prosuite-mcp
OfficialClick on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@prosuite-mcpCheck road connectivity in C:/data/tlm.sde"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
prosuite-mcp
MCP server that exposes Dira ProSuite quality verification to AI assistants (Claude, etc.).
Prerequisites
A running ProSuite Quality Verification Server reachable from the host where this server runs.
Configuration
Environment variable | Default | Description |
|
| ProSuite service host |
|
| ProSuite service port |
| — | Path to PEM certificate for TLS |
Usage
Windows users: see docs/windows-setup.md for a step-by-step guide including uv and Claude Code installation.
Both options below assume you create a project directory first:
mkdir mytest
cd mytest
uv init --python 3.12
uv add prosuite-mcpClaude Code CLI
Register the server from inside mytest, then start Claude:
claude mcp add prosuite \
-e PROSUITE_HOST=localhost \
-e PROSUITE_PORT=5151 \
-- uv run prosuite-mcp
claudeThe -- uv run prosuite-mcp tells Claude Code to start the MCP server via uv run in the current project, so prosuite-mcp is resolved from the local .venv. Run claude from the same mytest directory each time.
Copilot CLI
Register the server from inside mytest, then start Copilot:
copilot mcp add prosuite \
-e PROSUITE_HOST=localhost \
-e PROSUITE_PORT=5151 \
-- uv run prosuite-mcpTools
load_spec <path> — Loads a .qa.xml spec file. Call this at the start of a session with the path to your spec (local drive, OneDrive, network share). Replaces any previously loaded spec.
search_spec <query> [max_results] — Searches the loaded .qa.xml spec for conditions matching a natural-language query (English, German, French, Italian). Returns up to max_results (default 20) matching conditions with pre-filled condition_request blocks ready to pass directly to run_verification, plus the required_datasets list. Requires a spec to be loaded first via load_spec.
list_conditions [search] — Lists available quality conditions. Pass a keyword to filter by name or description.
describe_condition <name> — Shows the full docstring and parameter list for a condition, including which parameters expect dataset names vs. primitive values.
run_verification — Runs an ad-hoc quality verification against a workspace. Key parameters:
Parameter | Type | Description |
| string | Workspace path on the server ( |
| string | Logical name for the data model |
| list | Feature classes/tables: |
| list | Conditions to run: |
| string? | Server-side directory for Issues.gdb and HTML report |
| object? | Spatial filter |
Returns a summary with status, total_errors, and a per-condition breakdown.
Example
Once connected, you talk to Claude in plain language:
Check road connectivity in
C:/data/tlm.sde.
With a spec loaded, Claude calls search_spec to find the relevant pre-configured conditions from the .qa.xml file, then calls run_verification with the pre-filled parameters and returns a summary of errors per condition.
Without a spec, Claude uses list_conditions and describe_condition to find and configure conditions from scratch.
Development
uv sync --dev
uv run pytest
uv run ruff check src
uv run pyright srcLicense
MIT — see LICENSE.
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Maintenance
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