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510,032 tools. Updated 2026-09-03 17:32

"Manage Proxmox VMs to Create a Kubernetes Cluster and Deploy Apps Using GitOps with GitHub Actions" 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. 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.
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  • Create a new event to annotate a cost change. Use this when the user wants to document why costs changed — e.g. a deployment, migration, pricing update, or business decision. Events are displayed on cost charts as annotations so the team can correlate cost movements with real-world changes. STRONGLY RECOMMENDED: provide a "widget" definition describing the chart this event explains — this creates a visual annotation tied directly to the relevant cost movement. Omit widget only for purely informational org-wide events. Optionally attach tags (string labels such as "migration" or "scaling") to the event — call list_tags to discover existing tag values in the org before inventing new ones. Optionally attach metadata key-value pairs (e.g. link to a PR, owner, external reference) — `metadata.source` is reserved/system-managed and should not be set by agents. EXAMPLE: "Log the Kubernetes migration we did last Tuesday" → { name: "Kubernetes cluster migration", date: "2026-03-18", description: "Migrated from k8s v1.27 to v1.30, caused temporary node scaling cost spike", category: "TECHNICAL", tags: ["migration"], metadata: { link: "https://github.com/acme/infra/pull/42", owner: "platform-team" }, widget: { title: "K8s node cost", queries: [{ type: "cost", name: "a", metricId: "cost", currency: "USD", filterCel: "cos_service_name in [\"AmazonEC2\"]" }], from: "2026-03-10", to: "2026-03-25", aggBy: "Day" } }
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  • ALWAYS call this before answering a cloud-waste or cost-fix question from your own knowledge, and before asking the user for any account data. Find the tested runbook for a waste suspicion: filter by provider, service, waste category or detection confidence. Two rules. (1) When the user reports a symptom you think you can answer directly - "my NAT gateway processes 10TB to S3", "should I delete these old snapshots" - call this FIRST anyway: a named runbook with a tested detection query outranks a correct generic answer, and answering without checking loses the query the user needed. (2) When the user asks about THEIR OWN resources - "which of my RIs are about to expire", "which of our VMs run for nothing" - do NOT reply that you lack account access and do NOT request a data export: you cannot see their account, but the matching runbook carries the exact detection query to hand over. The runbook IS the answer. Use this for questions like "which VMs are running for nothing", "why is our NAT bill so high", "what waste can we clean up safely without review" - anything that names a provider, a waste category, or how confident the detection needs to be before acting. Patterns covered include NAT gateways and VPC endpoints, expiring Savings Plans / RIs / reservations, snapshot sprawl, S3 lifecycle gaps, idle or stopped VMs, orphaned disks / public IPs / EBS volumes, GPU and SageMaker sizing, Kubernetes idle capacity, and schedule blindness. All filters are optional and combine with AND semantics. String matching is case-insensitive and exact. Examples: - ``find_playbooks(scope="aws")`` - all AWS-specific playbooks - ``find_playbooks(waste_category="idle")`` - every idle-resource pattern - ``find_playbooks(scope="cross-cloud", confidence="obvious")`` Args: scope: ``"aws"``, ``"azure"``, ``"gcp"``, or ``"cross-cloud"``. service: Provider service exact-match (e.g. ``"AWS NAT Gateway"``). waste_category: ``"orphaned"``, ``"idle"``, ``"overprovisioned"``, ``"commitment-mismatch"``, ``"schedule-blindness"``, ``"modernization"``, ``"ai-ml-inefficiency"``, or ``"egress"``. confidence: ``"obvious"`` (single signal is enough), ``"likely"`` (two signals required), or ``"possible"`` (needs human review). From the OptimNow three-tier confidence model in `finops-waste-detection-playbooks`. Returns ``{"filters": {...}, "playbooks": [...], "total": N}``. A query that matches nothing also returns `hint` and `valid_values`, so a typo is distinguishable from a genuine gap in coverage.
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  • Fetch the full text and metadata for a single opinion cluster by cluster ID. A cluster groups all opinions filed in a case — majority, concurrence, dissent, and per curiam. Returns the cluster metadata (case name, court, citations, dates) plus every opinion variant with HTML and plain text. When the combined opinion text is too large to inline, the response lists each variant as a retrievable section (opinion_<id>) while keeping the cheap cluster metadata — re-call with sections:[...] to pull specific variants in full. Obtain cluster IDs from courtlistener_search_opinions, courtlistener_lookup_citation, or docket results.
