prosuite-mcp
OfficialThis server acts as an MCP gateway for Dira ProSuite geospatial quality verification, enabling AI assistants to perform automated GIS data quality checks through natural language interaction.
Load and manage QA specs: Load a
.qa.xmlspec file at runtime (load_spec), inspect its contents including specifications, workspace definitions, and datasets (describe_spec).Search and discover conditions: Search the loaded spec using natural language queries in English, German, French, or Italian (
search_spec), or list all available quality conditions filtered by keyword (list_conditions).Inspect conditions: Retrieve detailed documentation for specific quality conditions, including parameter types and whether they expect dataset names or primitive values (
describe_condition).Run quality verifications: Execute a named
QualitySpecificationfrom a loaded XML spec with workspace path substitutions (run_xml_verification), or perform ad-hoc verifications by specifying a workspace, datasets, and conditions directly (run_verification).Preview and test: Preview the XML representation of a condition (
condition_to_xml), see how adding a condition would modify a spec (add_condition_to_spec), and preview the execution results of a proposed condition before committing (preview_condition_run).Spatial and output filtering: Optionally restrict verifications to a bounding box and direct output (Issues.gdb, HTML report) to a server-side directory.
Click 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.
Related MCP server: QGIS MCP
Configuration
Environment variable | Default | Description |
|
| ProSuite service host |
|
| ProSuite service port |
| (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
No coding agent permitted? An experimental example drives the same tools from any OpenAI-compatible LLM, local or hosted: see docs/local-llm.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.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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