MCP Development

Skill Location: This file

Quick Start

Create MCP server: /toolkit:build:package → Full structure with SDK setup

Define tools: Follow <tool_schema> template with JSON Schema validation

Choose transport: stdio (local) or http (remote) based on use case

Validate server: scripts/test_mcp.sh → Quick integration testing

Why: MCP provides structured tool definitions with type safety—prevents runtime errors from malformed inputs.

Navigation

Critical Reference Loading

Key Reference: Authentication patterns in pattern_auth_patterns.md contain JSON Schema validation rules critical for runtime stability. Read these patterns in full when implementing authentication—summarization causes validation failures.

System Requirements

• MCP SDK: @modelcontextprotocol/sdk (latest via npm/pnpm)
• TypeScript: >= 5.0
• Node.js: >= 18
• Validation: scripts/test_mcp.sh (bundled CLI abstraction)
• Transport: stdio (local) or http (remote)
• Schema: Valid JSON Schema for tool input/output

Operational Patterns

This skill follows these behavioral patterns:

• Planning: Switch to planning mode for architectural decisions
• Discovery: Locate files matching patterns and search file contents for MCP integration
• Delegation: Delegate planning and exploration to specialized workers
• Tracking: Maintain a visible task list for MCP development

<critical_constraint> Use native tools to fulfill these patterns. The System Prompt selects the correct implementation for semantic directives. </critical_constraint>

Implementation Patterns

Pattern: Tool Definition Template

{
  "name": "tool_name",
  "description": "Tool to <verb> <resource>. Use when <condition>. Constraints: <limits>.",
  "inputSchema": {
    "type": "object",
    "properties": {
      "param_name": {
        "type": "string",
        "description": "Parameter description",
        "enum": ["value1", "value2"],
        "format": "email"
      }
    },
    "required": ["param_name"],
    "additionalProperties": false
  },
  "outputSchema": {
    "type": "object",
    "properties": {
      "result": { "type": "string", "description": "Result description" }
    }
  }
}

Pattern: stdio Transport (Local)

{
  "transport": {
    "type": "stdio",
    "command": "node",
    "args": ["server.js"]
  }
}

Pattern: http Transport (Remote)

{
  "transport": {
    "type": "http",
    "url": "http://localhost:3000",
    "authentication": {
      "type": "bearer",
      "token": "${API_TOKEN}"
    }
  }
}

Pattern: Error Message

"Invalid input: parameter must be a valid email address. Please provide a valid email like [email protected]."

Troubleshooting

<mission_control> Create portable MCP servers with strict tool schema definitions, clear transport logic, and prompt-engineered descriptions that guide agent behavior <success_criteria>Generated MCP server has valid JSON Schema for tools, prompt-engineered descriptions, and proper transport configuration</success_criteria> <standards_gate> Before creating MCP servers, review:

• Tool schema & transport → https://code.claude.com/docs/en/mcp.md
• Authentication patterns → Glob: lookup_auth_patterns.md </standards_gate> </mission_control>

<interaction_schema> design → tool_schema_definition → transport_logic → validation → output</interaction_schema>

MCP (Model Context Protocol) servers provide structured integration between Claude and external systems. They define tools, resources, and prompts that Claude can access through standardized protocols.

Core principle: Treat every MCP tool like a tiny, well-written prompt for the agent. The descriptions and schemas you write directly influence how well Claude understands and uses your tools.

Prompt Engineering for Tool Descriptions

<description_pattern> Structure tool descriptions to maximize agent understanding

<template_formula>

Standard description format:

description: "Brief description, non spoiling of the content. Use when {trigger condition + keywords + key sentences user might say that should lead the tool to be invoked}. Not for {exclusions}."

Alternative formula (MCP-style):

Tool to <verb> <resource>. Use when <trigger condition>. Constraints: <key limits>.

