Which integrations are available for this server?

Provides tools for interacting with GitHub repositories, including reading repo metadata, file contents, creating branches, updating files, creating pull requests, and commenting on PRs. Provides a tool to read recent GitHub Actions workflow runs for a repository.

How do I use Design System MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Design System MCP Server fetch design request context for request 42" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

Design System MCP Server

by nhatnguyenquang1838-coder

Overview Schema Related Servers Score Discussions

TypeScript

Remote

Design System MCP Server

Self-hosted MCP server for connecting ChatGPT / Workspace Agents to a Design System backend and guarded GitHub workflows.

What this provides

This server supports two integration modes:

Mode	Endpoint	Use case
MCP native connector	`/mcp`	ChatGPT Apps & Connectors / MCP connector
REST wrapper	`/api/...`	Custom GPT Actions using OpenAPI YAML

Design System MCP tools:

Tool	Type	Purpose
`ds_ping`	read	Health check from ChatGPT
`ds_get_request`	read	Fetch design request context by `request_id`
`ds_submit_agent_result`	write	Submit a completed agent review result back to the system

GitHub MCP tools:

Tool	Type	Purpose
`github_get_repo`	read	Read allowlisted repo metadata
`github_read_file`	read	Read UTF-8 file content
`github_create_branch`	write	Create guarded branch from base branch
`github_upsert_file`	write	Create/update file on guarded non-main branch
`github_create_pr`	write	Create pull request
`github_get_workflow_runs`	read	Read recent GitHub Actions workflow runs
`github_comment_pr`	write	Comment on pull request

REST endpoints for GPT Actions:

Method	Path	Purpose
`GET`	`/health`	Health check
`GET`	`/api/design-requests/{request_id}`	Fetch design request by ID
`POST`	`/api/agent-results`	Submit final agent review result
`GET`	`/api/github/repos/{owner}/{repo}`	Read repo metadata
`GET`	`/api/github/repos/{owner}/{repo}/files?path=...&ref=...`	Read file
`POST`	`/api/github/repos/{owner}/{repo}/branches`	Create branch
`POST`	`/api/github/repos/{owner}/{repo}/files`	Create/update file
`POST`	`/api/github/repos/{owner}/{repo}/pull-requests`	Create PR
`POST`	`/api/github/repos/{owner}/{repo}/pull-requests/{pr_number}/comments`	Comment PR
`GET`	`/api/github/repos/{owner}/{repo}/workflow-runs`	Read workflow runs

This repo is intentionally small. It is the public-MCP and REST-action foundation for a larger workflow:

Design System Backend / Custom GPT / ChatGPT
  -> reads design request or GitHub repo context
  -> creates guarded branch
  -> updates files on branch
  -> opens PR
  -> submits design review result or PR comment

Related MCP server: GPT MCP Service

Requirements

Node.js 20+
npm
Public HTTPS URL for ChatGPT connector usage
GitHub fine-grained PAT or GitHub App token for GitHub gateway usage

Local setup

npm install
cp .env.example .env
npm run dev

Health check:

curl http://localhost:8787/health

Root check:

curl http://localhost:8787/

REST test:

curl http://localhost:8787/api/design-requests/DSR-001

Submit test result:

curl -X POST http://localhost:8787/api/agent-results \
  -H "Content-Type: application/json" \
  -d '{
    "request_id": "DSR-001",
    "decision": "revise",
    "summary": "Mobile layout needs cleanup before implementation.",
    "risk_level": "medium",
    "frontend_tasks": [
      {
        "title": "Fix InvoiceCard mobile overflow",
        "acceptance_criteria": [
          "No horizontal scroll at 360px viewport",
          "Invoice content remains readable in mobile card"
        ]
      }
    ],
    "validation": ["Run typecheck", "Test 360px viewport"]
  }'

GitHub gateway setup

Set these env vars before using GitHub tools:

GITHUB_TOKEN=github_pat_xxx
GITHUB_ALLOWED_REPOS=nhatnguyenquang1838-coder/ds_mcp_server,nhatnguyenquang1838-coder/rental_home
GITHUB_DEFAULT_BASE_BRANCH=main
GITHUB_ALLOWED_BRANCH_PREFIXES=feature/,fix/,chore/,docs/,ai/

Recommended fine-grained PAT permissions for MVP:

Repository access: only selected repositories
Contents: Read and write
Pull requests: Read and write
Actions: Read-only
Metadata: Read-only

Guardrails:

- Repository must be in GITHUB_ALLOWED_REPOS.
- Direct writes to main/master/production/prod are blocked.
- Write branches must start with feature/, fix/, chore/, docs/, or ai/ by default.
- File paths cannot start with /, contain .., or use Windows backslash.
- No merge/delete/force-push/secret-management endpoints are exposed.

