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521,454 tools. Updated 2026-09-06 11:42

"How to deploy a web application" matching MCP tools:

  • Deploy a GitHub repository as a live web app on Dockhold. Call this when the user wants to put an app online, get a shareable HTTPS URL, or host a demo. Returns the new app id. Two paths: a PUBLIC repo needs only repo_url; a PRIVATE repo needs repo_url plus github_installation_id (call list_github_repos first, each repo comes with the installation_id to pass here). Deploying a private repo turns on auto-deploy: future pushes to that repo redeploy the app automatically. The app builds and comes online automatically; poll get_app_status to watch it. Set memory_mb to size the app's compute, one of the values get_resource_usage reports under compute.steps_mb: 256 MB fits a static site or a small API, 512 MB fits a typical Node or Python web app, and anything that holds data in memory needs more. Omit it and the app gets the minimum slice (256 MB) so it doesn't take your whole compute pool; resize_app changes the size later with no rebuild, applied as a rolling update that replaces the app's instances. The response reports memory_mb (what this app got) and compute_available_mb (what's left in your pool), so size the next app off that. This tool needs a GitHub repo URL: if the code only exists locally (no repo), it cannot be used here, and the user should run `npx dockhold login` then `npx dockhold deploy` in the project folder instead. Requires a token with the deploy scope.
    ConnectorNo auth
  • Answer what the user's project is — name, stack, how to run/test/build, auth, database, deploy, folder layout — from their files on disk, not from training data. ALWAYS call this before you invent npm/pip/cargo commands or read package.json yourself. ALWAYS call when the user says: what is this app, what's the stack, how do I run it, how do I test, is this a monorepo, where is auth, what database, how do we deploy. If they named Zephex or MCP, call this first on their project. One topic per call. Start with topic=identity on a new folder, then follow next_calls (usually run or framework). Other topics: backend, frontend, database, auth, deploy, structure, integrations, security. This is the user's machine, any project: Node, Python, Go, Rust, Java, PHP, a monorepo, an unsaved folder. Local/stdio: omit path to use the editor cwd, or pass path as their project folder. No disk on this transport: inline_files with package.json or pyproject.toml/go.mod/Cargo.toml plus 2–4 source files. Returns topic, summary, data (identity, commands, key_paths), hint, next_calls. Copy dev/test/build from data — do not guess bun vs npm vs uv. Not for finding a function name (find_code) or reading a file body (read_code). Those come after you know what the project is. Example: get_project_context({ topic: "identity" }) then get_project_context({ topic: "run" }). Also call topic=auth before touching login, topic=database before schema work, topic=structure when you need the folder map. force:true if the project just changed. Brief is enough for orientation; do not skip this tool to save a round-trip — one identity call replaces reading several manifests.
    ConnectorNo auth
  • Show your account's compute, database-RAM, and storage pools: how much you've bought, how much is used, and how much is free, plus every app's current size. Call this before any resize tool (the allowed sizes come from its steps fields), and to explain to the user why an app ran out of memory or a deploy was refused for capacity.
    ConnectorNo auth
  • DEPLOY THE CURRENT MAIN BRANCH TO A-TEAM CORE. ⚠️ HEAVIEST OPERATION (60-180s): validates solution+skills → deploys all connectors+skills to Core (regenerates MCP servers) → health-checks → optionally runs a warm test → auto-pushes to GitHub. 🌳 DEV/PROD WORKFLOW: 1. Edit files → ateam_github_patch (writes to `dev` branch by default) 2. (Optional) Preview what's about to ship → ateam_github_diff 3. Ship dev → main → ateam_github_promote (merges + auto-tags `prod-YYYY-MM-DD-NNN`) 4. Deploy main to Core → ateam_build_and_run This tool ALWAYS deploys the `main` branch — there is no `ref` parameter. To deploy in-progress dev work, first promote it. AUTO-DETECTS GitHub repo: if you omit mcp_store and a repo exists, connector code is pulled from main automatically. First deploy requires mcp_store. After that, edit via ateam_github_patch + promote, then build_and_run. For small changes prefer ateam_patch (faster, incremental). Requires authentication.
    ConnectorNo auth
  • Get the actual Python code behind a community leaderboard strategy. Use after `browse_community`: pass an entry's `id` here to read its real `feature_engineering()` + `strategy_config()` source so the user can inspect or tweak it. To deploy it unchanged, pass the same id to `one_shot` as `community_id`. Read-only, no signup needed. Args: community_id: The `id` of a community entry (from `browse_community`). Returns: dict with: id, title, username, description, symbol, timeframe, metrics {total_ret, win_rate, profit_factor, n_trades, mdd, sharpe_strat}, and `code` (the full Python source). SHOW the code to the user, and offer to deploy it via one_shot(community_id=...) or tweak it first.
    ConnectorNo auth
  • Project reference / help desk about Fractera. Use this to answer ANY user question about what Fractera is, how it works, its architecture, components, modes, data ownership, pricing, use cases, partner program, etc. — especially while a deploy is running and the user wants to learn more. TOKEN-ECONOMY: call with NO arguments first to get the lightweight list of section ids+titles, then call again with a single `section` id to fetch just that section. NEVER try to fetch everything at once; pull only the section(s) relevant to the user question. Set `lang:"ru"` for Russian-speaking users.
    ConnectorNo auth

