mcp-converter
Converts MCP servers to Claude Skills with 90%+ context savings using progressive disclosure pattern. Supports automatic detection and on-demand conversion.
Packaged view
This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.
Install command
npx @skill-hub/cli install oimiragieo-agent-studio-mcp-converter
Repository
Skill path: .claude/skills/mcp-converter
Converts MCP servers to Claude Skills with 90%+ context savings using progressive disclosure pattern. Supports automatic detection and on-demand conversion.
Open repositoryBest for
Primary workflow: Ship Full Stack.
Technical facets: Full Stack, Integration.
Target audience: everyone.
License: Unknown.
Original source
Catalog source: SkillHub Club.
Repository owner: oimiragieo.
This is still a mirrored public skill entry. Review the repository before installing into production workflows.
What it helps with
- Install mcp-converter into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
- Review https://github.com/oimiragieo/agent-studio before adding mcp-converter to shared team environments
- Use mcp-converter for development workflows
Works across
Favorites: 0.
Sub-skills: 0.
Aggregator: No.
Original source / Raw SKILL.md
---
name: mcp-converter
description: Converts MCP servers to Claude Skills with 90%+ context savings using progressive disclosure pattern. Supports automatic detection and on-demand conversion.
allowed-tools: read, write, bash, grep, glob
version: 1.0
best_practices:
- Convert MCP servers with 10+ tools
- Keep critical tools (1-5) as MCP
- Use automatic detection for new MCP servers
- Validate generated Skills before installation
error_handling: graceful
streaming: supported
---
# MCP-to-Skill Converter Skill
## Identity
MCP-to-Skill Converter - Transforms MCP servers into Claude Skills using progressive disclosure to achieve 90%+ context savings while maintaining full functionality.
## Capabilities
- **MCP Server Introspection**: Analyze MCP servers to discover tools and capabilities
- **Skill Generation**: Generate complete Skill structure (SKILL.md, executor.py, config)
- **Progressive Disclosure**: Create Skills with metadata-only loading (~100 tokens)
- **Automatic Detection**: Monitor and detect new MCP servers for conversion
- **Validation**: Validate generated Skills before installation
- **Installation**: Install converted Skills to user's Skills directory
## The Problem
MCP servers load all tool definitions into context at startup:
- 20+ tools = 30-50k tokens consumed immediately
- Context fills before Claude does any work
- Hard to scale beyond ~100 tools
- Most tools unused in each conversation
## The Solution
Convert MCP servers to Skills with progressive disclosure:
- **Startup**: ~100 tokens (metadata only)
- **When used**: ~5k tokens (full instructions)
- **Executing**: 0 tokens (runs externally)
- **Savings**: 90%+ context reduction
## How It Works
1. **Introspection**: Connect to MCP server and discover all tools
2. **Analysis**: Calculate token usage and conversion eligibility
3. **Generation**: Create Skill structure with progressive disclosure
4. **Validation**: Verify Skill structure and functionality
5. **Installation**: Install to `~/.claude/skills/`
## Usage Patterns
### On-Demand Conversion
**When to Use**:
- You have an MCP server with 10+ tools
- Context space is critical
- Most tools aren't used in every conversation
- You want maximum context efficiency
**How to Invoke**:
```
"Convert the github MCP server to a Skill"
"Convert all MCP servers with more than 10 tools"
"Convert the custom-server MCP to a Skill"
```
**What It Does**:
- Reads MCP server configuration
- Introspects server to discover tools
- Generates Skill structure
- Validates and installs Skill
### Automatic Detection
**When Enabled**:
- Monitor `.claude/.mcp.json` for changes
- Detect new MCP servers
- Analyze tool count and token usage
- Auto-convert based on rules
**Configuration**:
```yaml
auto_convert:
enabled: true
threshold:
tool_count: 10
estimated_tokens: 5000
exceptions:
- github # Keep as MCP
- memory # Keep as MCP
```
## Skill Structure
Generated Skills follow this structure:
```
skill-name/
├── SKILL.md # Metadata and instructions (~100 tokens)
├── executor.py # Dynamic MCP tool execution
└── config.json # MCP server configuration
```
### SKILL.md (Progressive Disclosure)
**Metadata Only** (~100 tokens):
- Skill name and description
- Tool categories
- When to use guidance
- Quick reference
**Full Instructions** (~5k tokens, loaded when used):
- Complete tool documentation
- Usage examples
- Error handling
- Best practices
### executor.py
Handles MCP tool calls dynamically:
- Connects to MCP server
- Executes tool calls
- Returns results
- Handles errors
## Integration
### With Tool Search
Skills work alongside Tool Search:
- **Tool Search**: Semantic discovery of tools