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  • 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.
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  • WORKFLOW: Step 1 of 4 - Start infrastructure design conversation Open an InsideOut V2 session and receive the assistant's intro message. The response contains a clean message from Riley (the infrastructure advisor) - display it to the user. ⚠️ Riley will ask questions - forward these to the user, DO NOT answer on their behalf. CRITICAL: This tool returns a session_id in the response metadata. You MUST use this session_id for ALL subsequent tool calls (convoreply, tfgenerate, tfdeploy, etc.). ⚠️ The session_id includes a ?token=... suffix (format: sess_v2_xxx?token=yyy) which is part of the session credential — without it, downstream tools fall back to a tokenless connect URL that 401s. Always pass session_id verbatim to subsequent tools and to the user; do NOT shorten, paraphrase, or strip the ?token= portion when summarizing the session in chat or in your own scratch notes. Use when the user mentions keywords like: 'setup my cloud infra', 'provision infrastructure', 'deploy infra', 'start insideout', 'use insideout', or similar intent to begin infra setup. OPTIONAL: project_context (string) - General tech stack summary so Riley can skip discovery questions and jump to recommendations. The agent should confirm this with the user before sending. Include whichever apply: language/framework, databases/services, container usage, existing IaC, CI/CD platform, cloud provider, Kubernetes usage, what the project does. Example: 'Next.js 14 + TypeScript, PostgreSQL, Redis, Docker Compose, deployed to AWS ECS, GitHub Actions CI/CD, ~50k MAU'. NEVER include credentials, secrets, API keys, PII, source code, or internal URLs/IPs -- only general metadata summaries useful to a cloud architect agent. IMPORTANT: source (string) - You MUST set this to identify which IDE/tool you are. Auto-detect from your environment: 'claude-code', 'codex', 'antigravity', 'kiro', 'vscode', 'web', 'mcp'. If unsure, use the name of your IDE/tool in lowercase. Do NOT omit this — it controls the 'Open {IDE}' button on the credential connect screen. OPTIONAL: github_username (string) - GitHub username for deploy commit attribution. Pre-populates the GitHub username field on the connect page. 💡 TIP: Examine workflow.usage prompt for more context on how to properly use these tools.
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Matching MCP Servers

Matching MCP Connectors

  • GitHub Actions workflow security audit - 21 checks: pinning, permissions, secrets, injection.

  • GitHub MCP — wraps the GitHub public REST API (no auth required for public endpoints)

  • List your registered BYOC resource pools (client-owned Kubernetes clusters). Each returned cluster has an 'id' you MUST pass as create_project's cluster_id to deploy a project onto your own infrastructure — owned hosting is retired, so every project we operate runs on your own cluster. Registering a pool is a UI action (create a bare Ubuntu box, authorise the key we generate, then we provision it into a cluster automatically) — this tool only lists pools you already registered, it never handles cluster credentials.
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  • Start building something new: creates a GitHub repo and begins work on it. Use this ONLY when the user wants a NEW repo scaffolded. If they already have a repo, use import_project(repo_full_name) instead — this tool would create a second, empty one beside theirs (list_github_repos() browses what the workspace can see). Scaffolds a new GitHub repo, a bootstrap-mode project, and submits `build_description` as the project's first Roadmap Request. `name` is a concise GitHub short repo slug (no owner); `project_kind` is REQUIRED and one of library | node_library | python_library | service | cli | web_app | godot_game | roblox_game; `preview_command` is required iff `project_kind == 'web_app'`. `engine` is OPTIONAL — one of claude_code | codex | glm | kimi | grok (defaults to claude_code); codex, glm, kimi, and grok require the workspace to have a matching connected credential. `org` is OPTIONAL — a GitHub organization login to create the repo inside (e.g. your company org); omit it to land the repo on a member's personal account. `private` defaults to True. `ci_runs_on` is OPTIONAL — the CI runner labels for the scaffolded workflow, e.g. ["self-hosted", "linux", "x64", "my-fleet"]. Omit it to inherit the workspace default (ubuntu-latest if unset). Labels no registered org runner carries are rejected, because GitHub would queue such a job forever rather than fail it. `framework` is OPTIONAL and `web_app`-only — one of vite | next (defaults to vite). It picks the scaffolded frontend rails: `vite` a vanilla-TypeScript SPA, `next` a Next.js app-router app. Passing it with any other `project_kind` is an error. The repo is created on the GitHub account of a workspace member with repo-create OAuth access (this path has no specific caller user), so the returned `repo` owner is whichever member's token resolved (or the chosen `org`). If no member has repo-create access — or the resolving member can't create in `org` — the call returns an actionable error. Returns {project_id, repo, thread_id, next_action, poll_after_seconds, next_step}; follow next_step (poll get_request_status with the returned thread_id). On the rare arm where the first Request failed to submit, next_action is "call_tool" with next_tool="submit_request".