Matching MCP Servers

Matching MCP Connectors

  • Change one or a few files of an already-published site, leaving every other file untouched (a merge — unlike deploy, which replaces the whole site). Ideal for small edits: fix a typo in index.html, swap a stylesheet, add one page. Best practice: call get_site_files first, edit the returned content, then call this with the files you changed and the `expected_version` from that read — if the site changed in the meantime you get a clear conflict telling you to re-read. Requires site_id + edit_token. Cannot delete files (use deploy to drop a file) and cannot remove index.html.
    ConnectorNo auth
  • Create a new application (workspace) owned by the caller. Requires a personal API key (usr_...) — application-scoped keys cannot create applications. Seeds default flows unless skipDefaultFlows is true. Creates persistent state and is NOT idempotent: calling it twice creates two applications. Returns the new application id, which you then pass as applicationId to the other tools.
    ConnectorNo auth
  • Get your exact script tag and ad-unit markup, plus placement guidance (authenticate with your application token at_... or API token sk_...; a Bearer web session from the in-page agent on rocketsloth.ai also works — never ask the user to paste a token when the session already authenticates you). Available immediately after apply. Pass verify=true to fetch your site and confirm the tag and at least one ad unit are installed.
    ConnectorNo auth
  • Submit a completed Experience Application for human review. Rejects with a missingFields list if any required field is still empty, or a 409 if the Application Fee hasn't been paid/waived yet (call purchaseProduct with productId 9 and applicationId first — Experience uses product 9, NOT product 8). There is no partial/optimistic submission. On success the application moves to human review. Requires NOMADSTAYS_MCP_AGENT_TOKEN.
    ConnectorNo auth
  • Publish the workspace to its bots — the API equivalent of the dashboard's Deploy button. This is the step that makes edits live. apply_actions writes to the DRAFT graph. Until this runs the connected bots keep serving the previously published version, so a change that looks applied has no effect for real users. Deploy after a batch of edits (and after run_flow_autotest passes), not after every single action. Publishes the ACTIVE version to every active bot of the application; pass botIds to publish to a subset. Rolling back to an older version is a dashboard action and is deliberately not available here. Delivery is asynchronous: a bot listed as "queued" was handed to the deploy queue, not confirmed restarted. Returns { deployed, versionId, bots[], queuedCount, failedCount, error } — check `error` and each bot's `status`, because a version can be marked published while no runtime received it. Safe to repeat: deploying twice republishes the same version rather than duplicating anything. It does change what real users see, so confirm with the user before publishing edits they have not reviewed. Requires the manage_automation permission.
    ConnectorNo auth
  • Get the two ways to buy from GYOTAK, with the contact details for each: retail (order here through place_order, or browse the web shop) and B2B wholesale for restaurants and businesses (LINE @284ezjvm, tier pricing, application required). Call this when the user asks how to buy, how to open a wholesale account, or how to reach GYOTAK. Takes no arguments and returns static text — for product availability or prices use get_catalog, and for other questions use ask_gyotak.
    ConnectorNo auth
  • Built-in product help — ask a natural-language "how do I…" question about Fastio and get a grounded, product-aware answer (or a short clarifying question) back in one call. EXPLAIN-ONLY / ADVISORY: it returns GUIDANCE TEXT and performs NO platform action (it will not create shares, move files, or change anything) — read the guidance, then act with the other tools. Answers are grounded in Fastio's own how-to knowledge AND phrased in terms of these MCP tools — they name the concrete `<tool> action="…"` calls to make — so prefer this over guessing endpoints or burning exploratory calls. For Q&A over YOUR uploaded files (RAG) use the `ai` tool instead — `how-to` answers questions about Fastio ITSELF. FREE and requires only an authenticated user (no org, no plan gate, no billing). Call action='describe' for the full action/param reference.
    ConnectorNo auth
  • Project reference / help desk about Fractera. Use this to answer ANY user question about what Fractera is, how it works, its architecture, components, modes, data ownership, pricing, use cases, partner program, etc. — especially while a deploy is running and the user wants to learn more. TOKEN-ECONOMY: call with NO arguments first to get the lightweight list of section ids+titles, then call again with a single `section` id to fetch just that section. NEVER try to fetch everything at once; pull only the section(s) relevant to the user question. Set `lang:"ru"` for Russian-speaking users.
    ConnectorNo auth
