DPS-Superskills-MCP
Exposes 31 high-assurance agentic coding skills as MCP tools and resources, enabling AI agents to invoke structured workflows across DISCIPLINE, TECHNIQUE, KNOWLEDGE LAYER, and REFERENCE registers.
README
DPS SuperSkills MCP Server
DPS SuperSkills v5.2.1 deployed as an MCP server — exposes 31 high-assurance agentic coding skills as tools for any MCP-compatible client (Claude Desktop, Cursor, VS Code, Windsurf, Antigravity, or any IDE/chatbot supporting MCP).
Package:
dps-superskills-mcpDefault transport:stdioSkills content:docs/DPS-superskills-v5.2.1/(31 skills, 31 nano references) Runtime entrypoint:dist/index.jsBase layer: SUPER-MCP Framework (TypeScript / ESM)
DPS SuperSkills — MCP Tools & Resources
This server exposes both MCP Tools (for on-demand invocation) and MCP Resources (for context auto-injection) to give any AI agent structured access to the full DPS SuperSkills v5.2.1 framework.
MCP Resources
DISCIPLINE skills (the Iron Laws) are automatically exposed as read-only MCP Resources at skill://<name> (e.g., skill://using-super-skills).
Compatible MCP clients (like Claude Desktop and Cursor) can automatically inject these high-priority resources into the LLM's system context at the start of a session, enforcing the rules without requiring the model to explicitly call a tool first.
Note: Resources are fully protected by the same rate-limiting, quota, and Output Firewall pipelines as Tools. Enabled by default; can be disabled via MCP_ENABLE_SKILL_RESOURCES=false.
MCP Tools
| MCP Tool | Purpose |
|---|---|
skill_list |
List all 31 skills with descriptions and register (DISCIPLINE / TECHNIQUE / KNOWLEDGE LAYER / REFERENCE). Optionally filter by register. |
skill_read |
Return the full SKILL.md content for a specific skill. Optionally include nano (compressed) version. |
skill_run |
Invoke a skill with caller context — returns structured workflow: ANNOUNCE, GOAL, CONSTRAINTS, CHECKLIST, OUTPUT TEMPLATE, active GOTCHAS, and NANO REFERENCE. |
31 Skills Available
DISCIPLINE (Iron Laws — non-negotiable):
complexity-gate · tdd-verified · verification-before-completion · context-reanchor · epistemic-health-check · privacy-secrets-gate
TECHNIQUE (Goal + constraints — adapt approach):
brainstorming · dps-init · audit-design · dps-promote · writing-plans · task-risk-score
systematic-debugging · pattern-globalize · specialist-review · release-readiness
subagent-driven-development · executing-plans · dispatching-parallel-agents
receiving-code-review · using-git-worktrees · session-handoff
KNOWLEDGE LAYER (Cross-cycle compounding):
domain-alignment · knowledge-compound · audit-distill · adr-commit
REFERENCE (Lookup only):
kb-query · skill-init · writing-super-skills · framework-doctor · using-super-skills
Client Configuration
To automatically generate the correct configuration with absolute paths for your environment, run:
./install.sh
Manual Configuration (Claude Desktop / Cursor / Antigravity)
If configuring manually, replace <absolute-path-to> with your actual full path:
{
"mcpServers": {
"dps-superskills": {
"command": "node",
"args": ["<absolute-path-to>/DPS-Superskills/dist/index.js"],
"env": {
"TRANSPORT_DRIVER": "stdio",
"STORAGE_DRIVER": "fs",
"MCP_SAFE_MODE": "true",
"MCP_PLUGIN_ALLOWLIST": "system.tool.js,skills.tool.js",
"MCP_ENABLE_SKILL_RESOURCES": "true"
}
}
}
}
VS Code / Windsurf (stdio)
{
"mcp": {
"servers": {
"dps-superskills": {
"command": "node",
"args": ["<absolute-path-to>/DPS-Superskills/dist/index.js"],
"env": {
"TRANSPORT_DRIVER": "stdio",
"STORAGE_DRIVER": "fs",
"MCP_SAFE_MODE": "true",
"MCP_PLUGIN_ALLOWLIST": "system.tool.js,skills.tool.js",
"MCP_ENABLE_SKILL_RESOURCES": "true"
}
}
}
}
}
Quick Start
pnpm install --frozen-lockfile
pnpm build
# Server is now ready for MCP client connections via stdio
Project Structure
.
├── docs/DPS-superskills-v5.2.1/ ← 31 skills content (SKILL.md + nano.md)
│ ├── <skill-name>/SKILL.md
│ ├── <skill-name>/<skill-name>.nano.md
│ ├── shared/ ← gotcha-schema, claim-grammar, etc.
│ ├── bootstrap-templates/
│ ├── quickstarts/
│ ├── tools/
│ └── README.md
└── src/
├── index.ts
├── skills/ ← DPS SuperSkills MCP bridge layer
│ ├── skill_loader.ts ← SKILL.md / nano.md parser
│ ├── skill_registry.ts ← 31-skill static registry
│ └── skill_executor.ts ← structured workflow formatter
├── plugins/
│ ├── skills.tool.ts ← skill_list, skill_read, skill_run tools
│ └── system.tool.ts ← ping, pattern_debt, test_long_task
└── ... ← Layer 0 (SUPER-MCP runtime)
By default the server reads skills from <project_root>/docs/DPS-superskills-v5.2.1. Override with:
MCP_SKILLS_PATH=/custom/path/to/skills
Layer 0: SUPER-MCP Runtime
This MCP server is built on top of the hardened SUPER-MCP Boilerplate (Layer 0).
While the primary focus of this project is the DPS SuperSkills implementation, the underlying architecture provides:
- Dual transports: Native support for both
stdioandhttp. - Durable Storage: Extensible storage (fs, Redis) for task and state persistence.
- Output Firewall: Redaction of sensitive data before returning to the LLM.
- Security Primitives: Capability-based safety policies (
MCP_SAFE_MODE), plugin allowlisting, and native tasks support.
(Note: Advanced configuration options for Redis, KMS encryption, OAuth, and HTTP deployments inherited from SUPER-MCP are supported but omitted from this README for brevity, as the standard local stdio usage is recommended for IDEs and Chatbots).
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.