An MCP server that exposes the Agent Skill creation guide (9 phases) as MCP resources. AI agents retrieve only the phases they need on demand and follow the process to build SKILL.md files.
Quick Start
Claude Code:
claude mcp add skill-forge-mcp -- npx skill-forge-mcp
Gemini CLI:
gemini mcp add skill-forge-mcp -- npx skill-forge-mcp
VS Code (GitHub Copilot) — .vscode/mcp.json:
{
"servers": {
"skill-forge-mcp": {
"command": "npx",
"args": ["skill-forge-mcp"]
}
}
}
Cursor:
{
"skill-forge-mcp": {
"command": "npx",
"args": ["skill-forge-mcp"]
}
}
Claude Desktop
{
"mcpServers": {
"skill-forge-mcp": {
"command": "npx",
"args": ["skill-forge-mcp"]
}
}
}
Usage
Ask your agent:
"I want to create a skill for React component design. Follow the SkillForge MCP process."
The agent will automatically:
- Fetch the process structure from
process://manifest - Read Phase 1 (
process://phase/1) for scoping, run baseline measurements - Record progress with
mark_progressas it advances through each phase - Generate the final SKILL.md following Phase 6 guidelines
Use search_process for keyword lookups across phases.
The 9 Phases
| Phase | Name | Purpose |
|---|---|---|
| 0 | Skill Specification | SKILL.md structure and frontmatter |
| 1 | Scoping & Baseline | Measure failure patterns; define research scope |
| 2 | Domain Research | Establish quality criteria and theoretical foundations |
| 3 | Gap Analysis | Verify whether research alone enables the agent to act |
| 4 | Deep Implementation Research | Fill gaps with code examples, anti-patterns, validation |
| 5 | Structuring & Completeness | Confirm coverage across all categories |
| 6 | Distillation into SKILL.md | Condense into ≤500 lines; maximize token efficiency |
| 7 | Deploy & Validate | Place, verify spec compliance, security review |
| 8 | Evaluate & Iterate | Compare against baseline, improve iteratively |
Features
- Staged access — retrieve content at phase or section granularity
- Cross-phase search — keyword search across all 9 phases
- Progress tracking — record and query per-phase completion status
- Prompt templates —
create_skillandresume_skillprompts for guided workflows - Structured output —
outputSchema+structuredContenton all tools for programmatic consumption - State persistence — optionally retain progress across sessions
- Low overhead — ~1,500 token fixed cost to the context window
API
Resources
| URI | Description |
|---|---|
process://manifest | Full index (JSON) |
process://phase/0 – process://phase/8 | Phase 0–8 content |
Resource Templates
| Template | Description |
|---|---|
process://phase/{phaseId}/section/{sectionName} | Retrieve a single section |
process://phases/{+phaseIds} | Batch retrieval (e.g. 1,2,3) |
Tools
| Tool | Description | Input |
|---|---|---|
search_process | Keyword search across all phases | { "query": "frontmatter", "maxResults": 5 } |
mark_progress | Record phase progress | { "phaseId": 1, "status": "in-progress" } |
get_status | Progress summary for all phases | {} |
status: "not-started" · "in-progress" · "completed"
Prompts
| Prompt | Description |
|---|---|
create_skill | Full guided workflow (Phase 0→8). Accepts a topic argument. |
resume_skill | Resume from current progress. Checks get_status and continues. |
Configuration
Set SKILL_FORGE_PERSIST=true to persist progress to ~/.skill-forge-mcp/state.json:
{
"mcpServers": {
"skill-forge-mcp": {
"command": "npx",
"args": ["skill-forge-mcp"],
"env": { "SKILL_FORGE_PERSIST": "true" }
}
}
}
Development
git clone https://github.com/popyson1648/skill-forge-mcp.git
cd skill-forge-mcp
npm install
npm run build
npm test # 52 tests
Project structure
src/
├── index.ts # Entry point
├── content.ts # Content loading & section extraction
├── search.ts # Cross-phase search
├── state.ts # State management & persistence
├── status.ts # Status table formatter
├── content/ # English content (served)
└── content-ja/ # Japanese translations (developer reference only)
tests/
├── content.test.ts
├── search.test.ts
├── state.test.ts
├── resources.test.ts
└── tools.test.ts
Requirements: Node.js >= 18
Contributing
Contributions are welcome! Feel free to open an Issue or submit a Pull Request.
License
MIT