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CI/CD & DevOps

Continuous Integration and Continuous Deployment tools and workflows. Enables automation of software delivery pipelines, build processes, testing, and deployment operations.

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    Enables MCP clients to inspect Google Play releases, reviews, Android vitals, and scoped bulk reports, and to prepare explicitly authorized changes using locally supplied service-account credentials. Reads are default, while optional writes and sensitive reads require explicit configuration and single-use execution.
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    AGPL 3.0
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    Enforces authorize-before-execute for any MCP-compatible AI agent. Exposes atlasent_evaluate and atlasent_verify_permit tools so a protected tool call only runs after AtlaSent issues and verifies a signed, single-use permit — fail-closed on any error, timeout, or malformed response.
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    Apache 2.0
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    One workspace for every AI coding assistant. Governance tools for API lint, diff, persistent ledger, multi-model deliberation, security audit, and test verification. Works with Claude Code, Codex, Cursor, and Gemini CLI.
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    Git and GitHub operations — repo status, diffs, branches, stashes, PRs, issues, and Actions from MCP.
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    Mneme exposes a governed Decision Index so MCP clients can propose candidate architectural decisions and query decision state, applicability, and traceability. Proposals remain non-authoritative: accepting or activating protections stays under explicit human control.
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    Enables interaction with the Tembo API to manage organization tasks and view enabled code repositories. Users can create, search, and list tasks or retrieve account information directly through MCP-compatible clients.
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    Enables AI assistants to manage CData Sync operations, including data synchronization jobs, connections, and ETL processes through stdio or HTTP transports. It provides tools for executing jobs, monitoring real-time progress via Server-Sent Events, and handling comprehensive workspace configurations.
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    The Octri CLI's MCP server. Push OpenAPI specs, build SDKs in ten languages, publish API docs, and triage production SDK errors from your AI assistant.
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    MCP server for the StepSecurity platform that enables investigating supply-chain and CI/CD security issues through natural language.
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    Apache 2.0
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    Publishes static sites to Drop2Run from an AI agent: hand it files written in the chat or a folder on disk, and it returns a live HTTPS URL. Six tools — publish_files, publish_dir, list_sites, delete_site, and login / login_code — with no git, no build step and no repository.
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    Enables AI clients to deploy static sites, track deployments, and manage sites on a Shiplo account through the Model Context Protocol.
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    Agentic data quality MCP server — runs structured validation rules against warehouses (DuckDB, BigQuery, Athena, Databricks, Postgres), diagnoses failures with LLM root cause analysis, and proposes SQL remediations. Full audit trail of every AI decision.
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    Stops your AI from re-introducing bugs, leaking provider keys, or weakening tests. Bug fixes become permanent regression guards; blocked mistakes become AI lessons the agent reads and learns from before its next edit.
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    Developers are constantly feeding context files to AI tools like Cursor, Windsurf, Copilot Workspace, and Claude Code. If your agent doesn't understand your real database schema, it writes code that fails in production. LintBase acts as the bridge. It connects directly to your database, reads the ground truth of your live documents, and generates structured context optimized for AI. 🤖 Stops AI
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    MIT
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    Self-hosted, multi-zone MCP server for GKE/EKS: git repo of Python tools → canary-deployed Rust+Python workers, OAuth sign-in, roles per group.
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    BSD 3-Clause

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