{
  "name": "create_channel",
  "description": "Tool to create a new Slack channel. Use when the user asks to create a new channel, make a new channel, or set up a channel."
}

{
  "name": "create_contact",
  "description": "Tool to create a new Salesforce contact. Use when the user wants to create a contact, add a new contact, or input contact data. Required workflow: call discover_required_fields('Contact') first to identify mandatory fields and prevent creation errors. Not for bulk imports."
}

{
  "name": "get_calls",
  "description": "Tool to list all calls in a date range. Use when the user asks for calls across a workspace without user/workspace filtering. Constraint: this tool does not support user or workspace filters; for filtered calls, use search_calls_extensive instead. Not for real-time or live call data."
}

<structure_rules>

1. Start with action: Verb + resource (what the tool does)
2. Add trigger condition: Keywords and phrases that activate the tool
3. Front-load constraints: Required workflows, hard limits, alternatives
4. End with exclusions: "Not for" clause prevents misuse

</structure_rules>

<length_guidance>

• Keep descriptions 1-2 sentences
• Under 1024 characters in practice
• Avoid marketing fluff
• Focus on non-spoiling description

</length_guidance>

</description_pattern>

Schema-Level Prompt Engineering

<schema_pattern> Use schemas not just for validation, but as prompts to the agent

<parameter_level_guidance>

<property_pattern name="enum_preference">

Use enums instead of free text when:

• Finite set of values (status: ["pending", "approved", "rejected"])
• Predefined options (unit: ["celsius", "fahrenheit"])
• Boolean-like choices (severity: ["low", "medium", "high", "critical"])

Why: Enums remove ambiguity and act as strong constraints at the schema level.

</property_pattern>

<property_pattern name="format_constraints">

Use format constraints:

"email": {
  "type": "string",
  "format": "email",
  "description": "User's email address"
}

Common formats: email, date, date-time, uri, uuid

</property_pattern>

<property_pattern name="conditional_requirements">

State mutual exclusivity or requirements in descriptions:

"agent_id": {
  "type": "string",
  "description": "Unique identifier for agent. At least one of agent_id, user_id, app_id, or run_id must be provided."
}

</property_pattern>

</parameter_level_guidance>

<output_schema>

Define outputSchema for complex responses:

{
  "name": "get_weather",
  "description": "Get weather conditions for a city",
  "inputSchema": {
    "type": "object",
    "properties": {
      "location": {
        "type": "string",
        "enum": ["New York", "Chicago", "Los Angeles"],
        "description": "Choose city"
      }
    }
  },
  "outputSchema": {
    "type": "object",
    "properties": {
      "temperature": {
        "type": "number",
        "description": "Temperature in Fahrenheit"
      },
      "conditions": { "type": "string", "description": "Weather conditions" },
      "humidity": { "type": "number", "description": "Humidity percentage" }
    }
  }
}

Why: outputSchema guides the agent about what shape to expect, improving reasoning about downstream tools.

</output_schema>

</schema_pattern>

When and How to Use Strong Language

<strong_language> Directive language (must, always, never, required) for agent guidance

<where_to_use>

Safety and guardrails:

"description": "Tool to delete a user record. Use only when the user has confirmed deletion and has appropriate permissions. Never allow deletion without explicit user consent."

Preconditions and ordering:

"description": "Tool to create a contact. Required workflow: call discover_required_fields('Contact') first to identify mandatory fields."

Format and cardinality constraints:

"title": {
  "type": "string",
  "description": "Title must be between 5 and 120 characters"
}

Error messages for agent recovery:

"Invalid date_range: date_from is after date_to. Please ensure date_from is earlier than date_to and try again."

</where_to_use>

Use strong language for:

• Safety requirements (never expose credentials)
• Required workflows (must call X first)
• Non-negotiable constraints (must be <= 100)
• Error recovery instructions

Avoid overusing strong language for:

• General behavior descriptions
• Optional features
• Documentation-level details (put these in schema)

Trade-off: Too much strong language causes token bloat and over-constraint. Use sparingly where it matters most.

</strong_language>

Guiding Agents with Errors

<error_guidance> Error messages are micro-prompts that guide agents to self-correct

Error message formula:

<Problem>. <Why>. <Fix>.

"Invalid date_from: date_from must be earlier than date_to. Please adjust date_from to a value before date_to and retry."

"Missing required parameter: repo_path is required. Please provide the path to the Git repository and retry."

"Access denied: token lacks write scope. Ask the user to grant write permissions or use a read-only tool."

"Result truncated: returned first 500 of 3,000 rows. To reduce truncation, specify a narrower date range or use filters (user_id, event_type)."

