"A server for running Kubernetes with Cursor integration" matching MCP tools:

• list_products

  agentic-shelf

  List products from the connected store, paginated. Use this tool when an agent needs to DISCOVER products by browsing the catalog rather than VERIFYING a known SKU. The response includes the SKU for every product, so a follow-up ``check_stock(sku)`` or ``get_product_details(sku)`` is a natural next step. Args: limit: Number of products to return (1-50, default 10). cursor: Opaque cursor from a previous response's ``next_cursor``. Omit for the first page. Returns: Dictionary with: - products: list of {sku, title, description (≤400 chars), product_type, tags, price, currency, available, image_url, storefront_url} - next_cursor: str or null — pass to the next call to paginate - has_more: bool — whether more products exist - live / source: provenance flags

  Connector

• tflogs

  InsideOut (Riley)

  MONITORING: Fetch Terraform deployment logs with pagination Fetches logs from a running or completed Terraform deployment job. For **completed jobs**: uses REST endpoint for instant retrieval (supports `tail` for server-side filtering). For **running jobs**: streams via SSE with timeout-based pagination. **PAGINATION** (running jobs only): Use `last_event_id` from the response to fetch more: 1. First call: `tflogs(session_id='...')` → get logs + `last_event_id` 2. Next call: `tflogs(session_id='...', last_event_id='...')` → get NEW logs only 3. Repeat until `complete: true` in response **RESPONSE FIELDS**: - `logs`: Array of log messages collected - `last_event_id`: Pass this back to get more logs (pagination cursor, SSE only) - `complete`: true if job finished, false if more logs may be available - `total_logs`: total log entries before tail truncation REQUIRES: session_id from convoopen response (format: sess_v2_...). OPTIONAL: job_id to target a specific deployment (use tfruns to discover IDs), timeout (default 50s, max 55s), last_event_id (for pagination), tail (return only last N entries) ⚠️ CONTEXT WARNING: Deploy logs can be hundreds of lines. Use tail: 50 for completed jobs to avoid blowing up the context window.

  Connector

• strale_ping

  Strale - 290+ API capabilities for AI agents

  Checks that the Strale API is reachable and the MCP server is running. Call this before a series of capability executions to verify connectivity, or when troubleshooting connection issues. Returns server status, version, tool count, capability count, solution count, and a timestamp. No API key required.

  Connector

• lifecycle_history

  Servicialo MCP Server

  Get the SCEvent stream for a session — all observed transitions reconstructed from status_history. Returns events[] with discriminated union by event_type (sc.scheduled, sc.confirmed, sc.completed, sc.delivered, sc.verified, sc.cancelled, etc.), plus stream_completeness ("complete" | "partial_pre_trigger") and pagination cursor. Events carry origin="reprojected_from_status_history" and canonical SCEvent shape per docs/protocol/sc-event-canonical-schema-2026-04-18.md §7.2. Filters: event_types (e.g. ["sc.delivered"]), from_sequence (cursor), limit (default 50, max 500). PII note: delivery_proof clinical fields (summary, outcome, next_steps) are returned only for admin-scoped keys. IMPORTANT: backfilled sc_resolved timestamps do NOT emit sc.resolved events in this stream (Forma B, see decisions log 2026-04-18-lifecycle-history-backfill-policy). For current resolution status, use lifecycle_get_state.sc_resolution. Requires X-Org-Api-Key.

  Connector

• shillbot_claim_task

  Swarm Tips — Aggregated AI Agent Activities

  [STATE] Claim a Shillbot task. Returns an unsigned base64 Solana transaction the agent must sign locally with its wallet, then submit via shillbot_submit_tx with action="claim". Non-custodial — the MCP server never sees your private key. Requires a registered wallet (call register_wallet first).

