Skip to main content
Glama
Sign In
DataForge Semantic MCP Server

DataForge Semantic MCP Server

by SGromych
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

df_get_rmd

Read-onlyIdempotent

Retrieve normalized semantic context for a DataForge project version, including measures, dimensions, facts, and counts in a single call.

Instructions

Get the normalized semantic context of a project version: project, version, measures, dimensions, facts and counts. Shares one API call and one cache entry with df_get_consolidated_rmd.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "project_id": "<project_id>",
      "version_id": "<version_id>"
    },
    "name": "df_get_rmd"
  }
}

Input Schema

NameRequiredDescriptionDefault
languageNoru
use_cacheNo
project_idYesDataForge project id
version_idYesProject version id
include_rawNoKeep the untouched API payload of every row
include_sqlNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.1

TDQS

B3.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already establish readOnly, idempotent, and non-destructive behavior, so the bar is lower. The description adds meaningful behavioral context beyond annotations: it returns normalized semantic context, includes counts, and shares one API call and one cache entry with df_get_consolidated_rmd, which informs caching and performance expectations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no filler. The main action and return contents are front-loaded, and the cache-sharing note is a single relevant addition. Every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only getter with simple parameters, the description covers the output shape at a high level and the safety profile is handled by annotations. However, it does not clarify when to choose this over df_get_consolidated_rmd despite the shared API call, and the undocumented parameters remain unexplained, which is a noticeable gap given there is no output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 50%, and the description does not compensate for the undocumented parameters (language, use_cache, include_sql). It lists 'project, version' as part of the semantic context but adds no practical meaning to any parameter beyond what the schema already provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states a specific verb ('Get'), a specific resource ('normalized semantic context of a project version'), and enumerates the returned contents (project, version, measures, dimensions, facts, counts). It references the closely related sibling df_get_consolidated_rmd, which helps distinguish it indirectly, though it does not explicitly define the difference between 'normalized' and 'consolidated'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description notes that it shares an API call and cache entry with df_get_consolidated_rmd, but gives no explicit guidance on when to use this tool versus the sibling or other get_* tools. There is no when-to-use or when-not-to-use information, leaving the agent to infer the routing decision.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

Other Tools