mcp-management

MCP is an open protocol enabling AI agents to connect to external tools and data sources. This skill provides scripts and utilities to discover, analyze, and execute MCP capabilities from configured servers without polluting the main context window.

Key Benefits:

• Progressive disclosure of MCP capabilities (load only what's needed)
• Intelligent tool/prompt/resource selection based on task requirements
• Multi-server management from single config file
• Context-efficient: subagents handle MCP discovery and execution
• Persistent tool catalog: automatically saves discovered tools to JSON for fast reference

Use this skill when:

1. Discovering MCP Capabilities: Need to list available tools/prompts/resources from configured servers
2. Task-Based Tool Selection: Analyzing which MCP tools are relevant for a specific task
3. Executing MCP Tools: Calling MCP tools programmatically with proper parameter handling
4. MCP Integration: Building or debugging MCP client implementations
5. Context Management: Avoiding context pollution by delegating MCP operations to subagents

1. Configuration Management

MCP servers configured in .claude/.mcp.json.

Gemini CLI Integration (recommended): Create symlink to .gemini/settings.json:

```bash

mkdir -p .gemini && ln -sf .claude/.mcp.json .gemini/settings.json

```

See [references/configuration.md](references/configuration.md) and [references/gemini-cli-integration.md](references/gemini-cli-integration.md).

GEMINI.md Response Format: Project root contains GEMINI.md that Gemini CLI auto-loads, enforcing structured JSON responses:

```json

{"server":"name","tool":"name","success":true,"result":,"error":null}

```

This ensures parseable, consistent output instead of unpredictable natural language. The file defines:

• Mandatory JSON-only response format (no markdown, no explanations)
• Maximum 500 character responses
• Error handling structure
• Available MCP servers reference

Benefits: Programmatically parseable output, consistent error reporting, DRY configuration (format defined once), context-efficient (auto-loaded by Gemini CLI).

2. Capability Discovery

```bash

npx tsx scripts/cli.ts list-tools # Saves to assets/tools.json

npx tsx scripts/cli.ts list-prompts

npx tsx scripts/cli.ts list-resources

```

Aggregates capabilities from multiple servers with server identification.

3. Intelligent Tool Analysis

LLM analyzes assets/tools.json directly - better than keyword matching algorithms.

4. Tool Execution

Primary: Gemini CLI (if available)

```bash

# IMPORTANT: Use stdin piping, NOT -p flag (deprecated, skips MCP init)

echo "Take a screenshot of https://example.com" | gemini -y -m gemini-2.5-flash

```

Secondary: Direct Scripts

```bash

npx tsx scripts/cli.ts call-tool memory create_entities '{"entities":[...]}'

```

Fallback: mcp-manager Subagent

See [references/gemini-cli-integration.md](references/gemini-cli-integration.md) for complete examples.

Pattern 1: Gemini CLI Auto-Execution (Primary)

Use Gemini CLI for automatic tool discovery and execution. Gemini CLI auto-loads GEMINI.md from project root to enforce structured JSON responses.

Quick Example:

```bash

# IMPORTANT: Use stdin piping, NOT -p flag (deprecated, skips MCP init)

# Add "Return JSON only per GEMINI.md instructions" to enforce structured output

echo "Take a screenshot of https://example.com. Return JSON only per GEMINI.md instructions." | gemini -y -m gemini-2.5-flash

```

Expected Output:

```json

{"server":"puppeteer","tool":"screenshot","success":true,"result":"screenshot.png","error":null}

```

Benefits:

• Automatic tool discovery
• Structured JSON responses (parseable by Claude)
• GEMINI.md auto-loaded for consistent formatting
• Faster than subagent orchestration
• No natural language ambiguity

See [references/gemini-cli-integration.md](references/gemini-cli-integration.md) for complete guide.

Pattern 2: Subagent-Based Execution (Fallback)

Use mcp-manager agent when Gemini CLI unavailable. Subagent discovers tools, selects relevant ones, executes tasks, reports back.

Benefit: Main context stays clean, only relevant tool definitions loaded when needed.

Pattern 3: LLM-Driven Tool Selection

LLM reads assets/tools.json, intelligently selects relevant tools using context understanding, synonyms, and intent recognition.

Pattern 4: Multi-Server Orchestration

Coordinate tools across multiple servers. Each tool knows its source server for proper routing.

scripts/mcp-client.ts

Core MCP client manager class. Handles:

• Config loading from .claude/.mcp.json
• Connecting to multiple MCP servers
• Listing tools/prompts/resources across all servers
• Executing tools with proper error handling
• Connection lifecycle management

scripts/cli.ts

Command-line interface for MCP operations. Commands:

• list-tools - Display all tools and save to assets/tools.json
• list-prompts - Display all prompts
• list-resources - Display all resources
• call-tool - Execute a tool

Note: list-tools persists complete tool catalog to assets/tools.json with full schemas for fast reference, offline browsing, and version control.

Method 1: Gemini CLI (recommended)

```bash

npm install -g gemini-cli

mkdir -p .gemini && ln -sf .claude/.mcp.json .gemini/settings.json

# IMPORTANT: Use stdin piping, NOT -p flag (deprecated, skips MCP init)

# GEMINI.md auto-loads to enforce JSON responses

echo "Take a screenshot of https://example.com. Return JSON only per GEMINI.md instructions." | gemini -y -m gemini-2.5-flash

```

Returns structured JSON: {"server":"puppeteer","tool":"screenshot","success":true,"result":"screenshot.png","error":null}

Method 2: Scripts

```bash

cd .claude/skills/mcp-management/scripts && npm install

npx tsx cli.ts list-tools # Saves to assets/tools.json

npx tsx cli.ts call-tool memory create_entities '{"entities":[...]}'

```

Method 3: mcp-manager Subagent

See [references/gemini-cli-integration.md](references/gemini-cli-integration.md) for complete guide.

See [references/mcp-protocol.md](references/mcp-protocol.md) for:

• JSON-RPC protocol details
• Message types and formats
• Error codes and handling
• Transport mechanisms (stdio, HTTP+SSE)
• Best practices

Execution Priority

1. Gemini CLI (Primary): Fast, automatic, intelligent tool selection

- Check: command -v gemini

- Execute: echo "" | gemini -y -m gemini-2.5-flash

- IMPORTANT: Use stdin piping, NOT -p flag (deprecated, skips MCP init)

- Best for: All tasks when available

1. Direct CLI Scripts (Secondary): Manual tool specification

- Use when: Need specific tool/server control

- Execute: npx tsx scripts/cli.ts call-tool

1. mcp-manager Subagent (Fallback): Context-efficient delegation

- Use when: Gemini unavailable or failed

- Keeps main context clean

Integration with Agents

The mcp-manager agent uses this skill to:

• Check Gemini CLI availability first
• Execute via gemini command if available
• Fallback to direct script execution
• Discover MCP capabilities without loading into main context
• Report results back to main agent

This keeps main agent context clean and enables efficient MCP integration.