• Return structured errors with isError flag
• Use natural language, not stack traces
• Include concrete examples of correct parameters
• Suggest recovery actions explicitly

</error_guidance>

Balancing Power vs Complexity

<complexity_management> Achieve maximum capability with minimum cognitive load

<per_tool_targets>

• One clear, atomic action per tool
• 1-3 required parameters, small number of optional (total < 6-7)
• Short descriptions (1-2 sentences, < 1024 chars)
• Narrow scope: Don't create "manage" tools; prefer "create", "delete", "list", "search"

</per_tool_targets>

<per_server_targets>

• Coherent domain: Group related tools by service (git**, slack*_, jira__)
• Small surface: Each server should do one thing well
• Consolidate chains: Merge tools that are almost always called together

</per_server_targets>

Use MCP annotations for client guidance:

• readOnlyHint: tool doesn't modify state
• destructiveHint: may cause destructive changes (triggers confirmations)
• idempotentHint: repeating the call is safe

</complexity_management>

Community Patterns and Examples

<community_examples> Reference patterns from official MCP servers and community implementations

Consistent snake_case with namespace prefixes:

{
  "git_status": "Shows working tree status",
  "git_diff_unstaged": "Shows unstaged changes",
  "git_commit": "Records changes to the repository"
}

Concise descriptions following the formula:

{
  "name": "get_structured_content",
  "description": "Returns structured content along with an output schema for client data validation"
}

Strong typing with enums and descriptions:

{
  "location": {
    "type": "string",
    "enum": ["New York", "Chicago", "Los Angeles"],
    "description": "Choose city"
  }
}

One dense description for server capability (not individual tools):

{
  "description": "Integrates with Slack Lists to enable creation, retrieval, filtering, and management of list items with support for bulk operations, data export to JSON/CSV formats"
}

</community_examples>

<tool_schema> Strict template for generating valid tool definitions

<tool_definition_template>

{
  "name": "{{TOOL_NAME}}",
  "description": "{{PROMPT_ENGINEERED_DESCRIPTION}}",
  "inputSchema": {
    "type": "object",
    "properties": {
      {{PARAMETER_DEFINITIONS}}
    },
    "required": [{{REQUIRED_PARAMS}}],
    "additionalProperties": false
  },
  "outputSchema": {{OUTPUT_SCHEMA}}
}

</tool_definition_template>

<parameter_template>

"{{PARAM_NAME}}": {
  "type": "{{PARAM_TYPE}}",
  "description": "{{PARAM_DESCRIPTION}}",
  "enum": [{{ENUM_VALUES}}],
  "format": "{{FORMAT}}",
  "default": "{{DEFAULT_VALUE}}"
}

</parameter_template>

<validation_rules>

• Tool names use snake_case with namespace prefix (e.g., service_action)
• Descriptions achieve clarity when following: "Tool to . Use when . Constraints: ."
• Valid JSON Schema ensures runtime reliability for inputSchema
• Parameter descriptions prevent misuse by explaining meaning and constraints
• The required field lists all non-optional parameters
• Set additionalProperties to false for strict validation
• Enums improve reliability for finite value sets
• Format constraints (email, date, etc.) add automatic validation

</validation_rules>

<common_types>

• string - Text values
• number - Numeric values (int or float)
• boolean - true/false
• array - Lists of items
• object - Nested structures
• enum - Fixed set of values

</common_types>

<common_formats>

• email - Valid email address
• date - ISO date (YYYY-MM-DD)
• date-time - ISO datetime
• uri - Valid URI
• uuid - Valid UUID

</common_formats>

</tool_schema>

Transport Logic

<transport_selection> Define when to use stdio vs http transport

<selection_criteria>

• Local tool → stdio
• Remote service → http
• Multi-user → http
• Development → stdio
• Production → http </selection_criteria> </transport_selection>

MCP servers provide:

• Tool definitions: Structured capabilities Claude can invoke
• Resource access: Shared data and context
• Prompt templates: Reusable interaction patterns
• Transport mechanisms: Communication protocols
• Portability: Work across different environments

MCP Architecture

Server-Based: MCPs run as separate servers that Claude connects to

Three Component Types:

1. Tools: Invocable functions with parameters
2. Resources: Data sources and context providers
3. Prompts: Template-based interaction patterns

Core Structure

Server Configuration (McpServer)

<critical_constraint> Use McpServer from @modelcontextprotocol/sdk/server/mcp.js (the legacy Server is deprecated) </critical_constraint>

import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import { z } from "zod";

const server = new McpServer({
  name: "mcp-server-name",
  version: "1.0.0",
});

