
Slashloop MCP
io.github.man0lPublished by GitHub account man0lv1.0.0Updated Nov 7, 2026
Track TikTok niches, score outliers, extract hooks, draft remakes via MCP.
Overview
Hosted MCP server for short-form video research: track TikTok, Reels and Shorts sources, find outliers, analyze videos and draft remakes.
- What you can do
- Track and manage sources: list, create, update, delete, refresh and suggest TikTok/Reels/Shorts accounts and hashtags
- Discover niches from keywords, hashtags or handles and browse the feed, library search and outlier summaries
- Fetch and analyze videos with Gemini, read transcripts, and extract hooks or generate hook variations
- Build creative assets: boards, ideas, briefs, scripts, exports, weekly retros and benchmarks
- Plan, estimate and generate experiments, with credit approval on spending tools
- Check usage, settings, refresh logs, spend status and job status
- When to use it
- Useful for creators, social media marketers and agencies who want an assistant to monitor short-form video niches, surface outlier videos and turn winners into hooks, ideas and creative briefs without leaving the chat.
- Requirements
- Remote streamable HTTP endpoint only; no local package. Requires OAuth sign-in through the browser on first tool call, and a workspace ID or exact workspace name for the agent skills. A paid plan or credit pack is needed for metered analysis and generation.
Installation
In SourceWeft
- Open Slashloop MCP in the dashboard and add it to a workspace.
- Connect the required credentials. They are stored privately and never shown on public pages.
- Enable the server for the chats that should use its tools.
Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.
Use with an agent
Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.
Read https://sourceweft.com/mcp/io.github.man0l%2Fslashloop/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.Other MCP clients
Add this to your client's mcpServers config. The client completes OAuth sign-in on first connect.
{
"mcpServers": {
"slashloop": {
"type": "http",
"url": "https://mcp.slashloop.dev/mcp"
}
}
}README
slashloop
Hosted MCP server for viral short-form video research — track TikTok / Reels / Shorts sources, find outlier videos, run Gemini video analysis, and turn winners into hooks, ideas, and creative briefs.
Remote HTTP MCP only (no local stdio server): hosted on Cloudflare
Workers (D1 + R2 + KV + Cron Triggers), authenticated via Supabase OAuth2
until the native-IdP swap (see docs/cf-full-backend-plan.md). Vercel is
retired. API keys (Gemini, the scraper proxy) live server-side,
so installers never handle them.
Live endpoint: https://mcp.slashloop.dev/mcp
Agent skills
skills/ contains installable agent skills for the remote MCP:
slashloop-sources, slashloop-refresh, slashloop-gallery,
slashloop-experiments, and slashloop. After publication to npm, install
them with:
Use --claude, --project, or --target <skills-dir> for another skills
root. Copy a skill directory into your agent's skills root (for Codex,
$CODEX_HOME/skills) and read its SKILL.md before running the workflow.
Every skill requires an explicit workspace ID or exact workspace name; none
silently defaults to the primary workspace.
Install
Claude Code (plugin — skills + remote MCP)
Then install slashloop from the Marketplace tab. The plugin registers the
remote MCP server and the /slashloop:track, /slashloop:discover skills.
On first tool call, complete the Supabase OAuth login in the browser.
Claude Desktop / Cowork / claude.ai (connector)
Settings → Connectors → Add custom connector →
https://mcp.slashloop.dev/mcp → log in → consent.
All 63 tools (plus whoami) are then available; ask in plain language
("track tiktok creator @x", "find outlier videos about Y").
The
/slashloop:track//discoverslash shortcuts are Claude Code plugin skills. In Desktop/Cowork you don't need them — the connector exposes every tool directly.
Self-host (Workers primary; Supabase OAuth)
Cutover in progress: Worker + D1 is primary (
docs/cf-full-backend-plan.md, runbookdocs/cloudflare-migration.md, checksdocs/cf-cutover-checklist.md). Below is the Supabase OAuth setup and local dev server.Vercel is retired (project deleted,
api/mcp.ts/api/pages.tsentrypoints removed in SLA-1243). The Supabase steps below are kept for the OAuth setup;remote:devis the local server.
1. Supabase dashboard
- Auth → URL Configuration → Site URL = your public connector URL.
- Auth → OAuth Server → Enable. Authorization path =
/oauth/consent. Turn on Dynamic client registration. - JWT signing → asymmetric (RS256).