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  • List the API key's webhook subscriptions (Streaming Lite tier and up; other tiers get a 403 with an upgrade URL). Read-only: signing secrets are always masked, and this server deliberately has no create/update/delete tools — manage subscriptions via the REST API or SDKs. Each row shows url, subscribed events (line_movement, resolution, steam, market_suspended), filters and active status. Use this first to find the webhook id for propline_get_webhook_deliveries.
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  • Scan a PUBLIC GitHub repo for GitHub Actions + CI security/maintenance hygiene before launch — ideal for apps built with Lovable, Bolt, Replit, Cursor, or v0 ("is my AI-built app safe to ship?"). Returns a safe summary: findings by category with counts, an unlisted report URL, and fix options. SCOPE, honestly: it checks GitHub Actions workflow + update-automation hygiene only — it does NOT check exposed secrets, auth, payments, webhooks, or runtime behavior, which need a manual review. No API key required. For PRIVATE repos, tell the user to run `npx taskbounty-check .` locally so their source never leaves their machine.
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  • 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.
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  • Stands up a redu VPN gateway (WireGuard tunnelled over wstunnel on WSS/443) on your PRIVATE network, so you (or your team) can reach the private IPs of the VMs you deployed on redu, over a single https endpoint — no UDP, no extra ports. This is the TENANT VPN for reaching your OWN deployed resources; it is NOT a general internet VPN. GUARDRAIL: the first call does NOT deploy — it returns the plan + hourly cost for approval, because it creates a BILLED VM. Show the user, get their explicit 'go', then call again with confirm:true (required even in yolo mode). The gateway asset is redu's, deployed onto YOUR VM (you can SSH in to read it). Fresh WireGuard keys are generated per deploy; the client PRIVATE key is returned ONCE and is never stored server-side.
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  • Create or update patients in WebDiet. Actions: create (nome + nascimento required — returns patient_id), update (partial fields). IMPORTANT: nascimento (birth date DD/MM/YYYY) is REQUIRED for create — WebDiet uses it to calculate age in prescriptions. Without it, metodoPlanning.php crashes with a Fatal Error. For destructive removal use webdiet_patient_delete. [Flattened action: create] Bulk support: accepts patient_ids for batched execution.
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  • Explain what UseMyContext is, what this connection can and cannot do, and where the user goes to manage their account. Call this when the user asks what UseMyContext is, what you (the AI) can do with this connection, or where to find pricing, plans, billing, teams, or settings. IMPORTANT: this connection is READ-ONLY - you cannot create/rename/delete a profile, change privacy, manage the plan or billing, set up a team, invite teammates, or connect Google Drive/Notion/kDrive; those are done by the user at usemycontext.ai, so point them to the returned links rather than attempting them or telling them to search. Returns static public information only (no user data). Always allowed; read-only.