// Tool registration with Zod
server.tool(
  "tool-name",
  "Tool description",
  {
    param: z.string().describe("Parameter description"),
  },
  async ({ param }) => {
    // Implementation
    return { content: [{ type: "text", text: result }] };
  },
);

// Transport connection
const transport = new StdioServerTransport();
await server.connect(transport);

Validation Framework

<critical_constraint> Use scripts/test_mcp.sh for MCP server validation—this script abstracts @modelcontextprotocol/inspector complexity into a simple CLI. </critical_constraint>

Quick validation commands:

# Health check (verifies server starts and responds)
scripts/test_mcp.sh Custom_MCP/{project}/dist/server.js health

# List all tools (verify schema and descriptions)
scripts/test_mcp.sh Custom_MCP/{project}/dist/server.js tools

# List resources
scripts/test_mcp.sh Custom_MCP/{project}/dist/server.js resources

# List prompts
scripts/test_mcp.sh Custom_MCP/{project}/dist/server.js prompts

# Call a tool (happy path)
scripts/test_mcp.sh Custom_MCP/{project}/dist/server.js call myTool --arg key=value

# Call with JSON arguments
scripts/test_mcp.sh Custom_MCP/{project}/dist/server.js call myTool --json '{"key": "value"}'

# Run full test suite
scripts/test_mcp.sh Custom_MCP/{project}/dist/server.js all

CI/CD validation with exit codes:

#!/bin/bash
set -e

PROJECT="your-project-name"
SERVER_PATH="Custom_MCP/${PROJECT}/dist/server.js"

# Health check (exit 0 = server running)
scripts/test_mcp.sh "$SERVER_PATH" health || exit 1

# List tools (verify definitions)
TOOLS=$(scripts/test_mcp.sh "$SERVER_PATH" tools)
echo "$TOOLS" | jq -e '.tools | length > 0' || exit 1

# Test critical tool
scripts/test_mcp.sh "$SERVER_PATH" call myCriticalTool --arg input="test" || exit 1

echo "MCP server validation: PASS"

For deep spec compliance, combine with external validators like mcp-validator:

# STDIO compliance test
python -m mcp_testing.scripts.compliance_report \
  --server-command "node Custom_MCP/${PROJECT}/dist/server.js" \
  --protocol-version 2025-06-18

Relevance Heuristic

<freshness_gate> Validate URL freshness before trusting documentation

Freshness Gate: Before trusting any code snippets from a URL:

1. Fetch the URL and check for last-updated metadata (Last-Modified header, date in content, or commit history)
2. If content is > 6 months old, search for a more recent version before using the code
3. Prefer recent commits over branch files for SDK documentation
4. Document the freshness check result in the session

Skip freshness check when:

• Checking npm/GitHub version info (timestamp is the version)
• The URL is clearly versioned (e.g., /v1/, /2026/)
• Official SDK changelog confirms stability

<freshness_check>

# Check GitHub file last commit date
gh api repos/modelcontextprotocol/specification/commits?path=specification.md --jq '.[0].commit.author.date'

# Or fetch and parse for dates
curl -sI https://github.com/modelcontextprotocol/specification | grep -i last-modified

</freshness_check>

</freshness_gate>

Protocol: Check Principles → Freshness Gate → Fetch Instance → Extract Delta → Dispose

Before fetching MCP specification URLs:

1. Check Principles - This skill covers tool schema design, transport selection, error guidance, and prompt engineering. The patterns here are stable.

2. Freshness Gate - Verify URL is < 6 months old. If older, search for updated version or use npm package version instead.

3. Fetch Instance Only When:

   • MCP SDK version has breaking changes
   • Transport mechanism differs from documented patterns
   • New primitive types not covered
   • Authentication flow has changed

4. Extract Delta - Keep only what this skill doesn't cover:

   • SDK-specific initialization changes
   • New transport options
   • Updated security requirements
   • Protocol version differences

5. Dispose Context - Remove fetched content after extracting delta

Delta Pattern: Fetch the URL, identify current tool-calling syntax, apply directly to the local file. Store patterns, not documentation. Documentation becomes stale; patterns remain actionable.

