"Coolify - An Open-source Self-hosting Platform" matching MCP servers:

Enables an AI agent to reverse-engineer a compiled program with Ghidra — inspecting decompiled code, instructions, callers, memory bytes, and strings — without any source code. Every reply is labelled as fact, computed, or guess, and each claim traces back to hash-checked saved evidence.

Enables researching, verifying, comparing, and composing open-source AI projects with transparent evidence and uncertainty boundaries through read-only tools.

Enables LLMs to manage a self-hosted Coolify instance, including applications, databases, services, servers, projects, deployments, environment variables, tags, teams, private keys, and S3 backup storages via the Coolify REST API.

Enables managing a self-hosted Coolify instance from Claude Code or any MCP client over stdio, using your own API token. Exposes tools to list and inspect servers, projects, applications, services, databases, deployments and teams, plus control (start/stop/restart), deploy, fetch logs, read and edit environment variables, and make raw API calls.

Local, zero-token event triggers for Claude Code, Codex, OpenCode and ZCode: when CI fails, a training run finishes, a service goes down or NVDA crosses your price, your agent wakes up in your conversation—even if closed.

Enables users to plan and create applications on a Coolify instance from container images, Git repositories, inline Dockerfiles, and repository-based Docker Compose, while validating ownership and returning deployment webhooks.

Exposes structured Microsoft Dynamics 365 Business Central source code (versions 23-29, 47 localizations) to AI agents via MCP, enabling fast lookups, searches, and code analysis.

Lets an AI assistant read and write business records in plain language, including looking up people, creating and updating tasks, logging time, and pulling utilization reports through a synthetic ops platform or an optional ClickUp adapter.

Privacy-first MCP server for querying personal health and finance data with AI. Built with Python, FastMCP, and SQLite. Local-first and open source.

MCP server for Argo CD and Vault that allows authenticated users to run CLI commands via GitLab SSO, with confirmation for dangerous operations and secret redaction from model context.

Analyzes codebases for cross-platform compatibility issues, detecting platform-specific APIs, file path problems, line ending inconsistencies, and shell command incompatibilities across Windows, macOS, and Linux.

MCP server for searching, browsing, and analyzing decompiled Minecraft source code locally. Supports symbol lookup, text search, reference lookup, and lightweight RAG.

Enables revision-bound source audits with exact article fingerprinting, claim-to-source mapping, quotation verification, and immutable JSON evidence reports for prepublication review.

MCP server for Claude Code self-management, enabling hot restart and context compaction commands.

Analyzes source code dependencies across multiple programming languages in the specified directory to identify file relationships, assisting in dependency management and project structure understanding.

Enables IDE plugins to authenticate and communicate with the YAAIF platform via MCP, bridging Cursor, VS Code, IntelliJ, Claude Code, Codex, and OpenCode.

MCP server for operating and testing Android devices with AI agents. Provides observation and action tools for interactive control and spreadsheet-driven test runs.

Searches job listings from Taiwanese job boards (104 and Yourator) and returns normalized results.

An MCP server that enables AI assistants to navigate, search, and analyze local Keycloak source code to support developer customizations like SPIs and authenticators. It provides tools for searching classes, generating boilerplate code, detecting breaking changes between versions, and tracing dependencies.

MCP server that builds a deterministic, source-traceable knowledge index of any codebase, enabling glossary lookup, code graphs, and exact-token search with every fact linked to its source file and line.

Multi-datasource MCP server that connects AI assistants to 6 database types (MySQL, PostgreSQL, ClickHouse, MongoDB, SQLite, Huawei DWS) with dynamic configuration, encrypted credential storage, and schema discovery.

Enables a local, read-only search over user-provided tabletop campaign source cards and module directories, routing queries to ranked hits across Markdown, JSON, and YAML text files while excluding core rulebook and SRD content by default. Returns file-and-line pointers with small context windows, plus explicit private-source opt-in, so a game master can locate and open the exact passage in their own library.

Enables running a local multi-agent pipeline that turns a product idea into a validated technical spec, with tools to generate, deterministically check, LLM-review, and retrieve stored runs.

Enables AI agents to learn from their work by recording tasks, extracting patterns, detecting mistakes, and proactively surfacing insights, all using the agent's own model through a cooperative intelligence pattern.

Read-only MCP server for Discord that lists guilds, channels, and reads or searches messages using a self-bot account via discord.py-self.

Indexes Unreal Engine source code into a local database, providing AI coding assistants with deep structural queries like class hierarchies, call graphs, and full-text search across all engine source files.

Captures user corrections and improvements during interactions, logs them, finds recurring patterns, and prescribes preventive fixes like CLAUDE.md rules, skills, scripts, or MCP tools to avoid repeating mistakes.

A self-updating MCP system that analyzes design and code inputs with an LLM, refines them through conversation, and crystallizes approved patterns into a local skill library for MCP agents.

Provides AI tools with on-demand, precise access to real AOSP framework and AndroidX source code, so they can search classes, extract exact method bodies with Javadoc, inspect inheritance hierarchies, and trace definitions and references across the entire tree. Sources are synced locally for fast, offline lookups, with optional language-server features for cross-file navigation.

Demonstrates agent-native platform onboarding with human-in-the-loop API key provisioning, plus live usage and rate-limit queries via Anthropic Admin APIs.

Enables AI agents to manage Splitwise expenses through natural language, including reading balances, splitting costs, and handling authentication and rate limits automatically.

An MCP server that provides weather forecasts and current conditions for any city via the free Open-Meteo API, with no API key or account required.

Delegate a Cursor task to a real, unattended background OpenCode agent — cheaper model, isolated history — through five small MCP tools.

MCP server wrapping a mock internal ops platform (FastAPI + SQLite) so Claude Code can read and write employee, project, task, and time data through natural language.

Local-first memory layer for AI coding agents — Markdown as source of truth, MCP server + CLI, human-reviewed capture, team knowledge via git PRs

Open Kioku is the local-first code intelligence and evidence layer for AI coding agents (Claude, Cursor, Codex, Zed, and other MCP clients). Instead of letting agents blindly crawl files, guess blast radius, or read the entire repository repeatedly, Open Kioku gives them a precise, pre-indexed code index to build evidence-backed plans before they edit, and verify boundary limits after they edit.

Read-only MCP server that exposes Kubernetes platform state (tenants, pods, SLOs, ArgoCD applications, chaos schedules, and catalog services) to AI agents, enabling natural language queries about cluster health and configuration.

Enables AI assistants to read and create geometry in an open Cadwork 3D document via a local bridge, with queued sequential execution, write approvals, undo support, and a live dashboard for monitoring activity.

Enables reproducible evaluation of AI agents on multi-source evidence investigation tasks, providing Docker-based scenarios, MCP tools, and automated scoring for payout reconciliation, performance-claim verification, and incident reconstruction.

Enables MCP clients to control the local Open Science research application, including creating projects, starting or continuing research sessions, inspecting progress and plans, canceling runs, and reading generated artifacts.