GitHub REST read file test:

curl "http://localhost:8787/api/github/repos/nhatnguyenquang1838-coder/ds_mcp_server/files?path=README.md"

Create branch test:

curl -X POST http://localhost:8787/api/github/repos/nhatnguyenquang1838-coder/ds_mcp_server/branches \
  -H "Content-Type: application/json" \
  -d '{"branch":"docs/test-github-gateway","from_branch":"main"}'

Create/update file test:

curl -X POST http://localhost:8787/api/github/repos/nhatnguyenquang1838-coder/ds_mcp_server/files \
  -H "Content-Type: application/json" \
  -d '{
    "path":"docs/test-github-gateway.md",
    "content":"# Test GitHub Gateway\n",
    "branch":"docs/test-github-gateway",
    "message":"docs: test github gateway"
  }'

Create PR test:

curl -X POST http://localhost:8787/api/github/repos/nhatnguyenquang1838-coder/ds_mcp_server/pull-requests \
  -H "Content-Type: application/json" \
  -d '{
    "title":"docs: test github gateway",
    "head":"docs/test-github-gateway",
    "base":"main",
    "body":"## Summary\n- Test GitHub gateway\n\n## Validation\n- Manual API call",
    "draft":true
  }'

Test with MCP Inspector

npx @modelcontextprotocol/inspector@latest \
  --server-url http://localhost:8787/mcp \
  --transport http

Expose publicly for ChatGPT development

Example with ngrok:

ngrok http 8787

Use the public MCP endpoint in ChatGPT:

https://<your-ngrok-domain>/mcp

ChatGPT MCP connector setup

In ChatGPT:

Settings
-> Apps & Connectors
-> Advanced settings
-> Developer mode
-> Create connector

Use:

Name: Design System MCP
URL: https://<your-public-domain>/mcp

Custom GPT Actions setup

Use openapi.yaml in this repo when configuring Custom GPT Actions.

Important: Custom GPT Actions should call REST endpoints, not /mcp directly.

Use server URL:

https://<your-public-domain>

Optional bearer auth

For local prototype, MCP_BEARER_TOKEN may be empty.

Before exposing to the internet, set:

MCP_BEARER_TOKEN=replace-with-a-long-random-token

Then MCP clients must send:

Authorization: Bearer replace-with-a-long-random-token

Note: the REST wrapper currently does not require this bearer token. Add real auth before using it with sensitive data.

Backend result forwarding

ds_submit_agent_result and POST /api/agent-results store result in memory and can also forward to your backend:

DS_BACKEND_URL=https://your-backend.example.com
INTERNAL_AGENT_RESULT_TOKEN=change-me

Expected backend endpoint:

POST /internal/agent-results
Header: X-Internal-Token: <INTERNAL_AGENT_RESULT_TOKEN>
Body: Agent result JSON

Scripts

npm run dev        # local development
npm run typecheck  # TypeScript validation
npm run build      # compile to dist
npm start          # run compiled server

Production notes

Minimum controls before production:

Set MCP_BEARER_TOKEN or implement OAuth for MCP.
Add auth for REST endpoints before using real data.
Keep write tools narrow and schema-validated.
Do not expose destructive tools in MVP.
Do not put secrets in tool output.
Audit all write calls.
Validate agent result JSON again in the backend.
Prefer GitHub App auth over PAT for multi-user/team production.

Docker

docker build -t ds-mcp-server .
docker run --rm -p 8787:8787 --env-file .env ds-mcp-server

This server cannot be installed

license - permissive license

quality - not tested

maintenance

How are these scores calculated?

Maintenance

–Maintainers

–Response time

–Release cycle

–Releases (12mo)

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