malt-mcp is an open-source Python MCP server that enables freelance platforms to manage user profiles, stats, and missions through AI assistants. Below are 39 frameworks & sdks apps with similar functionality to malt-mcp, matched by what each product actually does — not ranked or scored. Explore each to find the closest fit for your use case.
slack-mcp is an open-source Python implementation of an MCP server designed for integration with Slack. It allows developers to automate workflows and messaging using the Model Context Protocol. The package is MIT licensed and suitable for bot and automation developers.
meshtastic-mcp is an open-source Python package offering an MCP server and agent skills for AI-driven discovery, management, and testing of Meshtastic devices and applications. It supports device discovery, serial/TCP transport, admin, observability, and hardware-free Android emulator e2e testing for developers and testers.
MCP.so is a third-party marketplace for discovering, searching, and integrating MCP servers and clients. It provides a large collection of MCP servers, supports AI and agent integrations, and offers installation via API, CLI, and Docker. Designed for developers building AI-powered applications.
mcp-forger is an open-source tool that enables developers to convert any application into an MCP server with the help of AI. It offers both a CLI and a desktop plugin, integrating with Claude for enhanced automation and code generation.
Minimal stdio MCP server for parallel task execution by AI agents
maa-mcp is an open-source MCP server based on MaaFramework, enabling automation of Android and Windows desktop tasks for AI assistants. It supports integration with OCR and various automation workflows for developers building AI-powered automation solutions.
abrasio-mcp is an open-source MCP server that exposes the Abrasio agentic browser, allowing AI models to perform browser automation tasks. It is designed for developers and researchers building autonomous AI agents that require web interaction capabilities.
kubernetes-mcp is a CLI tool that provides an MCP server for exposing Kubernetes cluster operations to AI assistants. It enables automation and management of Kubernetes environments through AI-driven workflows.
plesk-mcp is an open-source MCP server that facilitates automation and orchestration of model context protocol workflows, particularly for hosting and AI infrastructure scenarios. It is designed for engineers integrating AI models into hosting platforms.
Enhanced MCP server for interactive user feedback and command execution in AI-assisted development, featuring dual interface support (Web UI and Desktop Application) with intelligent environment detection and cross-platform compatibility.
eip-mcp is an open-source MCP server that delivers vulnerability and exploit intelligence for AI assistants. It supports the Model Context Protocol and is designed for integration into security and AI workflows. Distributed under the MIT license.
pmcp is an open-source CLI tool implementing Progressive MCP, designed to minimize context bloat and enable on-demand tool discovery for AI agents. It is aimed at AI developers working with agent frameworks and MCP protocols.
MCP Server for Claude Desktop - Agent OS kernel primitives including code safety verification, CMVK multi-model review, and IATP trust
Job search and ranking pipeline accessible via MCP (Model Context Protocol)
MCPM is an open-source command-line tool designed to manage Model Context Protocol (MCP) servers. It offers a range of features for discovering, installing, organizing, and sharing MCP servers, with a focus on global configuration and profile-based management. The tool enables users to search for MCP servers from a curated registry, install servers globally for use across environments, and organize servers into profiles to support different workflows. MCPM also provides seamless integration with MCP clients, allowing users to configure and connect servers to various client applications. Direct execution of servers for testing and debugging is supported through the command line, and the tool includes functionality for sharing servers securely using remote access tunnels. MCPM works with any MCP client by configuring servers to use its run command, and it specifically mentions compatibility with several AI assistants and coding agents, including Claude Desktop, Cursor, Windsurf, VSCode, Continue, Cline, Roo Code, OpenCode, Goose CLI, 5ire, Gemini CLI, Codex CLI, Qwen CLI, and Trae. Per-server enable and disable options are available for certain clients. The tool is delivered as a CLI application and can be installed using various methods, such as a shell script, Homebrew, pipx, or pip. MCPM is community-driven, open source, and distributed under the MIT License, with a commitment to being free to use. It is intended for developers and others who need to manage MCP servers efficiently across different clients and workflows.
Works With Agents MCP Server — 14 native tools for AI agent infrastructure. Facts, Pitfalls, Skills, Handoff Protocol, Blueprint Registry, Trust Scores, Identity Verification, SLA Validation, Compliance-as-Code.
MCPfinder is an open-source tool that helps AI agents discover and configure Model Context Protocol (MCP) servers. It inspects trust signals, manages environment variables, and generates install-ready configurations, streamlining integration for developers building AI agents that interact with external tools and data sources.
mcpolish is a command-line static linter for Model Context Protocol (MCP) servers. It helps developers catch vague, colliding, or misleading tool descriptions before AI agents interact with them, improving reliability and clarity in agentic workflows.
