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product-specs-mcp

by QCObjects
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TypeScript
Remote

product-specs-mcp

MCP server over the QCObjects product-specs docs — lets AI agents learn framework usage for building apps (specs 01–16 + examples). Runs on Cloudflare Workers via Streamable HTTP (stateless).

Tools

Tool

What it does

list_specs

Lists all 16 spec docs with site paths

search_docs

Full-text search over the published site (title-weighted ranking)

get_page

Fetches a docs page as plain text (~12k chars)

get_spec

Fetches one numbered spec (01–16) as plain text

docs_status

Returns the docs base URL (provenance)

Endpoints: GET / (health) · POST /mcp (MCP Streamable HTTP).

Related MCP server: Documentation Fetcher & RAG Search

How it reads the docs

No vendored content — the Worker fetches the live Pages site at runtime: search/search_index.json for search (cached per isolate, INDEX_TTL_SECONDS), page HTML stripped to text for reads. Override the source with the DOCS_BASE_URL var (e.g. a preview deploy).

Local dev

npm ci
npm run check   # tsc + vitest
npm run dev     # wrangler dev (http://127.0.0.1:8787)

Deploy (Cloudflare Workers)

CI deploys main automatically. Required GitHub Actions secrets (repo Settings → Secrets and variables → Actions):

Secret

Value

CLOUDFLARE_API_TOKEN

API token with Workers Scripts: Edit on the account (create at dash.cloudflare.com → My Profile → API Tokens)

CLOUDFLARE_ACCOUNT_ID

Account ID (Workers & Pages → Overview, right sidebar)

Manual deploy: wrangler login && npm run deploy.

Git workflow

Topic branches from development (feature/*), PR into development, release development → main. Never rebase. SSH only.

This server cannot be deployed

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Maintenance

ActivityMaintained
ResponsivenessNo issues

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