"How to work with local files" matching MCP servers:

Converts Jenkins declarative pipelines into GitHub Actions workflow YAML files, facilitating migration from Jenkins to GitHub Actions CI/CD.

A local MCP server that connects Claude Desktop, Claude Code, and Claude Chat to your Azure DevOps organization, enabling querying work items, reviewing pull requests, triggering pipelines, searching code, managing test plans, and updating wikis using plain language.

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Enables AI agents to deploy static files and get live HTTPS URLs instantly, with support for custom domains and data residency.

Checks npm and PyPI packages for outdated versions, deprecation status, and breaking changes with cited sources, enabling AI agents to verify dependency freshness.

Security auditor for CI ecosystems that detects supply-chain and injection flaws in CI/CD configuration files across seven CI platforms, providing taint analysis, remediation, and compliance scoring.

A lightweight, powerful, and flexible workflow engine that executes tasks defined in YAML configuration files.

Local MCP runtime that gives persistent cross-session memory to 12 AI coding agents (Claude Code, Cursor, Codex, Gemini CLI, Windsurf, Amp, and more). SQLite-backed state survives context resets. Install: npm install -g @egchq/egc

Provides MCP tools to get a single-call snapshot of git and GitHub Actions CI status across all repositories in a folder, flag missing or stale architecture docs, write doc files, and detect release drift between source and release repositories.

Enables AI coding tools to validate local projects and publish or update applications to Bedengan App Hub via API, with automated checks and live deployment without manual approval.

MCP server for GitLab CI/CD — pipelines, jobs, schedules, branches, tags, merge requests and repository files. Works with any GitLab (SaaS gitlab.com or self-hosted) via python-gitlab.

Enables AI clients to assess infrastructure-as-code deployment risk, generate incident response runbooks, review CI/CD delivery readiness, and calculate SLO error budgets through structured advisory tools. Runs locally over stdio without cloud credentials or external API calls, returning guidance for platform work, pull request review, and production readiness checks.

A Model Context Protocol server that enables AI assistants to interact with Azure DevOps services, allowing users to query work items with plans to support creating/updating items, managing pipelines, handling pull requests, and administering sprints and branch policies.

Enables AI agents to deploy, manage, and configure web applications on sota.io, including project creation, deployment, environment variables, custom domains, and rollbacks.

Enables deployment and management of applications on the Citizen platform from git repositories or local files. It allows AI assistants to monitor deployment logs, handle authentication, and automatically fix build errors using intelligent error analysis.

Enables coding agents to upload local .apk or .ipa builds and receive tester install links without leaving the editor.

Publishes what an AI made — a page, a markdown or PDF doc, or a whole site — to a live HTTPS link. Runs locally over stdio from the @drop2run/mcp npm package, or hosted at https://mcp.dropto.run/mcp for chats that connect by URL.

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

Baron gives an AI coding agent one normalized contract for work orchestration: create and transition issues, cut branches, open and merge pull requests, and read CI and deployment status across Azure DevOps, GitHub and Slack.

Provides read-only access to Azure DevOps using your browser session, no PAT required. Enables browsing projects, repos, work items, pull requests, and feeds through MCP tools.

Enables AI assistants to interact with TrafficMorph for load-testing and CI-failure triage, including run management, profile lifecycle, and domain verification through natural language.

Local-only GitHub Actions and CI maintenance scanner for AI-built apps. Exposes scan, explanation, and fix-planning tools to MCP clients; modifies nothing and makes no outbound requests by default.

Enables AI assistants to manage website deployments over SFTP/FTPS by listing sites, testing connections, comparing files, previewing changes with approval tokens, creating SHA-256 verified backups, and executing authorized uploads.

Enables analyzing Salesforce deployment logs, validating metadata manifests, assessing permission risks, and generating remediation plans through deterministic, local-only rules.

Post-quantum readiness for AI coding agents: scans code for quantum-vulnerable cryptography (RSA/ECDH/ECDSA/DH) and returns NIST ML-KEM/ML-DSA/SLH-DSA (and hybrid) migration guidance, with fix verification and dependency checks. Content-based, advisory tools only; runs local (npx @quantakrypto/mcp) or as a hosted OAuth endpoint.

Enables AI assistants to query and manage Azure DevOps projects, boards, work items, repos, pull requests, and pipelines while enforcing governance boundaries such as access modes, project scoping, protected projects, delete gating, and typed confirmations.

Enables building structured release evidence by comparing two Git refs and correlating commits, merged pull requests, linked issues, labels, changed files, and contributors.

MCP server for GitFlic, the Russian Git hosting platform, enabling AI agents to manage projects, issues, merge requests, files, and more via 66 tools covering 13 API categories.

MCP server for Bitbucket Cloud that enables reviewing, managing, and merging pull requests, assigning reviewers by name, reading files at a ref, and inspecting pipeline status from any MCP client.

MCP server for deploying projects to multiple cloud platforms (Vercel, Railway, Neon, MongoDB Atlas, Docker) and running local dev servers, with orchestration for full-stack deployments.