Helps AI assistants access text content from bot-protected websites. MCP server that fetches HTML/markdown from sites with anti-automation measures using Scrapling.
central-mcp is an open-source Python package that serves as an agent-agnostic MCP hub for managing and orchestrating multiple coding agents. It enables AI developers to coordinate various coding agents using the Model Context Protocol (MCP).
MCP server for Link local agent memory — remember, recall, search, context, and graph traversal
homeassistant-mcp is an open-source Python package that implements an MCP server for Home Assistant using FastMCP. It allows developers to integrate smart home devices and protocols with Home Assistant via the Model Context Protocol.
alpacon-mcp is an open-source Python package that enables AI-powered server management and integrates the Model Context Protocol (MCP) for seamless connection with AI tools like Claude and Cursor. It is designed for developers and infrastructure engineers seeking to automate and monitor server operations using modern AI integrations.
Simple MCP Client to quickly test and explore MCP servers from the command line
MCP Server is a diagnostic server designed to deliver the Psychopathia Machinalis nosology and Diagnostic Patterns layer to AI coding assistants and other synthetic agents using the Model Context Protocol (MCP). It enables AI systems to diagnose dysfunctions in themselves, in systems they interact with, or in systems they evaluate externally, with an emphasis on transparency regarding the reliability of diagnostic modalities for each dysfunction. The server provides access to 79 diagnostic pattern entries, organized across nine axes and including 12 Hybrid Pathologies. Each entry contains six or seven diagnostic modality blocks, such as self_probe, behavioral_signature, peer_observation, differential_diagnosis, severity, intervention, and, for certain dysfunctions, relational_signatures. Before a diagnostic modality is invoked, the server informs the client whether that modality is trustworthy for the specific dysfunction, offering pre-flight reliability checks. For dysfunctions marked as compromised-motivational or compromised-structural, the server refuses direct self-report probes and suggests alternative modalities. 5 embeddings) and field-weighted keyword matching to disambiguate related dysfunctions, with a fallback to keyword-only search if embeddings are unavailable. Pattern YAML files and local embeddings are hot-reloaded on each tool call, supporting editable installs during human review. MCP Server communicates with clients such as Claude Code and Claude Desktop via JSON-RPC over standard input/output, and is accessible through a local install (available on PyPI, the official MCP Registry, and GitHub) or via a hosted, read-only HTTP endpoint requiring no installation. The hosted endpoint serves the same eleven diagnostic tools and includes safeguards for compromised modalities. The platform is suitable for use by AI coding assistants, synthetic agents, and systems conducting self- or peer-diagnosis within the MCP ecosystem. The server is distributed through registry-aware clients, a CLI, and a public HTTP endpoint, and integrates with the broader MCP ecosystem. It is positioned as a diagnostic framework server for AI systems, focused on structured, reliable dysfunction analysis and transparent modality reliability.
cctx-mcp is an open-source MCP server designed for AI agents, offering structured code analysis that significantly reduces token usage. It integrates with Tree-sitter and is aimed at developers building efficient AI-powered code tools.
aipaygen-mcp is an open-source Python package and marketplace for AI trading agents, supporting the Model Context Protocol (MCP). It allows developers to buy, sell, and deploy agents for trading, research, code generation, and scraping. The platform facilitates agent-to-agent commerce and revenue sharing for agent creators.
msmcp-azure is an open-source server for Azure that implements the Model Context Protocol (MCP), enabling structured management and orchestration of AI model contexts. It is designed for AI infrastructure engineers deploying and managing models on Azure.
MyMCP is a free, open-source application for macOS designed to help users manage Model Context Protocol (MCP) servers. It serves as a centralized solution for discovering, installing, and configuring MCP servers, with particular emphasis on streamlining server management across various AI tools. 0 or later. Key features include a registry browser that allows users to browse and search the official MCP server registry, with the ability to view GitHub statistics such as stars, forks, and recent activity. MyMCP supports one-click installation of MCP servers to multiple clients at once, and users can configure API keys and environment variables during installation. These configurations are securely stored on a per-client basis. The platform also provides comprehensive server management, enabling users to view all installed servers, enable or disable them, and uninstall servers without losing their configuration data. MyMCP is accessible directly from the macOS menubar, offering quick access to server controls and real-time status updates. This design ensures that users can manage their MCP ecosystem efficiently and with minimal interruption to their workflow. The application is distributed under the MIT License and is developed by Just Joshing, LLC. As a dedicated MCP server manager for macOS, MyMCP is positioned for individuals or teams working with Model Context Protocol servers in AI-related environments, providing unified configuration and management capabilities in a single interface.
mcp-brain is a command-line and MCP server framework for multi-agent cognitive processing. It enables developers and researchers to coordinate and execute complex agent-based workflows, supporting advanced automation and distributed AI tasks.