When NOT to fetch:

• Tool description formula (covered in skill)
• Schema patterns (covered with templates)
• Transport selection criteria (covered in tables)
• Error guidance (covered with examples)
• Strong language usage (covered in patterns)

Official Documentation (fetch for current MCP syntax):

• Tool schema & transport → https://code.claude.com/docs/en/mcp.md
• Inspector CLI (testing) → https://github.com/modelcontextprotocol/inspector
• MCP Validator (compliance) → https://github.com/Janix-ai/mcp-validator
• Protocol spec → https://modelcontextprotocol.io/
• Best practices → https://modelcontextprotocol.info/docs/best-practices
• SDK docs → https://modelcontextprotocol.io/quickstart/server
• Testing guide → https://www.stainless.com/mcp/how-to-test-mcp-servers

Workflow: Freshness check → Verify npm package version → Consult skill patterns → Fetch spec only if behavior differs → Extract delta → Dispose

Dynamic Sourcing Protocol

<fetch_protocol> Before creating MCP servers, fetch current syntax from:

• https://code.claude.com/docs/en/mcp.md (tool schema and transport)

Note: For CLI testing, use scripts/test_mcp.sh instead of fetching inspector documentation. </fetch_protocol>

Navigation

Official Documentation:

• Tool schema & transport → https://code.claude.com/docs/en/mcp.md
• Inspector CLI (testing) → https://github.com/modelcontextprotocol/inspector
• MCP Validator (compliance) → https://github.com/Janix-ai/mcp-validator
• Protocol spec → https://modelcontextprotocol.io/
• Best practices → https://modelcontextprotocol.info/docs/best-practices
• SDK docs → https://modelcontextprotocol.io/quickstart/server
• Testing guide → https://www.stainless.com/mcp/how-to-test-mcp-servers

Genetic Code

This component carries essential Seed System principles for context: fork isolation:

<critical_constraint> All components work with zero CLAUDE.md, CLAUDE.local.md, or .claude/rules/ dependencies (portability invariant). Achieve 80-95% autonomy (0-5 AskUserQuestion rounds per session). Use What-When-Not-Includes format in descriptions (third person). Progressive disclosure: SKILL.md contains core philosophy; references/ contains detailed content. Use XML for control (mission_control, critical_constraint), Markdown for data. When referencing other skills: use "invoke skill-name" or "invoke skill-name and read its file". Never cite absolute paths or reference .claude/rules/ from skills. </critical_constraint>

Delta Standard: Good Component = Expert Knowledge − What Claude Already Knows

Recognition Questions

Validation Checklist

Before claiming MCP development complete:

• Prompt-engineered descriptions used
• Schema-first design followed
• Transport layer properly configured
• Tool schemas validated

<guiding_principles>

The Path to MCP Server Quality

1. Prompt-Engineered Descriptions

Tool descriptions achieve optimal agent behavior when written as micro-prompts.

• Description formula: "Tool to . Use when . Constraints: ."
• Front-load constraints: Place critical requirements and workflows first
• Conciseness: 1-2 sentences, under 1024 characters

2. Schema-First Design

Valid JSON Schema prevents runtime errors and guides agent behavior.

• Use <tool_schema> template: Follow the tool definition structure exactly
• Kebab-case names: Service_action format improves discoverability
• Property descriptions: Explain parameter meaning and constraints
• Enums over free text: Finite value sets reduce ambiguity
• Format constraints: Add automatic validation (email, date, uri, uuid)

3. Transport by Use Case

Choose stdio or http based on deployment requirements.

• stdio for local: Single client, direct integration, simpler setup
• http for remote: Multiple clients, network transport, load balancing
• Define clearly: Transport configuration affects deployment architecture

4. Error Messages as Micro-Prompts

Errors guide agents to self-correct when structured properly.

• Pattern: "<Problem>. <Why>. <Fix>."
• Concrete suggestions: Include examples of correct parameters
• Recovery actions: Explicit next steps instead of stack traces

5. Portability First

Servers work across environments when configured properly.

• Environment variables: Externalize configuration
• Project-relative paths: Use ${CLAUDE_PROJECT_DIR} instead of hardcoding
• Self-contained dependencies: Bundle required packages
• Graceful degradation: Handle missing configuration safely

6. Security by Design

Input validation and sanitization prevent common vulnerabilities.

• Validate all inputs: Against schema before processing
• Sanitize user input: Prevent injection attacks
• Parameterized queries: Use prepared statements for databases
• Rate limiting: Prevent abuse and resource exhaustion
• Mask sensitive data: Never log credentials or tokens
• HTTPS only: Encrypt external communications

7. Performance Patterns

Servers remain responsive under load when optimized appropriately.

