Skip to main content
Glama
135,512 tools. Last updated 2026-05-22 17:59

"Information about CI/CD (Continuous Integration and Continuous Deployment)" matching MCP tools:

  • Signed snapshot of corpus liveness: distinct_cells, distinct_bands, facts_scanned, top per-band counts, manifest CIDs. Same payload that backs /v1/stream's corpus.state tick (signed). Use this for a one-shot poll instead of holding an SSE connection. When to use: Call when an agent needs a single liveness reading to surface in a dashboard, attach to a report, or decide whether to refresh local caches. Includes ed25519 signature over a deterministic preimage so the snapshot is verifiable. For a continuous feed, GET /v1/stream over Server-Sent Events instead.
    Connector
  • Returns the full list of domains under continuous SiteGuardian monitoring for the authenticated account. Each entry includes the domain, current security grade (A–F), timestamp of the last completed scan, and a relative dashboard URL. Use this when the user asks what they are monitoring, wants an inventory summary, or needs to look up a specific domain's exact spelling before calling get_domain_status / get_drift_events / get_fix_recommendations. The list is scoped entirely by the API key — there is no filter parameter to widen or narrow the result. Do NOT use this to enumerate domains the user does not own or monitor — it only returns their own inventory. Do NOT call it to trigger a scan (it does not); use scan_domain for one-off checks. Requires a valid API key.
    Connector
  • Returns information about safety features on Makuri, including age verification, content filtering, parental controls, and AI safety guardrails. Use when the user asks about child safety, content moderation, or how Makuri protects minors.
    Connector
  • Deploy a project to the staging environment. This triggers: (1) Schema validation, (2) Docker image build, (3) GitHub commit, (4) Kubernetes deployment, (5) Database migrations. The operation is ASYNCHRONOUS - it returns immediately with a job_id. Use get_job_status with the job_id to monitor progress. Deployment typically takes 2-5 minutes depending on schema complexity. If deployment fails, check: (1) Schema format is FLAT (no 'fields' nesting), (2) Every field has a 'type' property, (3) Foreign keys reference existing tables, (4) No PostgreSQL reserved words in table/field names. Use get_project_info to see if the deployment succeeded.
    Connector
  • INSPECTION: List all Terraform deployment runs for a session Returns job IDs, statuses, types (apply/destroy), and timestamps for every run. Use this to see deployment history, find job IDs for log inspection, or check which deployments succeeded or failed. REQUIRES: session_id from convoopen response (format: sess_v2_...).
    Connector
  • Returns the full three-step Demand Discovery validation framework: (1) Market Research, (2) Demand Discovery Report with the Demand Score and Build/Pivot/Kill verdict, (3) Agentic Launch (90-day continuous outreach). Use when a user asks "how do I validate an idea?", "what's the methodology?", or wants to understand the structured approach. Built on the "behavior over opinion" principle. Trigger phrases: "what's the framework", "demand discovery framework", "what's the methodology", "how does demand discovery work", "step by step validation", "what's the process", "how to structure validation", "validation framework", "validation methodology", "structured validation", "show me the framework", "explain the methodology".
    Connector

Matching MCP Servers

Matching MCP Connectors

  • Persistent zero-knowledge memory for AI agents. AES-256-GCM encryption, PII redaction.

  • The PropelAuth Integration MCP Server helps you and your favorite AI agent integrate PropelAuth as quickly and easily as possible into your project. Whether you're integrating PropelAuth into your Next.js project or your FastAPI backend, the Integration MCP Server will ensure your AI agent has the best context possible for a successful integration.

