Git RAG MCP Server

by vamsi-desu

Overview Schema Source Related Servers Discussions Admin

Python

Local

validate_rag_result

Check a RAG operation result for basic validity to catch issues before using it in GitHub, file, or QA workflows.

Instructions

Perform basic validation of a RAG MCP tool result.

Args: operation: RAG operation being tested.

result:
    Result returned by the RAG MCP server.

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": {
      "operation": "<operation>",
      "result": "<result>"
    },
    "name": "validate_rag_result"
  }
}

Input Schema

Name	Required	Description	Default
`result`	Yes
`operation`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 13, 2026

TDQS

C2.8/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. 'Basic validation' is undefined: it does not say which checks run, whether a failed result raises an error or returns a negative verdict, or whether the tool is read-only. This is a significant gap for a validation tool.

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

Conciseness4/5

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

Short and front-loaded: one purpose sentence followed by a tidy Args block. Nothing is padded, though the Args entries are so terse they add little information.

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?

An output schema exists, so return values need not be described. However, with no annotations, no enum on 'operation', and 0% schema coverage, the definition does not give an agent enough to construct a correct call or predict validation outcomes.

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 0%, so the description must compensate. It only restates the parameter names ('operation: RAG operation being tested', 'result: Result returned by the RAG MCP server') without giving accepted operation values, string formats, or whether 'result' is raw text or serialized JSON.

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?

States a specific verb and resource ('validate a RAG MCP tool result'), which distinguishes it from the sibling validate_github_result by target system. It stops short of explaining what 'basic validation' actually checks, so the boundary of its behavior is fuzzy.

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?

There is no guidance on when to call this versus validate_github_result, nor any precondition such as having just invoked a RAG operation. The Args block documents inputs but not invocation context, leaving usage to inference.

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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