• Cache repeated operations: Use @lru_cache or equivalent
• Paginate large results: Return data in manageable chunks
• Batch operations: Group related calls when possible
• Set timeouts: Prevent indefinite waits </guiding_principles>

<critical_constraint> System Physics:

1. Skill portability: The skill must function without CLAUDE.md, CLAUDE.local.md, or .claude/rules/ dependencies (core invariant)
2. Optional tooling: External validators (mcp-validator, mcp_testing) are recommended for deep compliance but not required—the skill provides manual review patterns as fallback
3. Use McpServer from @modelcontextprotocol/sdk/server/mcp.js (legacy Server deprecated)
4. Completion claims require verification evidence
5. Prompt-engineered descriptions required for protocol correctness </critical_constraint>

Dynamic Knowledge Loading

This skill uses Blind Navigation for references. Load specialized knowledge ONLY when specific conditions are met:

Dynamic Sourcing

Syntax Source: This skill focuses on patterns and philosophy. For raw MCP tool schema syntax:

1. Fetch: https://code.claude.com/docs/en/mcp.md
2. Extract: The specific tool schema fields you need
3. Discard: Do not retain the fetch in context

Common Mistakes to Avoid

Mistake 1: Missing additionalProperties

❌ Wrong:

"inputSchema": {
  "type": "object",
  "properties": { "param": { "type": "string" } }
}

✅ Correct:

"inputSchema": {
  "type": "object",
  "properties": { "param": { "type": "string" } },
  "additionalProperties": false
}

Mistake 2: Weak Tool Descriptions

❌ Wrong:

"description": "Tool to get data"

✅ Correct:

"description": "Tool to retrieve user authentication status. Use when checking if a user is logged in or verifying session validity. Not for authentication operations (use auth-tool instead)."

Mistake 3: Missing Required Parameters

❌ Wrong:

"inputSchema": {
  "type": "object",
  "properties": { "user_id": { "type": "string" } }
}

✅ Correct:

"inputSchema": {
  "type": "object",
  "properties": { "user_id": { "type": "string", "description": "The user ID to look up" } },
  "required": ["user_id"],
  "additionalProperties": false
}

Mistake 4: Using Deprecated Server Class

❌ Wrong:

import { Server } from "@modelcontextprotocol/sdk/server/index.js"

✅ Correct:

import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js"

Mistake 5: Poor Error Messages

❌ Wrong:

"Invalid input"

✅ Correct:

"Invalid user_id: 'abc123' is not a valid UUID format. Please provide a valid UUID like '550e8400-e29b-41d4-a716-446655440000'."

Validation Checklist

Before claiming MCP development complete:

Tool Schema:

• Valid JSON Schema for inputSchema
• All required parameters listed in required array
• additionalProperties set to false
• Parameter descriptions explain purpose and constraints

Tool Description:

• Follows formula: "Tool to X. Use when Y. Constraints: Z."
• Includes trigger conditions
• Excludes use cases clearly (Not for...)

Transport:

• stdio configured for local tools
• http configured for remote tools
• Authentication properly set up

Server:

• Uses McpServer (not deprecated Server class)
• Tools registered with valid schemas
• Server properly initialized

Testing:

• test_mcp.sh validation passes
• Tool calls work correctly
• Error messages are helpful

Best Practices Summary

✅ DO:

• Use additionalProperties: false for strict validation
• Write tool descriptions as micro-prompts
• Include all required parameters in schema
• Use enums for finite value sets
• Set format constraints (email, date, etc.)
• Use McpServer from correct import path
• Test with test_mcp.sh before claiming complete

❌ DON'T:

• Skip parameter descriptions
• Use loose schemas without additionalProperties
• Write vague tool descriptions
• Forget required array for mandatory params
• Use deprecated Server class
• Skip error message improvement
• Skip validation testing

<critical_constraint> System Physics:

1. Zero external dependencies (portability invariant)
2. Use McpServer from @modelcontextprotocol/sdk/server/mcp.js (legacy Server deprecated)
3. Completion claims require verification evidence
4. Prompt-engineered descriptions required for protocol correctness
5. additionalProperties: false required for tool schemas </critical_constraint>