  • Returns structured information about what the Recursive platform includes: features, AI model details, supported integrations, and what's included at every tier. Use for systematic feature comparison.
    Connector
  • Returns information about the supplier network: available destinations, experience categories, booking platforms, and protocol details. Call this before search_slots to understand what regions and activity types are available.
    Connector
  • Returns information about the supplier network: available destinations, experience categories, booking platforms, and protocol details. Call this before search_slots to understand what regions and activity types are available.
    Connector
  • Returns information about the supplier network: available destinations, experience categories, booking platforms, and protocol details. Call this before search_slots to understand what regions and activity types are available.
    Connector
  • 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').
    Connector
  • Switch the app's V1 CI from "boot the real app + deps" mode to sandbox mode (mocks fetched by content-hash from the cloud canonical pool). The doc-stated trigger: ~1 week after CI is wired, when the dev has felt the slow runs / flakes and you can pitch "your CI takes 90s and flaked twice this week — rerecord mocks and CI drops to ~8s." What flips: * The CI workflow YAML gets a --sandbox flag on `keploy test-gen run` and the docker-compose-up step removed. This tool returns the updated YAML; you re-PR it. Pre-condition: every resource you want in CI must have recorded mocks (config.yaml.mockRegistry.mock populated). Resources without mocks will fail in sandbox mode because there's nothing to serve. Run devloop_record_sandbox per resource first; verify via devloop_schema_drift_report-style checks before proposing the switch.
    Connector
  • Apply or stack animations on objects in an existing 3D scene. Single animation (backward compatible): Provide animation_type (string) to apply one animation. Existing animation config fields are PRESERVED by default. Only missing fields are filled from defaults. Stacked animations (new): Provide animations[] array to apply multiple animations at once. Each entry can target a different object and carry its own config. Compatible animations on the same object are merged safely. Channel conflicts (e.g. float + bounce both on position.y) are detected and reported as warnings — not errors. Config merge behavior (override field): override: false (default) — existing config fields win. Preserves range, speed, amplitude set by generate_scene. override: true — incoming config fully replaces existing. Rotate range semantics: range >= 3.14 → CONTINUOUS SPIN (robot.rotation.y = t * speed) range < 3.14 → OSCILLATION (robot.rotation.y = sin(t) * range) Default range for rotate is 6.28 (full continuous spin). Merge flag: merge: true (default) — new animations added alongside existing. merge: false — existing animations for same target+type replaced.
    Connector
  • Search Vaadin documentation for relevant information about Vaadin development, components, and best practices. Uses hybrid semantic + keyword search. USE THIS TOOL for questions about: Vaadin components (Button, Grid, Dialog, etc.), TestBench, UI testing, unit testing, integration testing, @BrowserCallable, Binder, DataProvider, validation, styling, theming, security, Push, Collaboration Engine, PWA, production builds, Docker, deployment, performance, and any Vaadin-specific topics. When using this tool, try to deduce the correct development model from context: use "java" for Java-based views, "react" for React-based views, or "common" for both. Use get_full_document with file_paths containing the result's file_path when you need complete context.
    Connector
  • Calculate the recommended inverter size for running AC loads from a DC battery system. Accounts for continuous power, startup surge power (motors typically surge 2-3x), and includes a 25% headroom for the continuous rating. Returns the recommended inverter wattage and the DC current draw at system voltage.
    Connector
  • INSPECTION: List all Terraform deployment runs for a session Returns job IDs, statuses, types (apply/destroy), and timestamps for every run. Use this to see deployment history, find job IDs for log inspection, or check which deployments succeeded or failed. REQUIRES: session_id from convoopen response (format: sess_v2_...).
    Connector
  • Returns general information about the Makuri platform, including mission, target users, founding details, and company information. Use this tool when the user asks 'what is Makuri', 'who made it', or wants a general overview.
    Connector
  • IMPORTANT: Always use this tool FIRST before working with Vaadin. Returns a comprehensive primer document with current (2025+) information about modern Vaadin development. This addresses common AI misconceptions about Vaadin and provides up-to-date information about Java vs React development models, project structure, components, and best practices. Essential reading to avoid outdated assumptions. For legacy versions (7, 8, 14), returns guidance on version-specific resources.
    Connector
  • Returns information about the supplier network: available destinations, experience categories, booking platforms, and protocol details. Call this before search_slots to understand what regions and activity types are available.
    Connector
  • Check the status of a deployment job. STATUS VALUES: pending (job queued), running (deployment in progress), completed (success), failed (deployment failed). TIMELINE: Typical deployment takes 2-5 minutes. If status is 'running' for >10 minutes, check get_project_info for detailed pod status. If status is 'failed', use get_project_info to see deployment errors and check schema format (must be FLAT, no 'fields' nesting).
    Connector