Wedges
Uses Upstash Redis for persistent storage of Film Club rooms and critiques.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Wedgesrun the taste extraction"
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.
Wedges
The agent edition of Both Hands Full. → wedges.dev
Both Hands Full is a set of exercises that help humans protect their taste, voice, and judgment in the age of synthetic everything. Wedges is the inversion: point your agent at the same exercises and walk away with a portable taste profile — a style guide, worldview, glossary, voice patterns, and irreducible list — that any agent can load to serve your work without flattening it.
Hold critique in one hand. Hold curiosity in the other. Keep walking.
It has two halves:
Solo — a public remote MCP server. Point any agent at it, run the exercises, get your taste profile.
Together — Film Club, shared crit rooms where a few people drop work and read each other's through their taste profiles. Real feedback, not polite feedback.
Solo: the MCP server
Connect Claude Code, Codex, ChatGPT, Cursor — same URL.
claude mcp add --transport http wedges https://wedges.dev/api/mcp{ "mcpServers": { "wedges": { "type": "http", "url": "https://wedges.dev/api/mcp" } } }Then, in a session: "Run the Wedges taste extraction." The agent self-drives via the start_wedges prompt.
Tool | What it does | LLM? |
| The exercise catalog | no |
| The 10 Selector Pressure rounds to present to the user | no |
| Voice-drift analysis of a paragraph | yes |
| Visual taste analysis of images (base64 preferred; URLs are unreliable) | yes (vision) |
| Deterministic taste profile from the user's round choices | no |
| Structure the "things AI can't eat" list | no |
| Assemble the portable taste profile (markdown + JSON) | no |
Resources: wedges://catalog, wedges://pressure-rounds, wedges://profile. Prompt: start_wedges.
LLM tools use the server's
ANTHROPIC_API_KEY(Haiku) by default; passanthropic_api_keyto use your own.The LLM tools are rate-limited (~10/min per IP on the shared key, ~60/min BYO) plus a Vercel Firewall rule on
/api/mcp. The solo flow stores nothing — the profile is handed back and forgotten.
Related MCP server: Graph
Together: Film Club
wedges.dev/club — start a room, send the link to a few people, everyone joins with a display name + their taste-profile.md. Drop one unfinished thing; the room generates a critique from each other member's taste lens (server-side) — what they'd cut, where it goes generic, whether they'd ship it.
Identity: share-link + display name, cookies, no accounts.
Storage: rooms persist until deleted (Upstash Redis in prod; in-memory in dev). Your profile is yours, rooms are invite-only and deletable.
In production the club is gated behind the store being configured (
isStoreConfigured()), so it stays dark until a Redis is connected.
Repo map
app/
api/[transport]/route.ts # the MCP server (one file)
api/club/... # Film Club API (create/join/get/submit/delete)
page.tsx # landing (xerox-punk)
opengraph-image.tsx # branded OG card
club/ # Film Club hub + room UI
lib/
exercises/ # mirror-booth, taste-audit (ported, UI-free)
selector-pressure.ts # deterministic taste scoring + rounds
profile.ts # taste-profile.md assembly
anthropic.ts, errors.ts, rate-limit.ts
club/ # store, types, critique core, cookies
docs/VISION.md # the Film Club design brief
ROADMAP.md # what's nextEnvironment
.env.schema is the agent-readable contract. Keep values in ignored local
files or Vercel, validate with varlock load --agent --show-all, and run
secret-dependent commands through varlock run --inject vars -- <command>.
Develop
npm install
npm run dev # http://localhost:3000
npm run verify # typecheck + MCP smoke test (needs the dev server running)Exercise logic is ported from the Both Hands Full app. See docs/VISION.md and ROADMAP.md.
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