  Connector

• get_app_status

  BorealHost

  Get app installation status and log. Poll this after install_app() to track progress. Requires: API key with read scope. Args: slug: Site identifier app_id: App ID from install_app() response Returns: {"id": "uuid", "app_name": "forge", "status": "running"|"installing"|"failed", "install_log": "..."} Statuses: "installing", "running", "stopped", "failed", "uninstalled"

  Connector

• switch_dannet_server

  dannet

  Switch between local and remote DanNet servers on the fly. This tool allows you to change the DanNet server endpoint during runtime without restarting the MCP server. Useful for switching between development (local) and production (remote) servers. Args: server: Server to switch to. Options: - "local": Use localhost:3456 (development server) - "remote": Use wordnet.dk (production server) - Custom URL: Any valid URL starting with http:// or https:// Returns: Dict with status information: - status: "success" or "error" - message: Description of the operation - previous_url: The URL that was previously active - current_url: The URL that is now active Example: # Switch to local development server result = switch_dannet_server("local") # Switch to production server result = switch_dannet_server("remote") # Switch to custom server result = switch_dannet_server("https://my-custom-dannet.example.com")

  Connector

• browse_by_tag

  AI Agents Overflow

  Browse the knowledge base by technology tag at the START of a task. Call this when beginning work with a specific technology to discover what verified knowledge already exists — before you hit problems. Examples of useful tags: 'pytorch', 'cuda', 'fastapi', 'docker', 'ros2', 'numpy', 'jetson', 'arm64', 'postgresql', 'redis', 'kubernetes', 'react'. Returns a list of questions (title + tags + score) for the given tag, ordered by community score. Call `get_answers` on relevant results.

  Connector

• whensport_tdf_getRacePhase

  tour-de-france-2026

  Get current Tour de France race phase. Returns one of: 'pre' (before the first stage, with nextStage + daysUntil), 'live' (a stage is currently running, with currentStage + elapsedPct), 'rest-day' (rest day between stages, with restDay + nextStage), 'between-stages' (off-day between consecutive stages, with lastStage + nextStage), 'finished' (race over, with finalStage).

  Connector

• convoawait

  InsideOut (Riley)

  Wait for a pending response from Riley after a convoreply timeout. 🎯 USE THIS TOOL WHEN: convoreply returned a timeout error. This allows you to continue waiting for the response without resending the message. REQUIRES: - session_id: from convoopen response OPTIONAL: - message_id: if known (from convoreply timeout error) - timeout (integer): seconds to wait. For Cursor, use 50 (default). Max 55. Returns the same format as convoreply when successful.

  Connector

• tflogs

  InsideOut (Riley)

  MONITORING: Fetch Terraform deployment logs with pagination Fetches logs from a running or completed Terraform deployment job. For **completed jobs**: uses REST endpoint for instant retrieval (supports `tail` for server-side filtering). For **running jobs**: streams via SSE with timeout-based pagination. **PAGINATION** (running jobs only): Use `last_event_id` from the response to fetch more: 1. First call: `tflogs(session_id='...')` → get logs + `last_event_id` 2. Next call: `tflogs(session_id='...', last_event_id='...')` → get NEW logs only 3. Repeat until `complete: true` in response **RESPONSE FIELDS**: - `logs`: Array of log messages collected - `last_event_id`: Pass this back to get more logs (pagination cursor, SSE only) - `complete`: true if job finished, false if more logs may be available - `total_logs`: total log entries before tail truncation REQUIRES: session_id from convoopen response (format: sess_v2_...). OPTIONAL: job_id to target a specific deployment (use tfruns to discover IDs), timeout (default 50s, max 55s), last_event_id (for pagination), tail (return only last N entries) ⚠️ CONTEXT WARNING: Deploy logs can be hundreds of lines. Use tail: 50 for completed jobs to avoid blowing up the context window.

  Connector

• discovery_upload

  Disco

  Upload a dataset file and return a file reference for use with discovery_analyze. Call this before discovery_analyze. Pass the returned result directly to discovery_analyze as the file_ref argument. Provide exactly one of: file_url, file_path, or file_content. Args: file_url: A publicly accessible http/https URL. The server downloads it directly. Best option for remote datasets. file_path: Absolute path to a local file. Only works when running the MCP server locally (not the hosted version). Streams the file directly — no size limit. file_content: File contents, base64-encoded. For small files when a URL or path isn't available. Limited by the model's context window. file_name: Filename with extension (e.g. "data.csv"), for format detection. Only used with file_content. Default: "data.csv". api_key: Disco API key (disco_...). Optional if DISCOVERY_API_KEY env var is set.

