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tosin2013

mcp-adr-analysis-server

by tosin2013

review_existing_adrs

Read-onlyIdempotent

Review existing ADRs against actual code implementation to identify drift and non-compliance. Get actionable update plans with cloud/DevOps expertise.

Instructions

Review existing ADRs against actual code implementation with cloud/DevOps expertise. TIP: After review, call get_server_context to update @.mcp-server-context.md with findings.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectPathNoPath to the project directory.
specificAdrNoSpecific ADR filename or title to review (optional)
adrDirectoryNoDirectory containing ADR filesdocs/adrs
analysisDepthNoDepth of analysis to performdetailed
includeTreeSitterNoUse tree-sitter for enhanced code analysis
generateUpdatePlanNoGenerate action plan for updating non-compliant ADRs

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changedv2.7.46
    • removedInput schema / properties / conversationContext
      Removed value: -{
      -  "additionalProperties": false,
      -  "description": "Rich context from the calling LLM about user goals and discussion history",
      -  "properties": {
      -    "budget": {
      -      "description": "Budget or resource constraints (e.g., \"limited budget\", \"enterprise scale\")",
      -      "type": "string"
      -    },
      -    "constraints": {
      -      "description": "Limitations, compliance requirements, or restrictions (e.g., [\"GDPR compliance\", \"budget under $50k\", \"minimal downtime\"])",
      -      "items": {
      -        "type": "string"
      -      },
      -      "type": "array"
      -    },
      -    "focusAreas": {
      -      "description": "Specific areas of concern or interest (e.g., [\"security\", \"performance\", \"maintainability\"])",
      -      "items": {
      -        "type": "string"
      -      },
      -      "type": "array"
      -    },
      -    "humanRequest": {
      -      "description": "Original human request text for context restoration and knowledge graph storage",
      -      "type": "string"
      -    },
      -    "previousContext": {
      -      "description": "Relevant context from previous conversation (e.g., \"User mentioned concerns about database splitting\")",
      -      "type": "string"
      -    },
      -    "projectPhase": {
      -      "description": "Current project phase (e.g., \"planning\", \"development\", \"migration\", \"production\")",
      -      "type": "string"
      -    },
      -    "requirements": {
      -      "description": "Specific requirements or preferences mentioned",
      -      "items": {
      -        "type": "string"
      -      },
      -      "type": "array"
      -    },
      -    "timeline": {
      -      "description": "Timeline or urgency information (e.g., \"launch in 3 months\", \"urgent migration\")",
      -      "type": "string"
      -    },
      -    "userGoals": {
      -      "description": "Primary objectives the user wants to achieve (e.g., [\"microservices migration\", \"improve security\"])",
      -      "items": {
      -        "type": "string"
      -      },
      -      "type": "array"
      -    },
      -    "userRole": {
      -      "description": "User's role or expertise level (e.g., \"senior architect\", \"developer\", \"project manager\")",
      -      "type": "string"
      -    }
      -  },
      -  "type": "object"
      -}
  2. Addedv1.0.0

TDQS

B3.1/5.0
Behavior3/5

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

The description does not contradict the readOnlyHint annotation and adds a small amount of context: the cloud/DevOps analytical perspective and the fact that findings are meant to be persisted later via get_server_context. However, it does not disclose operational details such as file read scope, analysis depth semantics, or side effects beyond the annotation's read-only signal.

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?

The description is compact and front-loaded with the core purpose, followed by a useful actionable TIP. The 'cloud/DevOps expertise' phrase is slightly generic but does not add meaningful bloat.

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?

The tool has six parameters and no output schema, so the description carries more responsibility to explain what the review produces. It only mentions 'findings' without describing their structure, and it does not clarify how analysisDepth affects output or how specificAdr is matched. The agent must infer too much from the name and schema alone.

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 description's omission of parameter details is acceptable. It adds no additional meaning about how projectPath, adrDirectory, or analysisDepth interact, but the schema already documents these sufficiently.

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 action ('Review') on a defined resource ('existing ADRs') with an explicit comparison target ('actual code implementation'). It is reasonably distinct from sibling tools like validate_adr or suggest_adrs, though it doesn't name them.

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 phrasing implies when the tool is relevant—checking ADRs against implementation—but it provides no explicit when-to-use guidance, exclusions, or alternative sibling tools. The TIP about get_server_context is follow-up workflow advice, not selection guidance.

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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