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_HOST |
localhost |
ProSuite service host |
PROSUITE_PORT |
5151 |
ProSuite service port |
PROSUITE_SSL_CERT_PATH |
(none) | Path to PEM certificate for TLS |
Usage
Windows users: start at docs/windows-setup.md.
- CLI coding agents (Claude Code, Copilot CLI, opencode): see docs/cli-clients.md
- Any other MCP client (Claude Desktop, other GUI apps, or anything else): see docs/gui-clients.md
Tools
Every tool is defined in src/prosuite_mcp/tools.py: its docstring is the authoritative description, the same one your MCP client shows the LLM.
Example
Once connected, you talk to the assistant in plain language:
Check road connectivity in
C:/data/tlm.sde.
With a spec loaded, the assistant calls describe_spec to see which specifications and workspaces it defines, then run_xml_verification to run one against your data, and returns a summary of errors per condition. The spec goes to the ProSuite service as-is, so per-condition filters and defaults are applied exactly as your domain experts configured them. search_spec browses the conditions in a spec by keyword.
Without a spec, the assistant uses list_conditions and describe_condition to find and configure conditions from scratch, then run_verification to run them ad-hoc. Datasets take a filter_expression here too, but only one per dataset per run, so a spec that filters the same feature class differently in two conditions cannot be reproduced this way.
Development
See docs/development.md.
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