  Connector

• bank_accounts

  Inferventis — Financial Data, News & Web MCP

  Retrieves bank account details and recent transaction history via a connected bank API integration. Returns a list of transactions for the specified account, or for all linked accounts when no account ID is provided. Use bank_accounts when an agent needs to inspect account balances, review recent spending, categorise transactions, or reconcile records against a specific bank account. Prefer open_banking_transactions when the integration uses a PSD2 Open Banking provider (TrueLayer) covering 300+ UK and European banks — open_banking_transactions returns richer transaction metadata including merchant names, categories, and running balances. Prefer stripe_payments when the source of payments is a Stripe merchant account rather than a retail bank account. This tool requires a valid bank API credential to be configured on the server.

  Connector

• execute_integration

  mcp

  Execute an integration action — e.g., send an email via Resend, create a payment via Mollie. The system resolves vault credentials server-side so you never handle API keys directly. The integration must be configured first via setup_integration (not needed for built-in integrations). Call get_integration_schema first to get the exact endpoint name and required input fields.

  Connector

• investigate_question

  VaultCrux Memory Core

  Composite server-side investigation tool. Pass a question and the server automatically: (1) detects intent (aggregation/temporal/ordering/knowledge-update/recall), (2) queries the entity index for structured facts, (3) builds a timeline for temporal questions, (4) retrieves memory chunks with the right scoring profile, (5) expands context around sparse hits, (6) derives counts/sums for aggregation, (7) assesses answerability, and (8) returns a recommendation. Use this as your FIRST tool for any non-trivial question — it does the multi-step investigation that would otherwise take 4-6 individual tool calls. The response includes structured facts, timeline, retrieved chunks, derived results, answerability assessment, and a recommendation for how to answer.

  Connector

• list_templates

  Carbone MCP

  List stored Carbone templates with filtering, search, and pagination. Filter by Template ID, Version ID, category, or upload origin. Use includeVersions to see the full version history of each template. Supports cursor-based pagination for large collections. Note: filtering by tags is not supported by the Carbone API — use list_tags to discover tags, then filter results manually.

  Connector

• convoawait

  InsideOut (Riley)

  Wait for a pending response from Riley after a convoreply timeout. 🎯 USE THIS TOOL WHEN: convoreply returned a timeout error. This allows you to continue waiting for the response without resending the message. REQUIRES: - session_id: from convoopen response OPTIONAL: - message_id: if known (from convoreply timeout error) - timeout (integer): seconds to wait. For Cursor, use 50 (default). Max 55. Returns the same format as convoreply when successful.

  Connector

• lookup_headers

  botoi-mcp

  Fetch HTTP response headers for a URL. Use when inspecting server configuration, security headers, or caching policies.

  Connector

• register

  AI Agents Overflow

  Register your agent to start contributing. Call this ONCE on first use. After registering, save the returned api_key to ~/.agents-overflow-key then call authenticate(api_key=...) to start your session. agent_name: A creative, fun display name for your agent. BE CREATIVE — combine your platform/model with something fun and unique! Good examples: 'Gemini-Galaxy', 'Claude-Catalyst', 'Cursor-Commander', 'Jetson-Jedi', 'Antigrav-Ace', 'Copilot-Comet', 'Nova-Navigator' BAD (too generic): 'DevBot', 'CodeHelper', 'Assistant', 'Antigravity', 'Claude' DO NOT just use your platform name or a generic word. Be playful! platform: Your platform — one of: antigravity, claude_code, cursor, windsurf, copilot, other

  Connector

• healthcheck

  ALM X++ MCP Server

  WHEN: checking server status, loaded D365 version, or custom model path. Triggers: 'status', 'statut', 'is the server ready', 'how many chunks', 'index loaded'. Returns JSON with: status, indexed chunk count, loaded version, custom model path.

  Connector