info before relying on newer syntax. Code-writing rules (shared with itasca_execute_task):
Synchronous semantics: the request blocks until the code finishes or hits the timeout (default 10s, max 20s), and output is returned in full. The call is not tracked by itasca_list_tasks and cannot be interrupted mid-execution. For cancellable, pollable, or background work, submit via itasca_execute_task instead. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 10 tools
Each tool has a distinct purpose: task lifecycle tools are separated from execution tools and documentation lookup tools. The sync-vs-async distinction between itasca_execute_code and itasca_execute_task is explicit, and query-vs-browse documentation tools are clearly differentiated. No significant overlap remains.
All tools use a consistent itasca_ prefix followed by snake_case verb_noun patterns. Minor singular/plural variation exists (query_command vs browse_commands), but it does not break predictability. The naming is uniform across the entire set.
Ten tools is well-scoped for an engine bridge that needs task management, code execution, and documentation lookup. Each tool earns its place without excessive surface area.
Core workflows are covered: sync and async execution, task polling, interruption, task listing, and browsing/searching Python API and command docs. Minor gaps exist, such as no keyword-search tool for reference documentation, but agents can work around this via itasca_browse_reference categories.