"Understanding File Systems and Their Functions" matching MCP servers:

MCP server to manage and deploy Scaleway Serverless Functions, enabling creation, listing, updating, deleting, downloading, and logging of functions through natural language.

A demonstration project for building and running Model Context Protocol (MCP) servers using Netlify Serverless Functions. It provides a template for deploying serverless MCP endpoints with automated CI/CD pipelines through Netlify.

Monitor failing GitHub Actions workflows, auto-fix them with OpenCode, and retry the run — driven by a workflow_run webhook, coordinated through an MCP server.

Enables creating release manifests and verifying that local release folders or public HTTPS bytes match the manifest, using read-only MCP tools.

Provides a read-only tool to check Wrangler configuration files for common mistakes before deployment, supporting environment selection and strict mode.

Supply-chain gate for AI agent skills and MCP servers: poison-scan tool definitions, hash-pin the vetted set into a lock file and verify drift in CI. truecopy-mcp is a drop-in stdio proxy that filters a live server's tools/list down to its pinned, unmodified, unpoisoned tools.

tailtest-cline is a Cline plugin that automatically generates and runs tests every time the agent edits a source file. https://github.com/avansaber/tailtest-cline

Enables AI coding agents to see their Odoo.sh projects by listing projects, branches and builds, waiting for a build to finish, reading build and server logs, and optionally rebuilding branches or updating the firewall. It runs read-only by default with bounded, time-limited tool calls, keeping the user's Odoo.sh session out of the agent's reach.

A Model Context Protocol server that lets development agents work with Odoo.sh from their development environment, listing branches, watching builds, and streaming logs. It sits on top of the odouche Python library's public interface.

MCP server that triggers Jenkins automation jobs and returns their results, with an action registry, parameter validation, and credential redaction.

Enables reviewing GitHub Actions workflows for outdated actions, deprecated Node runtimes, retired runners, deprecated commands, and security risks, with file, line, and fix for each finding.

Enables querying Codecov coverage data including file, commit, repository, and pull request coverage.

A comprehensive and efficient Model Context Protocol server for task management that works with Claude, Cursor, and other MCP clients, providing powerful search, filtering, and organization capabilities across multiple file formats.

Enables natural language interactions with CircleCI through Model Context Protocol, allowing users to retrieve build logs, find flaky tests, check pipeline statuses, and manage workflows without leaving their IDE.

An MCP server that connects Gemini 2.5 Pro to Claude Code, enabling users to generate detailed implementation plans based on their codebase and receive feedback on code changes.

Renders an interactive pipeline DAG and test-harness dashboard inline in MCP hosts, showing node statuses, pass rates, costs, and latency from a JSON state file.

Lets MCP clients such as Claude or ChatGPT find the pull requests waiting on your review, read their details and changed files, check CI status, post comments, and submit approve, request-changes, or comment reviews. It runs locally over stdio with a personal token or as a remote server with its own OAuth 2.1 authorization server (PKCE, dynamic client registration, per-client consent, and refresh-token rotation) so GitHub is only used to sign the user in.

Read-only MCP server for JFrog Artifactory repository intelligence, enabling listing repositories and paths, fetching metadata, properties, and stats, and performing bounded file searches without mutation.

SFTP deploys to shared hosting (cPanel, Plesk, any SFTP host) that an agent can undo. Every deploy backs up the files it replaces on the server first; restore puts them back and refuses if a live file was edited since. Deploy and restore only run a previewed plan. No delete, no-backup or prune tools.

Enforces disciplined programming practices by requiring AI assistants to audit their work and produce verified outputs at each phase of development, following structured workflows for refactoring, feature development, and testing.