- Email/password enabled + a user.
2. Env
3. Run / deploy
Schema changes
Production schema is managed by Supabase migrations, not Prisma. SQL files
in supabase/migrations/ are applied by the Supabase GitHub integration on
merge to the default branch. prisma/schema.prisma stays the source of truth
for the client (types + query builder) — the two must be kept in sync by
hand.
To add a schema change:
Media storage (optional)
TikTok cover images and MP4s are persisted to Supabase Storage so the feed
doesn't render broken images once the source CDN's signed URLs expire, and so
re-analysis can skip a metered proxy download. Leave SUPABASE_SECRET_KEY unset and
the entire path no-ops — everything else works as before.
Setup is one step: set SUPABASE_SECRET_KEY and CRON_SECRET in Vercel. Two
buckets are needed — thumbs (public, 5MiB, images only) and media
(private, 100MiB, video/mp4 only).
supabase/migrations/*_media_storage_buckets.sql creates them if they're
absent, so a fresh project or a local supabase start comes up ready.
That migration is create-only (
ON CONFLICT DO NOTHING) — it never reconciles a bucket that already exists, so dashboard settings are safe from it. It also downgrades a permissions failure onstorage.bucketsto aNOTICErather than blocking a deploy.So on a project whose buckets were created by hand — which includes this one — the size limits and mime allowlists above do not exist and will not be added by deploying. A bucket made in the dashboard has no limit unless someone typed one in. Nothing breaks without them; they are a ceiling, not a requirement. To actually get them, set them in the dashboard.
The setting that does matter is
mediamust be private — public would mean an open mirror of scraped video. Worth confirming once.
Retention defaults to 3 days and is a per-workspace setting changed via the
update_settings tool, capped per plan. Supabase has no object lifecycle
rules, so expiry runs as a daily Vercel Cron (/api/cron/media-retention).
Analysis runs off the request path
analyze_video with the gemini-native backend queues rather than
analysing inline, and returns a jobId. Poll get_video — analysisJob
reports progress, analysis carries the result once it lands. gemini-text
still returns its analysis directly; it is one text call and finishes in
seconds.
The reason is a hard ceiling, not a preference: a native analysis has to
download the MP4, upload it to Gemini, wait for processing and then generate,
which does not fit api/mcp.ts's 60s maxDuration — and the Vercel plan
cannot raise it. The MCP client applies its own timeout too, so a synchronous
call could not be rescued by a bigger server budget anyway.
Enqueueing fires a non-blocking call to /api/jobs/analyze, which runs the job
on a fresh invocation with its own 60s. That dispatch is best-effort and nothing
depends on it.
What makes the queue reliable is pg_cron, running inside Postgres every
minute (supabase/migrations/*_pgcron_drain_analyze_jobs.sql). Vercel Cron is
capped at one run per day on this plan and rejects sub-daily expressions at
deploy time; pg_cron is not subject to that at all. Each minute it POSTs
/api/jobs/analyze, but only when a row is queued or running — so an idle
queue costs zero function invocations.
The job does nothing else: recovering abandoned claims is the worker's job, in
TypeScript, so MAX_ATTEMPTS and STUCK_AFTER_MINUTES have exactly one
definition (src/lib/jobs.ts) instead of a second copy in SQL that drifts.
running is in the gate because only the worker can decide a claim is
abandoned.
Two secrets must exist in Supabase Vault or the job is a deliberate no-op:
They are read by name at run time and are not in the migration. If you rotate
CRON_SECRET in Vercel, update the Vault copy too, or the drain silently 401s.
There is deliberately no Vercel Cron fallback for this. A daily duplicate of a
per-minute job is a third code path earning its keep only if pg_cron breaks, and
it would mask that breakage rather than surface it. If the drain stops, jobs
visibly pile up in queued — which is the signal you want.
Full design, including the later phases: docs/media-storage-plan.md.
⚠️ Do not run
bun run db:pushagainst production. It bypasses the migration history entirely and will drift from what Supabase has applied. It exists only for throwaway local databases. Likewise, never runprisma migrate— it maintains its own_prisma_migrationstable that Supabase knows nothing about.
Routes
The three /api/billing/* routes carry CORS for SITE_URL (the landing site's
origin); /mcp and /api/stripe/webhook don't need it — neither is called
from a browser.