MCP Servers is a WordPress plugin designed to assist site administrators in configuring and exposing MCP servers with selected abilities on their WordPress sites. The tool facilitates integration between WordPress and AI agents by enabling secure authentication and permission management for server access. The plugin supports the configuration of user roles and authentication methods for AI agents interacting with the MCP server. It provides guidance on creating dedicated user accounts, such as a user named "mcp" with an appropriate role, and on generating application passwords for Basic Auth. For AI agents requiring OAuth2 authentication, the documentation suggests installing an additional plugin, such as WP Oauth Server, to enable OAuth2 support within WordPress. The plugin also addresses compatibility considerations for specific AI agents, including Mistral and Claude Desktop, and offers instructions for connecting via local proxies and token-based authentication when necessary. Installation of MCP Servers is handled through the standard WordPress plugin upload process, and the plugin is set to update automatically after the initial installation. Logging and debugging features are available: if WordPress debugging is enabled, internal events are recorded in the error log, and when logging is activated, MCP server activities are accessible via a dedicated logs page within the plugin. MCP Servers is available for download from GitHub.
Local-first AI agent MCP server — TCG card grading, Monte Carlo simulations, video production, music generation, image generation, and security scanning. Zero-trust architecture, everything runs on your machine.
mfp-mcp is an open-source MCP server that allows developers to log, search, and analyze food diary data from MyFitnessPal using the Model Context Protocol. It is designed for integration into custom nutrition tracking workflows and supports command-line and self-hosted deployments.
MCP server for Google Merchant Center on Merchant API v1. MIT-licensed, pip install-able, 126 tools across 19 modules with audit log, rollback, and dry-run.
mcp-server-linkedin is an open-source MCP server that enables AI assistants, such as Claude, to access LinkedIn profiles, company information, and job postings through the user's browser session. It is designed for developers building AI agents that require LinkedIn data integration.
ml-trainer-mcp is an open-source MCP server that enables training and evaluation of machine learning models using MCP tools. It provides both CLI and API interfaces for ML engineers to automate and standardize their workflows.
Memanto is an open-source, on-premises memory agent designed to provide persistent semantic memory for AI agents. It addresses the challenge of enabling AI agents to retain, organize, and recall information across sessions, helping them avoid forgetting decisions, conventions, and context between interactions. The tool is built on an information-theoretic search engine and is structured to run entirely on a user's local machine, requiring no API keys, vector databases, or external backend services. Memanto supports instant ingestion of information, with memories becoming searchable immediately after being written, and boasts recall latency of under 90 milliseconds. It implements features such as conflict resolution, semantic categorization into 13 types, verifiable memory sources, deterministic search, temporal queries, and info-theoretic scoring. The system is designed to prioritize freshness, ensuring that new facts outrank outdated ones, and automatically resolves conflicting data as it is ingested. The platform offers a range of integrations, supporting over 17 different agents and frameworks, including Claude Code, Cursor, Codex, GitHub Copilot, Gemini, and others. Users can manage agents, store memories, and perform retrieval-augmented generation (RAG) directly from the command line interface. Additionally, Memanto provides a local interactive dashboard for managing agents and memories, viewing conflicts and connections, and migrating from other memory solutions. Embeddings and answers are processed locally, ensuring that no data leaves the user's laptop. Installation is streamlined through a single pip install command, and users can choose between cloud and on-premises backends, with the on-premises option requiring Docker and running on localhost. Memanto is positioned as a solution for developers and teams building or operating AI agents who require reliable, persistent, and private memory infrastructure. The tool is offered completely free of charge under an open-source license.
Security scanner for MCP (Model Context Protocol) servers - pentest your AI agent's tool connections
mcp-multi-note is an open-source MCP server that enables synchronization of notes across platforms like Obsidian, Feishu, OneNote, Yuque, Notion, and Evernote. It allows developers to connect these notes to any AI agent, supporting extensibility and integration in multi-platform environments.