  • Turns YOUR repo classification (you scan the repo and pass what you found) into a complete, approvable deploy plan WITHOUT creating anything. ⚡ REDU NEEDS THREE FILES IF THEY EXIST - redu.md, the compose file, the Dockerfile - and there are two ways to give them. ⭐ BEST, for an upload-mode deploy: run prepare_upload FIRST and pass its `source_token`; redu reads all three straight out of the upload you already made, the upload stays deployable, and you emit nothing. Pasting the same files costs you 20-29 KB of output for bytes the server already has. Otherwise (git mode) paste `redu_md` (cat redu.md), `compose_yaml`, `dockerfile`. Either way you do NOT read or interpret them; redu parses them SERVER-SIDE and returns (a) a short digest, (b) `pin_dname` so a redeploy keeps the SAME public URL, and (c) `preflight` - preemptive fixes for known failure patterns found in YOUR repo, each learned from a real failed build. Giving redu these files is the single highest-value thing you can do for a first deploy. picks the VM + managed-Postgres sizes, prices them at the real pricing_rules rates, and checks they FIT your quota — so a plan that can't provision is caught HERE, before any spend. You pass what you detected in the repo (runtime, port, needs_postgres/redis/clickhouse/vector_db); it returns resources + £/hr + £/mo + a feasibility verdict + a checkpoint summary to confirm with the user. Defaults: app VM m1.medium, managed Postgres m1.small, managed ClickHouse m1.medium; pass single_vm to collapse the app + Postgres onto one VM. SET needs_clickhouse:true FOR ANY ANALYTICS-SHAPED APP (Plausible, PostHog, Langfuse, Matomo, SigNoz, or anything with a clickhouse image / CLICKHOUSE_* env / a ClickHouse client dep): those products keep config in Postgres and EVERY EVENT in ClickHouse, so the events tier is a second VM with a second line on the bill: measured 2026-08-07, omitting it quoted GBP 53.29/mo for a GBP 65.99/mo deployment. It is sized, quota-checked and priced here; unlike Postgres and Redis it is not auto-wired by deploy_app, so the plan tells you to run plan_managed_datastore engine:'clickhouse' -> create_clickhouse and pass CLICKHOUSE_* env yourself. Vector-DB needs are flagged, not provisioned. Any containerizable app works (node, python, go, ...) — it deploys as a container, so the language doesn't gate it. Set serves_http:false for a non-web repo (a library, CLI, or language runtime with no HTTP server) and it returns a clean not-a-web-service verdict instead of a costed VM plan. Set heavy_build:true for resource-heavy builds (compiled-from-source native code, a monorepo/turborepo build, a large Node heap) and it raises the app VM to a build-capable floor so the on-VM build doesn't get OOM-killed. Set memory_heavy:true for a RAM-forward app whose persistent state lives in a MANAGED DB / external store (Next.js like cal.com/cal.diy, Rails, Django, JVM/Java apps) — it sizes onto a memory-optimized SMALL-DISK flavor (m1.mem16/m1.mem32: full RAM, a lean 40 GB disk instead of 160 GB) that costs less and snapshots/clusters far faster; do NOT set it if the app keeps lots of data on local disk. Also returns a brand-named markdown report (Mermaid diagram + cost) to save as redu-deploy-plan.md and show the user. Every deploy leaves TWO MANDATORY files at the repo root with DIFFERENT purposes: redu-deploy-plan.md = THIS run's plan/estimate, and redu.md = the DURABLE deploy memory the NEXT deploy reads. If a redu.md exists, READ it FIRST and reuse its known-good plan + recorded fixes; if NONE exists, one MUST be created at the end of the deploy (get_deployment returns redu_md_bootstrap_markdown for exactly that case; when a redu.md DOES exist, pass it as redu_md and write the merged redu_md_markdown). They are SEPARATE files — even if your own memory/notes from a prior deploy call redu-deploy-plan.md 'the record', the durable record is redu.md, so do not skip creating it.
    ConnectorNo auth
  • Rotate the client secret for a confidential OAuth application in a connected Clerk application. **Sensitive** — the response includes a new client_secret. Update authorized OAuth clients immediately and do not log the secret. Call clerk.get_connected_accounts first. Pass clerk_instance_id to target a specific connection, or omit it to use the default account. Returns the updated OAuth application summary with the new client_secret. Cost = 10 tokens.
    ConnectorNo auth
  • List the GitHub repositories you have connected to Dockhold, across every installation. Call this before deploy_app when the target repo is private, or when the user asks which repos they can deploy. Each repo comes with its installation_id: pass that (with the repo's clone URL) to deploy_app to deploy a PRIVATE repository. Public repos don't need it.
    ConnectorNo auth
  • Who is connected to Layero and how many projects they have. Call this first when you are unsure the token is configured: a clear error here is cheaper than one halfway through a deploy.
    ConnectorNo auth
  • Start here when building an application. Returns an overview of what the AdCritter platform offers and a catalog of feature guides you can query with the adcritter_guidance tool to learn how to build each part of the app. Call adcritter_guidance(key) for any feature area to get detailed building instructions with API endpoints and response shapes.
    ConnectorNo auth
  • INSPECTION: Retrieve Terraform outputs from a completed deployment Returns structured output values (VPC IDs, endpoints, cluster names, etc.) after a successful deploy. Sensitive outputs are redacted (shown as '(sensitive)'). By default returns outputs for the latest successful deploy. Optionally specify job_id to get outputs for a specific deployment. REQUIRES: session_id from convoopen response (format: sess_v2_...). OPTIONAL: job_id (specific deployment), lifecycle (filter by step e.g. 'cloud-provision').
    ConnectorNo auth