"Octopus Deploy" matching MCP tools:

• get_project_info

  Fractera

  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.

  Connector

• deploy_from_url

  vibedeploy

  Publish a website to a live URL from a public archive link. Point this at a tar(.gz) archive on github / gist / S3 and the server fetches and deploys it, no upload from your side. Server-side fetch of a tar(.gz) archive from a public HTTPS URL, then deploy its contents. Sidesteps the case where your code-execution sandbox can reach github / gist / S3 etc. but not mcp.vibedeploy.be's upload endpoint. Equivalent to begin_deploy → POST uploadUrl → commit_deploy in one call. Hostname allowlist enforced; see the archiveUrl description.

  Connector

• ateam_build_and_run

  ateam-mcp

  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.

  Connector

• ateam_redeploy

  ateam-mcp

  Re-deploy skills WITHOUT changing any definitions. ⚠️ HEAVY OPERATION: regenerates MCP servers (Python code) for every skill, pushes each to A-Team Core, restarts connectors, and verifies tool discovery. Takes 30-120s depending on skill count. Use after connector restarts, Core hiccups, or stale state. For incremental changes, prefer ateam_patch (which updates + redeploys in one step).

  Connector

• tfdeploy

  InsideOut (Riley)

  WORKFLOW: Step 4 of 4 - Deploy infrastructure to the cloud Deploy infrastructure by starting a Terraform job for an InsideOut session. This tool initiates the actual deployment process after Terraform files have been generated. IMPORTANT: This starts a long-running job (15+ minutes). Use tfstatus to monitor progress. SINGLE-FLIGHT: only one TF job (apply/plan/destroy/drift) runs per session at a time. If another job is already in flight, tfdeploy returns tf_job_conflict with the live job_id — attach with tfstatus/tflogs instead of retrying, or pass force_new=true to override. Returns confirmation that the deployment has started. REQUIRES: session_id from convoopen response (format: sess_v2_...). OPTIONAL: plan_id (string) — Apply a previously created plan from tfplan. Preview-then-apply workflow: tfplan → tflogs (review) → tfdeploy(plan_id=...). OPTIONAL: sandbox (boolean, default false) — deploys real generated Terraform. Set to true for cheap sandbox template (testing only). OPTIONAL: ignore_drift (boolean, default false) - when true, proceeds with deploy even if infrastructure drift is detected. By default, deploys fail on drift. Use after reviewing drift details via tfdrift or tflogs. OPTIONAL: force_new (boolean, default false) - bypass the session-level single-flight guard. Use only when the existing run is provably wedged. CREDENTIAL FLOW (if credentials are missing): 1. Response includes a connect_url — present it to the user 2. Call credawait(session_id=...) to poll for credentials 3. When credawait returns success, retry tfdeploy Do NOT call credawait without first showing the connect URL to the user.

  Connector

• tfdeploy

  InsideOut (Riley)

  WORKFLOW: Step 4 of 4 - Deploy infrastructure to the cloud Deploy infrastructure by starting a Terraform job for an InsideOut session. This tool initiates the actual deployment process after Terraform files have been generated. IMPORTANT: This starts a long-running job (15+ minutes). Use tfstatus to monitor progress. SINGLE-FLIGHT: only one TF job (apply/plan/destroy/drift) runs per session at a time. If another job is already in flight, tfdeploy returns tf_job_conflict with the live job_id — attach with tfstatus/tflogs instead of retrying, or pass force_new=true to override. Returns confirmation that the deployment has started. REQUIRES: session_id from convoopen response (format: sess_v2_...). OPTIONAL: plan_id (string) — Apply a previously created plan from tfplan. Preview-then-apply workflow: tfplan → tflogs (review) → tfdeploy(plan_id=...). OPTIONAL: sandbox (boolean, default false) — deploys real generated Terraform. Set to true for cheap sandbox template (testing only). OPTIONAL: ignore_drift (boolean, default false) - when true, proceeds with deploy even if infrastructure drift is detected. By default, deploys fail on drift. Use after reviewing drift details via tfdrift or tflogs. OPTIONAL: force_new (boolean, default false) - bypass the session-level single-flight guard. Use only when the existing run is provably wedged. CREDENTIAL FLOW (if credentials are missing): 1. Response includes a connect_url — present it to the user 2. Call credawait(session_id=...) to poll for credentials 3. When credawait returns success, retry tfdeploy Do NOT call credawait without first showing the connect URL to the user.

  Connector

• deltasignal_readiness

  DeltaSignal ATLAS-7

  Use this read-only tool before analysis to verify that the DeltaSignal ATLAS-7 data plane is live, fresh, and safe to query. It returns service readiness, active source dates, issuer coverage, quality coverage, debt coverage, live-price status, market regime, and tower-coherence diagnostics. Parameters: none; call it exactly as-is when the user asks if DeltaSignal is ready or whether data freshness is acceptable. Behavior: read-only and idempotent; it performs one HTTPS read, has no destructive side effects, does not write external systems, and does not handle secrets or payments itself. Use it at the start of an agent workflow, after a deploy, or whenever results should be gated on freshness; use daily_changes for what changed and issuer tools for company-specific analysis.

