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CodeGuardian MCP

CodeGuardian MCP

by codegoddy
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TypeScript
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build_context

Build or rebuild a comprehensive project context index, capturing symbols, git history, and intent signals to enable accurate validation of AI-generated code against the actual codebase.

Instructions

Build or rebuild project context including symbols, git history, and intent signals. Usually auto-called by other tools.

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": {
      "projectPath": "<projectPath>"
    },
    "name": "build_context"
  }
}

Input Schema

NameRequiredDescriptionDefault
languageNoProgramming language to focus on (default: all)all
maxFilesNoMaximum files to index (default: 1000)
projectPathYesRoot path of the project to analyze
forceRebuildNoForce rebuild even if cached
includeTestsNoInclude test files in context (default: true)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.4.8

TDQS

B3.4/5.0
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 burden of behavioral disclosure. It mentions rebuilding and the components of context, but does not disclose side effects, cache invalidation, resource intensity, idempotency, or whether this can destroy previous context. For a tool that can 'rebuild', this is a significant transparency gap.

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 wasted words. The core purpose is front-loaded, and the second sentence adds valuable invocation context without padding.

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

Completeness2/5

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

With no output schema and no annotations, the tool description should explain what happens after the call and what the agent receives. It does not mention return values, completion semantics, or side effects, and the five parameters remain contextually underspecified beyond their schema definitions. The auto-call note helps but is not sufficient.

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 description coverage is 100%, so the schema already documents all five parameters adequately. The description adds no parameter-specific meaning, but the baseline of 3 is appropriate given that the schema handles the heavy lifting.

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 uses a specific verb phrase, 'Build or rebuild project context', and names the concrete contents it covers: symbols, git history, and intent signals. This clearly distinguishes the tool from the validation and guardian sibling tools, which focus on different concerns.

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 phrase 'Usually auto-called by other tools' gives a useful invocation signal, implying that direct calls may be rare. However, it does not state when an agent should call it directly, when to avoid it, or how it relates to alternative tools like start_validation or get_dependency_graph.

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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