"namespace:io.github.getstack-run" matching MCP tools:

• me.validation_history

  AI Design Blueprint Doctrine

  Pro/Teams — return the authenticated user's architect.validate run history with the Blueprint Readiness Score (0-100), letter grade (A-F), and tier (draft, emerging, production_ready). Three lookup modes: (1) `run_id=<id>` returns a SINGLE run with the full persisted result_json — use this to RECOVER a result when your MCP client tool-call timed out before architect.validate returned. The run completes server-side and persists; the run_id is surfaced in the first progress notification of every architect.validate call so you have the recovery handle even when your client gives up early. (2) `repository=<name>` returns the full per-run trend for that repository plus a regression diff between the latest two runs. (3) No arguments returns one summary per repository the user has validated, sorted by most recent. Use modes (2) or (3) BEFORE calling architect.validate again on the same repository — they tell you which principles regressed since the last run, so you can focus the new review on what is actually changing. Auth: Bearer <token>. Pro or Teams plan required.

  Connector

• retry_run

  Hydrata - ANUGA Flood Simulation

  Retry a failed simulation run. Resets an errored run back to 'created' status and triggers a new package build. The same run ID is reused. Only valid when status is 'error'. Returns 409 for any other state.

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• create_commentary

  Bridge Town

  Attach narrative analysis to a model run, or to one named output of the run. Use this after compare_runs / get_run_output to save the agent's interpretation alongside the data it explains. If output_name is omitted, the commentary is run-level. If output_name is provided and the run has output data available, the name is validated against the same resolver as get_run_output.

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• hivelearn_publish_course

  HiveLearn

  Publish a course: sets is_published=true after validating that every lesson has content_url. Returns error if any lesson is still empty — run hivelearn_get_course_structure to diagnose.

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• me.validation_history

  AI Design Blueprint

  Pro/Teams — return the authenticated user's architect.validate run history with the Blueprint Readiness Score (0-100), letter grade (A-F), and tier (draft, emerging, production_ready). Three lookup modes: (1) `run_id=<id>` returns a SINGLE run with the full persisted result_json — use this to RECOVER a result when your MCP client tool-call timed out before architect.validate returned. The run completes server-side and persists; the run_id is surfaced in the first progress notification of every architect.validate call so you have the recovery handle even when your client gives up early. (2) `repository=<name>` returns the full per-run trend for that repository plus a regression diff between the latest two runs. (3) No arguments returns one summary per repository the user has validated, sorted by most recent. Use modes (2) or (3) BEFORE calling architect.validate again on the same repository — they tell you which principles regressed since the last run, so you can focus the new review on what is actually changing. Auth: Bearer <token>. Pro or Teams plan required.

  Connector

• training_list_runs

  Tenzro Ledger MCP

  List every active Tenzro Train run this node is syncing. Each run carries task_id, status (Pending/Active/Completed/Failed/Cancelled), current_round, state_root, enrolled_trainers, and (once terminal) the sealed receipt. Read-only — safe for monitoring agents.

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• start_simulation

  Hydrata - ANUGA Flood Simulation

  Start a flood simulation run for a built scenario. The scenario must be in 'built' status. Returns 202 with the new run. The run transitions through: built → queued → computing → processing → complete. After starting, poll get_run_status to track progress. Returns 409 if the scenario is not in the correct state.

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• deploy_service_from_file_contents

  Google Cloud Run

  Deploys a Cloud Run service directly from local source files. This method is suitable for scripting languages like Python and Node.js, of which the source code can be embedded in the request. This is ideal for quick tests and development feedback loops. You must include all necessary dependencies within the source files because it skips the build step for faster deployment. **Key Requirements:** 1. source_code: Should set to sourceCode.inlinedSource.sources with array of source files, each having `filename` and `content`. 2. Size limit: you are subject to total request size limit of 50MiB.

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• get_run_output

  Bridge Town

  Retrieve a single named output from a completed model run. Use this instead of get_run when you only need one output and want to avoid the 1 MiB truncation cliff for large multi-tab runs. Resolves run_id using full UUID or UUID prefix. Requires a successful run status.

