Enables agents and teams to manage versioned delivery work items, role-tagged handoffs, revision- and source-bound evidence, QA gate evaluation, and release-owner attestations through MCP tools.
Enables AI assistants to deploy and manage hosted apps from git repos, read logs, add Postgres databases and domains, manage API keys and budgets, and send requests to 200+ AI models. Connects over remote Streamable HTTP with OAuth sign-in, so users need no API keys, installs, or local server.
Enables deterministic GitHub issue and pull request delivery workflows, including issue creation, development, verification, PR publication, review, and merge, with strict configuration and admission controls.
A LAN multi-AI collaborative development ecosystem connecting tools like Cursor, Windsurf, and Claude Desktop via MCP for automated Dev-QA-Ops workflows.
Enables evidence-first release readiness assessment by running or accepting build, API, browser, visual, performance, and security evidence, then returning SHIP, REVIEW, or HOLD recommendations with clustered regressions.
Enables acceptance gates for AI coding-agent runs by recording evidence, running deterministic validation, applying a quality gate, and rendering auditable outcomes.
Enterprise-grade MCP server for Jenkins CI/CD integration that enables AI assistants to diagnose build failures, analyze pipelines, and search logs through natural conversation.
Enables LLM agents to connect to multi-cloud DevOps control planes for Terraform plan inspection, drift detection and remediation, cost estimation, incident triage, and cloud resource discovery across Azure, AWS, and GCP. It supports autonomous workflows for PR review, FinOps optimization, and self-healing operations through MCP tools.
Connects AI coding assistants to GitLab instances, enabling project and issue management, merge request reviews, CI/CD inspection, repository browsing, code search, and local AI-powered features via Ollama.
Enables lifecycle-first governance for Edge AI fleets via MCP tools for approval requests, gate evaluation, and manual hold, ensuring deterministic deployment decisions with two-person approval, attestation, and safe rollback.
Enables LLM clients to access DevSecOps tooling such as CI/CD pipeline status, vulnerability triage, log search, and dependency scanning through MCP, turning AI copilots into security-aware engineering partners.
Enables AI clients to analyze software test results and defect records, producing explainable GO, CONDITIONAL_GO, or NO_GO release-readiness recommendations with deterministic risk scoring, failed-test retrieval, defect hotspot ranking, and regression test planning.
A hosted remote MCP server for managing Android release gates, with tools to check release status, explain permission blockers, issue release receipts, summarize device matrices, and export release logs.
Provides AI agents with 25 security analysis tools including vulnerability scanning, package hallucination detection, prompt injection firewall, and CI/CD integration.