- **Skills**: On-demand tool loading with minimal context
- **Combined**: Optimal context usage for large tool libraries
### With Skill Builder
Uses Skill Builder plugin for:
- Validation of generated Skills
- Template-based generation
- Testing and verification
- Installation management
### With Marketplace
Integrates with superpowers-marketplace:
- Install marketplace plugins
- Auto-detect MCP servers in plugins
- Convert plugin MCP servers to Skills
- Manage plugin ecosystem
## Best Practices
### When to Convert
**Convert to Skill When**:
- MCP server has 10+ tools
- Most tools unused in each conversation
- Context space is critical
- Tools are independent
**Keep as MCP When**:
- 1-5 tools (minimal context impact)
- Complex OAuth flows required
- Persistent connections needed
- Cross-platform compatibility critical
### Critical Tools to Keep as MCP
Keep these as MCP (always loaded):
- Core file operations: `read_file`, `write_file`, `search_code`
- Essential integrations: `create_pull_request`, `get_issue`
- Frequently used: `take_screenshot`, `navigate_page`
### Hybrid Approach
**Best Strategy**: Use both MCP and Skills
- **MCP**: Core tools (1-5 tools, always loaded)
- **Skills**: Extended toolset (10+ tools, on-demand)
- **Tool Search**: Discovery and semantic matching
## Examples
### Example 1: Convert GitHub MCP
```bash
# On-demand conversion
"Convert the github MCP server to a Skill"
# Result: Creates ~/.claude/skills/github/
# - SKILL.md (100 tokens metadata)
# - executor.py (dynamic tool calls)
# - config.json (MCP configuration)
```
### Example 2: Batch Conversion
```bash
# Convert multiple MCP servers
"Convert all MCP servers with more than 10 tools to Skills"
# Analyzes all MCP servers
# Converts eligible servers
# Installs all generated Skills
```
### Example 3: Automatic Detection
```yaml
# .claude/skills/mcp-converter/conversion_rules.yaml
auto_convert:
enabled: true
threshold:
tool_count: 10
exceptions:
- github
- memory
```
## Error Handling
**Common Issues**:
- MCP server not responding: Check configuration and environment variables
- Tool introspection fails: Verify MCP server is accessible
- Skill generation errors: Check templates and validation
- Installation fails: Verify Skills directory permissions
**Recovery**:
- Retry with verbose logging
- Validate MCP configuration
- Check Skill Builder integration
- Review conversion rules
## Context Savings
**Before (MCP)**:
```
20 tools = 30k tokens always loaded
Context available: 170k / 200k = 85%
```
**After (Skills)**:
```
20 skills = 2k tokens metadata
When 1 skill active: 7k tokens
Context available: 193k / 200k = 96.5%
```
## Dependencies
- `mcp` Python package (for MCP server introspection)
- Skill Builder plugin (for validation)
- Existing MCP configuration (`.claude/.mcp.json`)
## Batch Conversion
**Convert Multiple MCP Servers at Once**:
```bash
"Convert all MCP servers from the catalog"
"Convert all MCP servers with more than 15 tools"
"Convert MCP servers: postgres, aws, docker"
```
**Catalog-Based Conversion**:
The skill uses `mcp-catalog.yaml` to identify popular MCP servers for conversion:
- **Automatic Detection**: Servers in catalog are automatically considered
- **Priority-Based**: High priority servers converted first
- **Batch Processing**: Convert multiple servers concurrently (max 3 at a time)
- **Validation**: All converted skills validated before installation
**Catalog Features**:
- 25+ popular MCP servers pre-configured
- Tool count and token estimates
- Conversion priority levels
- Category tagging
- Keep-as-MCP exceptions (github, filesystem, memory)
**Batch Conversion Process**:
1. Load `mcp-catalog.yaml` to get server list
2. Filter by conversion criteria (tool count, tokens, priority)
3. Convert servers in parallel (max 3 concurrent)
4. Validate all generated skills
5. Install to `~/.claude/skills/`
6. Generate conversion report
## Catalog Support
**Using the MCP Catalog**:
The catalog (`mcp-catalog.yaml`) provides:
- **Server Metadata**: Name, description, tool count, token estimates
- **Conversion Rules**: Auto-convert thresholds and exceptions
- **Batch Settings**: Concurrent conversion limits and timeouts
- **Statistics**: Total servers, conversion recommendations
**Catalog Integration**:
- Catalog automatically loaded when skill is invoked
- Servers filtered by conversion criteria
- Exceptions (keep-as-MCP) respected
- Priority-based conversion order
**Example Catalog Entry**:
```yaml
- name: postgres
description: PostgreSQL database operations
tool_count: 20
estimated_tokens: 35000
conversion_priority: high
keep_as_mcp: false
categories:
- database
- data
```
## Related Skills
- **tool-search**: Semantic tool discovery
- **marketplace-manager**: Plugin installation and management
- **memory-manager**: Context persistence