  Connector

• models_infer

  Roboflow (Official)

  Run hosted inference on an image using a trained model. Returns JSON predictions only. For visualized/annotated images, use workflow_specs_run with a visualization block instead.

  Connector

• me.validation_history

  AI Design Blueprint Doctrine

  Pro/Teams — return the authenticated user's architect.validate run history with the Blueprint Readiness Score (0-100), letter grade (A-F), and tier (draft, emerging, production_ready). Three lookup modes: (1) `run_id=<id>` returns a SINGLE run with the full persisted result_json — use this to RECOVER a result when your MCP client tool-call timed out before architect.validate returned. The run completes server-side and persists; the run_id is surfaced in the first progress notification of every architect.validate call so you have the recovery handle even when your client gives up early. (2) `repository=<name>` returns the full per-run trend for that repository plus a regression diff between the latest two runs. (3) No arguments returns one summary per repository the user has validated, sorted by most recent. Use modes (2) or (3) BEFORE calling architect.validate again on the same repository — they tell you which principles regressed since the last run, so you can focus the new review on what is actually changing. Auth: Bearer <token>. Pro or Teams plan required.

  Connector

• get_run

  Hydrata - ANUGA Flood Simulation

  Get full details of a simulation run including timing and results. Returns the complete run record: status, progress, timing (start/end timestamps, duration), compute details (backend, instance type, cost), mesh info, error messages, and result log. Use get_run_status for lightweight polling; use this for final results.

  Connector

• list_brand_audit_watches

  dns

  Returns the caller's recurring brand-audit watches: watchId, domain, interval, webhook presence, last-run time, and active state. Owner-scoped. Read-only.

  Connector

• trainings_stop

  Roboflow (Official)

  Request an early stop on an in-flight training run. Distinct from cancel: the run finishes the current phase gracefully (mining or training) instead of terminating immediately.

  Connector

• validate_agent_trajectory

  IA-QA — 130+ QA & Dev Tools for AI Agents

  Run declarative assertions on an agent trace (OpenAI tool-call messages, LangChain run trees, or plain text logs). No LLM call — deterministic. Assertion types: order (tool A before B), must_call, must_not_call, max_calls, min_calls, no_error, recovery (agent continues after error). Returns per-assertion PASS/FAIL, parsed steps, and an overall verdict. Use this to gate CI/CD on agent behavior correctness.

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• run_risk_audit

  ENTIA Entity Verification

  Run comprehensive AI-readiness + digital risk audit on any domain. Analyzes SSL, DNS, structured data, LLM visibility. Returns risk score 0-100. 5 req/min, 30s timeout.

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• get_context

  Hemrock MCP

  Returns the universal context-setting primer for Hemrock models, plus an optional template-specific addendum. Always run this first before any other prompts.

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• get_store_flow_errors

  Power Automate MCP Server by Flow Studio

  [Requires Pro+ plan] [DEPRECATED — scheduled for removal] Get cached failed run history for a flow from the Power Clarity store (convenience wrapper around get_store_flow_runs with status=Failed). Returns failedActions and remediation hint per run to help diagnose issues. Data is from the stored snapshot — not live from the Power Automate API. Use get_live_flow_runs and filter by status=Failed instead.

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• validateTestSuite

  Keploy

  POST /apps/{appId}/test-suites/{suiteId}/validate — Validate a test suite — Run the suite against a public, non-loopback base URL to capture responses and run assertions. DO NOT use for local-app / localhost validation — the SaaS backend rejects private IPs with 500. For local apps, curl endpoints yourself (Bash) and pass the captured responses into create_test_suite directly. Requires scope: `write`.

  Connector

• get_live_flow_runs

  Power Automate MCP Server by Flow Studio

  Fetch live run history for a flow directly from the Power Automate API using impersonation — not the cached store. Returns run name, status, startTime, endTime, trigger name/code, and any top-level error.

  Connector