  Connector

• one_shot

  quantifyme

  End-to-end deploy: generate strategy → train → deploy live. One of `prompt` (free-form NL), `preset` (curated winning strategy), or `community_id` (copy a published community strategy) is required. If more than one is passed, precedence is community_id > preset > prompt. Args: prompt: Natural-language strategy description (e.g. "Buy when RSI < 30, sell > 70"). symbol: Currency pair to backtest on. One of: EURUSD, USDJPY, GBPUSD, USDCHF, USDCAD, AUDUSD, NZDUSD. Default EURUSD. timeframe: Candle granularity. One of: 1min, 5min, 15min, 1h. Default 15min. claude_model: Which Claude variant to use for code generation. "sonnet" (default — best quality, 1/day free) or "haiku" (faster, 3/day free). Ignored when `preset` is set (no generation needed). preset: Curated winning-strategy slug. Skips Claude generation entirely — deploys a pre-saved strategy known to backtest well on the chosen symbol. Available slugs: ema_cross_fast, momentum, scalper_stack, sma_only, trend_ema, volatility, bb_squeeze, all_mix, pivot_kid_ema. Not every slug exists for every symbol — call list_models afterwards to confirm what deployed. community_id: Copy-trade a published community strategy. Pass the `id` of an entry from `browse_community`. Loads that exact strategy code, skips Claude generation, then trains + deploys it. `symbol`/`timeframe` still apply to the backtest+deploy. webhook_url: Optional webhook to receive live signals. telegram_chat_id: Optional Telegram chat ID for signal delivery. Returns IMMEDIATELY (the deploy runs in the background so the live card can stream progress) with: - job_token (str): pass to get_deploy_result to fetch the final result. - poll_url (str): the card polls this for live progress; you can ignore it. - pending (bool): always true here — the deploy is still running. - symbol, timeframe (str). Call this EXACTLY ONCE per request. Pass the user's words as `prompt`; do not pre-pick presets/community strategies — the server routes (vague → a proven community strategy, specific rules → a fresh generation). NEXT STEP (always): call get_deploy_result(job_token) ONCE — it blocks until the deploy finishes and returns the out-of-sample stats + `stem` + `source`/`author` as TEXT so you can summarize. The live card already shows the chart, so you do NOT need get_model_chart. If source='community', tell the user it used a pre-existing strategy by @author and offer to generate a custom one.

  Connector

• get_strategy_code

  quantifyme

  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.

  Connector

• get_deploy_result

  quantifyme

  Wait for a `one_shot` deploy to finish and return its final result. `one_shot` returns a job_token immediately and the LIVE CARD already streams progress and renders the interactive backtest chart itself. Call this ONCE with the token to get the final numbers as TEXT so you can summarize them — it does NOT render another card (no need for get_model_chart). It BLOCKS until the deploy finishes (or ~2.5 min); on timeout it returns ok:false + pending:true — call it again with the same token. IMPORTANT: if `source == "community"`, the deploy used a PRE-EXISTING strategy by `@author` — tell the user that, share the `live_url` as the Live dashboard link, and ask whether they'd like to GENERATE A CUSTOM strategy instead. Use the `note` field as your guide. Args: job_token: the token returned by `one_shot`. Returns: dict with: ok, stem, model, live_url, symbol, timeframe, channels (list), stats:{ret, wr, pf, n, mdd} (out-of-sample test-split metrics — SHOW THESE), source ("community" | "generated"), author (community username if any), author_url + strategy_url (render @author and "pre-existing strategy" as those Markdown links), community_id, suggest_custom (bool), and note (a ready instruction — follow it). On failure: {ok:false, error} (or {pending:true}).

  Connector

• get_project_info

  Fractera

  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.

  Connector

• check_status

  Fractera

  Read the current installation progress ONCE, on demand. Call this only when the user explicitly asks how the deploy is going (e.g. "what is the status", "did it finish") — never on a timer and never in a polling loop. The deploy takes 8-14 minutes and the authoritative status channels are the email pipeline + the dashboard; one read on request is enough. Returns the current step, the list of completed steps (~44 total in a full bootstrap), and whether installation is done or failed.

  Connector

• dero_get_gas_estimate

  DERO MCP Server

  Estimate gas (compute + storage) for transfers, SC deploys, or SC invokes via DERO.GetGasEstimate. This is a PRE-FLIGHT check; nothing is submitted. When to call: BEFORE any wallet-side transfer/scinvoke (using external wallet tooling) to size fees, OR when explaining deploy costs to a user. PREFER citing dero_docs_search("gas estimate" or "fees") so the user understands how compute vs storage gas are charged. Input Requirements (CRITICAL): - At least ONE of `transfers`, `sc`, or `sc_rpc` MUST be provided. - `sc` is the DVM-BASIC contract source string when estimating a deploy. - `sc_rpc` is an array of `{ name, datatype, value }` invocation arguments (entrypoint + SC_ID + caller-provided params). - `signer` is OPTIONAL but PREFERRED; pass the `dero1.../deto1...` address that would sign the eventual tx. Output: `{ gascompute, gasstorage, status }`.