Required variables
See docs/stripe-implementation-plan.md for the full Stripe dashboard setup
(products, prices, webhook registration). Schema is applied by the Supabase
migration in supabase/migrations/ on merge; the remaining manual step is
populating the env vars above from a real Stripe account.
Tool inventory (63 tools, plus whoami on the remote host)
Experiments are the agent-facing twin of the site's /experiments page and
wrap the same service as api/experiments.ts (src/experiments/service.ts):
create_experiment (free draft, one experiment per source slideshow, or mode:"brief" for a single draft with no source video) →
estimate_experiment stage plan → user approves → plan_experiment
(background analysis + pattern report + variant briefs) → status review →
optional update_experiment_variant → estimate_experiment stage generate
→ user approves → generate_experiment (background rendering). Every
spending tool takes approvedCredits and refuses if the fresh estimate is
higher; omitted idempotency keys are derived from the request, so an identical
retry replays instead of duplicating.
discover is the keyword-driven front door: paste a niche (keywords, #hashtags,
@handles) → AI expands into seed keywords → each seed gets a small real probe
scrape → hashtags + creators are mined from sampled captions with view
evidence → pick from verified suggestions to track. The site's Discover screen
(/discover) drives the same pipeline over REST (POST /api/sources/discover
/api/sources/discover/mine).
Spend cap behavior
- Cap:
PROXY_TRAFFIC_CAP_GBper calendar month - Enforced at: every
refresh_source(and single-video download) before proxy traffic is spent - On breach: the call is refused, a
cap_breachevent is persisted toUsageLog, and the optionalAPIFY_CAP_NOTIFICATION_HOOKfires - To check: call
get_scraper_spend_status(get_apify_spend_statusis the legacy name of the same tool) - Historical Apify spend rows stay in
UsageLogand are still reported - Resets on the first of each calendar month.
Architecture notes
- Stateless per request: each
POST /mcpbuilds a fresh transport +McpServer(WebStandardStreamableHTTPServerTransport), scoped by the JWTsubviarunWithUser(AsyncLocalStorage) →requireWorkspace(). - Multi-tenant: every workspace lookup keys off the Supabase user id; JWT scoping isolates users.
- Failure tracking is DB-backed (
Workspace.failureCountsJson) so the "2 consecutive failures → fallback" rule survives across stateless requests. Entries decay after an hour, and a success clears only the streak of the backend that succeeded — an account-level failure (OpenRouter out of balance) also parks that backend in a penalty box for the rest of the window. - No in-process scheduler:
run_auto_analyzeis an on-demand tool; for nightly batch usebun src/scripts/auto_analyze_cron.ts. - Batch discount:
run_auto_analyzepassesbatch: true→BATCH_COST_ESTIMATES(50% Gemini Batch API discount). Singleanalyze_videouses interactive rates. - Schema is the contract: both analyzers emit the same
VideoAnalysisDataZod schema; unfilled fields arenullwith ananalysisBasistag.
Scripts
VPS worker (optional — removes the 60s ceiling)
Vercel Hobby caps functions at 60s, which a full-length OpenRouter video analysis (Qwen needs ~45s+ on a 10s clip and >50s on real clips) cannot fit. The same queue can be drained by a long-running worker with no wall-clock limit:
src/worker/process-job.ts— the per-job processing switch (fetch / analyze / rescore / refresh), shared by the Vercel worker (api/jobs/analyze.ts) and the VPS loop, so the retry/refund policy lives in exactly one place.src/worker/index.ts—bun run worker: reclaims stuck jobs, claims in priority (fetch → analyze → rescore → refresh) withFOR UPDATE SKIP LOCKED(safe to run alongside the Vercel worker / pg_cron — jobs are never double-claimed), processes with no budget, idlesWORKER_IDLE_MS(default 3s).- Docker:
docker build -t slashloop-worker -f worker/Dockerfile .and run withworker/.env.example(same env as Vercel plusOPENROUTER_VIDEO_TIMEOUT_MS/OPENROUTER_VIDEO_MAX_DURATION_SEC). - If the VPS dies, pg_cron keeps poking Vercel's worker → text-level analysis still works.
Source: README.md at commit 907e4c4
Tools
0Version history
1- v1.0.0LatestOct 31, 2026
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