"How to take notes on my local machine and on Notion" matching MCP servers:

A minimal starter template for building Model Context Protocol (MCP) servers using TypeScript and FastMCP, including an example weather tool for demonstration.

MCP server for Azure DevOps Server 2022 (on-premises) that enables AI assistants to interact with work items, repositories, builds, and sprints through 29 tools.

MCP server wrapping the full VitoDeploy REST API to manage projects, servers, sites, databases, services, workers, SSL, DNS, and more through any MCP-compatible agent, with 108 tools covering every endpoint.

Combines GitHub releases from multiple repositories into a single product release note, with context sources for LLM synthesis.

An MCP server that adds engineering discipline to AI-assisted development, enforcing evidence-gated TDD, security review, backup strategy, and deployment generation to turn AI-generated code into production-ready software.

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.

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.

A TypeScript starter template for building Model Context Protocol (MCP) servers with built-in support for tools, testing, and CI/CD pipelines. It provides a complete development environment for creating custom AI assistant integrations for tools like Claude, Copilot, and Cursor.

A multi-language testing automation server that enables AI assistants to discover, plan, and execute tests across six major programming languages. It provides comprehensive tools for repository scanning, automated test execution, and detailed coverage reporting.

A stdio MCP server that exposes Copado Release Data Template version control to AI coding agents, offering read-only inspection tools (status, history, diff, lint, plan, verify) plus git-only snapshots and two-step preview/apply tools for editing and restoring templates. Every organization write requires a single-use preview ID and explicit confirmation, and re-checks the live template so concurrent changes are never silently overwritten.

Enables inspecting local Git repositories and automating delivery tasks such as status checks, diffs, commits, pull requests, and deployments using git and GitHub CLI.

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.

Connects AI tools to GitHub and local git repositories, enabling natural language management of issues, PRs, code analysis, and workflows.

A production-ready template for building Model Context Protocol servers in Python, featuring example tools, structured logging, and multiple transport protocols.

AI code review against your team's own rules from your repository, before the pull request: two tools, review_changes and get_team_rules. Closed-source binary distributed via GitHub Releases; published in the official MCP Registry as dev.reviewgate/reviewgate.

Enables a coding agent to answer "is this iOS release ready?" by running read-only App Store Connect checks: build processing, App Review state, a 13-point submission preflight, release-notes policy linting, and App Store Server Notification reconciliation. The lone write capability is a dry-run-first, seven-gate submission tool that always requires explicit confirmation.

Generates a daily standup note from GitLab merge request or GitHub pull request state: what is ready to merge, what is blocked, what is stale, and what is waiting on your review. When CI is red it opens the failed job's log and reports the error lines, so the note says why the pipeline failed rather than just that it did.

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.

Provides disposable email inboxes for AI agents to automatically receive and extract OTPs and magic links, enabling seamless email verification during autonomous workflows.

Deploy, run and manage apps on your own self-hosted AppCrane from any MCP client. 62 tools: create an app, push code, deploy to sandbox, check health and logs, provision a managed Postgres, MariaDB, MongoDB or Redis, and promote to production after review. Your instance, your SSO, your data. Repo: https://github.com/gitayg/appcrane-mcp · npm: appcrane-mcp · Site: https://appcrane.dev

Deploys and manages projects on Swigs Cloud from any MCP client, turning folders or git repositories into live HTTPS sites in about two minutes.

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

Compacts noisy test, build, and cloud-log output before an AI agent reads it — dedupes repeats, collapses stack frames, folds Playwright retries, and renders CloudWatch/GCP JSON logs down to the signal. Typically 80–95% fewer tokens on failures. Tool: compact_output. Run: npx -y logslim logslim-mcp

MCP server that audits npm dependencies against the live registry, providing per-dependency reports on versions behind, deprecation, and license.

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.

The network-change verifier for AI agents: validate a BGP or routing change in a real containerlab lab before it reaches production, and get a pass, fail or inconclusive verdict with evidence. Runs on FRR, Nokia SR Linux, SONiC and Arista cEOS.

Runs a project's Playwright or CTRF test suite and returns a redacted failure packet (failing test, file and line, console errors, failed requests, rerun command) so a coding agent can fix and rerun. Also reports whether a commit has a signed, passing test receipt on GitHub.

Uptime monitoring your AI agent can set up: create HTTP, SSL, ping, TCP and DNS monitors checked from multiple regions, run checks on demand, read and acknowledge incidents, manage cron heartbeats, maintenance windows and status page updates.