jaj-dataverse-dev-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| DATAVERSE_ENVIRONMENTS_PATH | No | Override the path to the environments.json config file |
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
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| pingA | Check that the MCP server is running. |
| list_environmentsA | List the configured Dataverse environments that can be accessed. |
| whoamiB | Get the Dataverse user, business unit and organization for the Azure CLI authenticated identity. |
| dataverse_requestA | Execute a Dataverse Web API request. The path is relative to /api/data/v9.2/. Supports OData queries, CRUD, functions and actions. Use $select and $top where appropriate to avoid unnecessarily large responses. Do not pass a complete URL. |
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 4 tools
Each tool has a clearly distinct purpose: ping checks server availability, list_environments shows configured environments, whoami returns identity info, and dataverse_request handles arbitrary Dataverse API calls. There is no overlap or ambiguity, as the generic tool is explicitly scoped to the Dataverse Web API.
Tool names do not follow a consistent pattern. ping and whoami are single-word commands, list_environments uses verb_noun, and dataverse_request is a noun_noun combination. While readable, the mixed styles are not predictable.
With only 4 tools, the server is well-scoped for its purpose: a few helper tools plus one powerful generic execution tool. This is a reasonable and focused set, not too thin or bloated.
The dataverse_request tool can execute any Dataverse Web API request (CRUD, OData, functions, actions), providing full coverage of the domain. The auxiliary tools add environment and identity context, leaving no obvious gaps in functionality.