  Connector

• deploy_app

  mcp

  Deploys an app to a VM and exposes it at a public https://<name>-<id>.redu.cloud URL. The container is built ON the VM. PREREQS — run check_deploy_prerequisites first for network_id + keypair_name, then plan_deploy for cost approval. Source can be git repo or prepare_upload source_token. PORT must be the real app listen port. To wire a DB, pass database:'managed' (dedicated managed datastore VM on the same private network, reused on same-name redeploy) or database:'single_vm' for Postgres on the app VM. Choose db_engine ('postgres' default; 'mysql'/'mariadb' for WordPress/Matomo/LAMP, managed only). For WordPress/WooCommerce cluster intent, do not use generic stateless deploy: pass app_profile, cluster_target:true, database:'managed', db_engine:'mariadb' or 'mysql', cluster_media_mode:'media_space', and either media_space_id or create_media_space:true. Redu mounts the media space into wp-content/uploads and refuses unsafe local uploads. Build+provision takes minutes; poll list_deployments/get_deployment.

  Connector

• prepare_upload

  mcp

  Returns the LOCAL shell commands to package your working directory and upload it for an upload-mode deploy (no git, no PAT). Run them in the user's terminal, capture `source_token` from the upload's JSON response, then call deploy_app with that source_token (omit repo). The upload authenticates AUTOMATICALLY with a short-lived ticket minted from your MCP credential — NO API key needed in the command and nothing secret is printed (it falls back to needing $REDU_API_KEY only if minting is unavailable). Excludes node_modules/.git/.venv/build output and .env by default; honors .gitignore when is_git_repo=true.

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• get_project_context

  Zephex

  Scans manifests and config — one topic slice per call. Detects stack, scripts, monorepo, API routes, auth/DB providers, integrations, env vars. Secret-sanitized. Workflow: topic=identity first on new repo → follow next_calls (framework, run, structure). Topics: identity, framework, backend, frontend, database, auth, deploy, run, structure, integrations, security, overview. brief ≤500 tokens; standard adds version health; full adds file tree. 7 credits hosted. Every response: topic, focus, summary, data.key_paths, hint, related_topics, next_calls, meta.credits. Use data and next_calls — never invent commands. Call when: new session; user asks stack, scripts, or how to run/test/build. Do NOT: symbol search (find_code), file bodies (read_code), wiring (explain_architecture), tests (check_test). Pass path (absolute project dir) or inline_files (package.json + 2-4 source files). force:true refreshes cache. Read-only.

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• Zephex_dev_info

  Zephex

  Expert developer playbooks — not your repo. Stripe webhooks & checkout, Supabase RLS, Next.js auth (clerk, next-auth), payment flows, CSP/HSTS, deploy patterns. operation=search finds entries by question; operation=get returns full guidance by slug from search. Read summary and checklist first. 2 credits hosted. No project path. Call when standard patterns beat guessing — wiring stripe checkout, fixing auth middleware, Supabase RLS policies, hardening after audit_headers. Use AFTER repo tools if code context is still thin. NOT for user's codebase (get_project_context, find_code, read_code), registry packages (check_package), tests (check_test), live URL (audit_headers), or saving decisions (project_memory). Example: Zephex_dev_info({ operation: 'search', query: 'Stripe webhook raw body verification', category: 'payments' }) then get with returned slug. Read-only.

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• verify_deployment

  agent-ready-kit

  Use this after a customer has deployed the agent-ready files to confirm the live site reaches the expected level. Re-scans the site, reports current level, which checks pass, and which still fail with their fix string. Same scanner as scan_site, but framed as post-deploy verification rather than initial assessment.

  Connector

• ping

  Japan Toilet & Accessibility

  Connection test / health check — call this first to confirm the server is reachable. Returns server identity, deploy version, tool count, station coverage, and the update times of the realtime layers (JMA alerts, train status) so you can confirm freshness, not just liveness. No auth, no arguments, lightweight.

  Connector

• update_schema

  RationalBloks

  Update a project's schema (saves to database, does NOT deploy). ⚠️ CRITICAL: Follow ALL rules from create_project: • FLAT format (no 'fields' nesting) • string: MUST have max_length • decimal: MUST have precision + scale • Use "datetime" NOT "timestamp" • DON'T define: id, created_at, updated_at • NEVER create users/customers/employees tables (use app_users) ⚠️ MIGRATION RULES: • New fields MUST be "required": false OR have "default" value • Cannot add required field without default to existing tables • Safe: {new_field: {type: "string", max_length: 100, required: false}} WORKFLOW: 1. Use get_schema to see current schema 2. Modify following ALL rules 3. Call update_schema (saves only) 4. Call deploy_staging to apply changes 5. Monitor with get_job_status NOTE: This only saves the schema. You MUST call deploy_staging afterwards to apply changes.

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