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GTech-Context-MCP-Server

GTech-Context-MCP-Server

by Venkatesh-Jyothula
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

GTech Networks DB: resolve which tables/docs are relevant to a user query

resolve_tables_for_query

Rank relevant database tables for a natural-language user request, providing reasons, matching workflow documents, and next steps to guide schema fetching.

Instructions

[GTech / Hexagon HxGN NetWorks Core (G/Technology) database only] Only call this for requests already confirmed to concern the GTech/NetWorks Core database (see get_context). Given a natural-language user request (e.g. 'add a new approval step', 'change the order components display in'), returns a ranked list of relevant tables with reasons, plus matching workflow/pattern/relationship docs and concrete next steps. Call this after get_context and before fetching any specific table schema — it tells you WHICH schema docs to fetch instead of guessing.

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": {
      "query": "<query>"
    },
    "name": "resolve_tables_for_query"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoMax tables to recommend, default 8
queryYesThe user's request, in their own words

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It describes output behavior but does not explicitly state it is read-only or non-destructive, nor mention any side effects, authorization needs, or rate limits. Adequate but not fully transparent.

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?

Concise and well-structured; front-loads the domain restriction in brackets. Each of the three sentences adds value: scope, prerequisite, and output. No redundancy or fluff.

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

Completeness4/5

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

Given no output schema, the description compensates by describing return content (ranked list with reasons, workflow/pattern/relationship docs, concrete next steps). Covers prerequisites and workflow position. Lack of response format details prevents a 5.

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

Parameters3/5

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

Schema coverage is 100% with both parameters (query, limit) already described. The tool description does not add significant new semantics beyond restating schema info. Baseline 3 is appropriate.

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

Purpose5/5

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

The description clearly states the tool resolves tables/docs relevant to a user query for the GTech/NetWorks Core database, using specific verbs ('returns a ranked list of relevant tables with reasons...'). It distinguishes from siblings like get_table_schema and get_context by specifying its position in the workflow.

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

Usage Guidelines5/5

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

Explicitly says when to call ('Only call this for requests already confirmed to concern the GTech/NetWorks Core database'), provides sequencing ('Call this after get_context and before fetching any specific table schema'), and explains its value ('tells you WHICH schema docs to fetch instead of guessing').

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

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