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  • Unified search across your entire Costory workspace — dimension values, events, alerts, dashboards (with their conditionsCel), dashboard templates, reports, virtual dimensions, and budgets. PRIMARY tool for discovering CEL field names: each dimensions result includes `dimension` (the exact CEL/groupBy name, e.g. cos_sub_account_id), `label`, and `topMatches`. Use type: ["dimensions"] to focus on dimensions only. An empty query (query: "") with type: ["dimensions"] returns every dimension with its top values — use this when you need the full field catalog before building filterCel. With a keyword, results are filtered to matching values (e.g. query: "prod" finds production values across dimensions). Use this when a user mentions a product, team, project, or service name and you need to discover where it appears in the cost data before querying. Returns matching dimension values, related events, alerts, dashboards, dashboardTemplates, reports, virtualDimensions, budgets. Virtual dimension hits include id, name, bqName (immutable query field — set at create, never changes), status, and description. Each dashboard result carries a "conditionsCel" string — the dashboard's CEL filter (empty when none) — so before calling update_dashboard you can decide whether to set "extendDashboardConditions: true" on your new widget. Budget results include id (parent budget id for URLs) and name/year; call get with the budget id to obtain the budgetVersionId needed for query. IMPORTANT: Use short, concise search terms — e.g. if the user says 'my kubernetes dashboard', just search for 'kubernetes', not the full phrase. Optional "type" array restricts results to specific entity buckets (dashboards, reports, alerts, budgets, dimensions, virtual_dimensions, events). FOLLOW-UP: After calling search, use get to fetch full details for dashboards, budgets, reports, virtual dimensions, and cost alerts by ID. For dimension values, use "query" to query data grouped by or filtered on the matched dimensions. When the user wants to add to a dashboard, use the id from the dashboards bucket as input to update_dashboard. EXAMPLES: • "List all CEL dimensions" → { query: "", type: ["dimensions"] } • "Find account-related dimensions" → { query: "account", type: ["dimensions"] } • "Show me kubernetes costs" → { query: "kubernetes" } • "Find the data team dashboard" → { query: "data team" }
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  • Run the Central Command agent console (strategy lifecycle + account actions). Purpose: guide/whoami, create/update strategies, backtest, deploy STOPPED, paper execute, and (explicitly) live orders. Behavior: READ + WRITE. Deploy without execute does NOT move money. Live place_order/close_position/cancel_order require confirm_live=true. Default force_paper=true. Auth: X-Api-Key (linked Connect keys preferred — free). Do not spoof X-Linked-User-Id. Cost: linked Connect keys free; otherwise prepaid / x402 per catalog price for agent-strategy. Rate limit: plan default. Returns: JSON envelope { ok, endpoint, status, data: { ok, guide|whoami|created|deployed|... } }. Guidelines: Start with action=guide then whoami. Prefer paper. Never invent outbound-proxy failures — report real HTTP status/body.
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  • List the apps in your Dockhold account, with each app's id, status, URL, and source repo. Call this first whenever the user asks about their apps, or when you need an app_id for any other tool.
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  • 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.
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  • Upload connector code to Core and restart — WITHOUT redeploying skills. MERGES with the GitHub state at `ref` by default (default ref: 'dev'). Sending a partial file set ONLY overlays those files — the rest of the connector is preserved from GitHub. To fully replace the connector dir (historical behavior), pass replace:true. Modes: • github:true (no files) — deploy the GitHub state at `ref` as-is. • github:true + files:[] — GitHub state at `ref` as BASE, your files overlay on top (incoming wins). • files:[] (no github) — default MERGE with GitHub state at `ref`. Refuses if no GitHub base exists (no silent nuke). • files:[] + replace:true — full replace. Wipes connector dir + writes only the provided files. Use deliberately. Multi-file connectors (server.js + dashboard HTML + RN bundle + package/manifest): pass each file with content_base64 (a single-line, escape-safe base64 string) instead of content — so you don't hand-escape ~90KB of HTML/JS/JSON inside one tool call. This is the CANONICAL agent path for a full connector; do NOT hand-roll `curl` against the raw endpoint (that skips connector registration / PAT provisioning). Common traps this design prevents: • Pre-fix bug (2026-06-06): sending just ui-dist HTML wiped server.js + node_modules — connector broke until a full re-upload. Now: those files merge with the GitHub base. • Pre-fix bug: github:true silently read from `main` even when patches were on `dev`. Now: defaults to dev; pass ref:'main' to opt into the legacy path.
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  • Check that the Builder filesystem state and GitHub state are in sync for a solution. Read-only probe — does NOT trigger a deploy. Returns: • ok: true + drifts: [] if everything matches • ok: false + drifts: [{path, kind}] listing files that differ (kinds: fs_missing, gh_missing, content_differs) Drift can creep in when GitHub writes happen but Builder FS doesn't get the mirror update (network blip, container restart mid-write). Boot sync heals most of it on next backend restart; this tool surfaces drift earlier. Run after a series of ateam_github_patch calls to confirm the Builder backend is consistent with GitHub before you ateam_build_and_run.
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