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MCP Codebase RAG Server

MCP Codebase RAG Server

by di5rupt0r
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

get_file_content

Retrieves the full file content from a codebase, optionally verifying the file belongs to a specified project before reading. Returns the content as a string.

Instructions

Return the full content of a given file path.

Args:
    path: File path to read
    project: When supplied, validates that the path belongs to this project
             before reading. Raises an error if the path is not indexed.
    
Returns:
    File content as string

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": {
      "path": "<path>"
    },
    "name": "get_file_content"
  }
}

Input Schema

NameRequiredDescriptionDefault
pathYes
projectNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It transparently describes the validation behavior, error condition for non-indexed paths, and return type as a string. It does not address edge cases like binary files or encoding, but this is a simple read tool.

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?

The description is concise and well-structured with Args and Returns sections. Every sentence is informative with no wasted words.

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

Completeness5/5

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

The tool is simple with two parameters and an output schema present. The description covers purpose, parameter behavior, and error handling, making it complete for an agent to select and invoke correctly.

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

Parameters5/5

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

The input schema has no descriptions for parameters (0% coverage), so the description fully compensates. It explains path as the file to read and project as an optional validation parameter that raises an error if the path is not indexed, adding significant semantic meaning.

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 returns the full content of a given file path. This specific verb+resource phrasing distinguishes it from sibling tools like search_codebase or list_indexed_projects.

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

Usage Guidelines3/5

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

The description explains how to use the project parameter but does not explicitly state when to use this tool versus alternatives. Usage is implied by the read operation, but no exclusions or alternative tool mentions are provided.

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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