ucm-mcp is an open-source MCP server designed for AI-agent code navigation and mapping. It supports AST parsing and integrates with AI agents to facilitate code analysis and automation. Below are 38 frameworks & sdks apps with similar functionality to ucm-mcp, matched by what each product actually does — not ranked or scored. Explore each to find the closest fit for your use case.
contextl-mcp is an open-source MCP server designed for AI coding agents. It provides repository intelligence, code search, and integrates with the Model Context Protocol, allowing developers to build advanced AI-powered code tools. Distributed under the MIT license.
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 The system is designed to prioritize freshness, ensuring that new facts outrank outdated ones, and automatically resolves conflicting data as it is ingested.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.
MCP Server for Claude Desktop - Agent OS kernel primitives including code safety verification, CMVK multi-model review, and IATP trust
itu-mcp is an open-source Model Context Protocol (MCP) server that connects İTÜ Ninova (LMS) and OBS student portals to AI tools like Claude and Codex. It provides APIs for accessing courses, grades, deadlines, and transcripts, enabling developers to build educational integrations and AI-powered assistants.
Unity MCP Server is an open-source server that bridges AI agents and the Unity Editor, allowing automated scene manipulation, physics simulation, and multi-instance management. It is designed for AI and game developers seeking to integrate autonomous agents with Unity workflows.
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.
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.
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.
codebase-agent-mcp is an autonomous agent designed to provide token-efficient code analysis, documentation retrieval, and implementation guidance for large library repositories. It leverages OpenAI-compatible LLMs and supports integration via MCP and API, making it suitable for developers working with extensive codebases.
agentdrive-mcp is an open-source MCP server designed for use with Claude Code, enabling agent-driven automation and integration via API. It is suitable for developers building automation systems and agent frameworks.
projectmind-mcp is an open-source local MCP server that equips AI coding assistants with persistent memory, hybrid code search, AI-generated annotations, and an AST symbol graph. It runs entirely locally, requiring no API keys, and is aimed at developers seeking privacy and advanced code intelligence features.
yuuno-mcp is a command-line MCP server that allows developers to build and run AI media canvases, integrating with Claude and Cursor. It is designed for AI developers working with video and media generation workflows, supporting the Model Context Protocol for advanced automation.
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.
kira-mcp is an open-source local MCP server for AI agents, providing YOLO-based UI-element detection, OCR, and full keyboard, mouse, and clipboard automation. It is designed for developers building autonomous agents that interact with desktop environments.
miosa-mcp is an open-source MCP server that exposes MIOSA computer-use tools for integration with Claude Code and other agent frameworks. It provides a standardized API for agent developers to enable automation and computer control capabilities in their AI systems.
ai-firewall-mcp is an open-source MCP server component for AI Firewall, providing a security layer for large language models. It helps AI security engineers protect LLM deployments from prompt injection and jailbreak attacks using a multi-agent approach.
wm-mcp is an open-source CLI tool that lets users run a world model locally and expose it as an MCP server, enabling LLM agents to call it as a tool. It supports video models and is designed for AI researchers and developers.
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.
mcp-cn-commerce is an open-source Python MCP server that enables AI agents to read and process business data from Chinese e-commerce platforms like Douyin Shop, JD.com, and Taobao. It is designed for developers building agent-based commerce solutions.
codebase-memory-mcp is an open-source, fast code intelligence engine designed for AI coding agents. Distributed as a single static binary MCP server, it enables local analysis of codebases for agent frameworks and research. It is suitable for developers building AI-powered code tools and workflows.
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.
agent-brain-ag-mcp is an open-source Model Context Protocol (MCP) server that exposes Agent Brain as MCP tools, resources, and prompts. It enables developers to integrate Agent Brain capabilities into agent-based applications, supporting RAG workflows and Claude integration. Ideal for AI developers seeking extensible agent frameworks.
iris-security-mcp is an open-source Python package that implements an MCP server, allowing organizations to connect Claude to AI agent governance and compliance systems. It supports secure agent management and integrates with existing compliance workflows. Designed for developers and teams building or managing AI agents.
MCP Manager is a Windows application that centralizes the configuration and management of Model Context Protocol (MCP) servers for AI development tools. It streamlines syncing, testing, and backing up server configs for developers using multiple AI coding assistants and IDEs.
agent-harnesses-mcp is an open-source MCP server that provides recommendations, search, and head-to-head decision guides for over 100 agent harnesses. It is designed for AI developers and researchers working with LLM-based agents, offering weekly rescoring and structured comparison tools.
personal-memory-mcp is an open-source CLI tool that runs a local MCP server to extract and store personal memory from AI chat histories. It is intended for users and developers who want to manage their AI interaction data locally and securely.
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).
smartoption-mcp is a developer infrastructure package that exposes smartoption-ai APIs as MCP servers and command-line tools. It enables AI agents and users to automate trading workflows, manage strategies, and access trading signals. The package includes customer and admin CLIs and supports self-hosted deployment.
The cendor-mcp server provides a read-only implementation of the Model Context Protocol (MCP) for connecting agent-mode AI coding assistants to Cendor's live documentation and API call-shapes. It is designed to support assistants such as Claude Code, Cursor, GitHub Copilot (in agent mode), and Windsurf Cascade by supplying them with accurate, up-to-date information about Cendor libraries, ensuring that generated code aligns with the current published package versions on PyPI and npm. The tool operates in a pull-based manner: the assistant sends queries to the server, which responds with information, but no user code or data is sent to the server, and the server never initiates communication with the client. cendor-mcp offers several specific functions to AI assistants. These include full-text search over Cendor documentation, retrieval of complete documentation pages in markdown, access to the correct API call-shapes for specific symbols (with both correct and common incorrect forms), provision of runnable, CI-typechecked code snippets for tasks, and listing of cookbook recipes that can be copied and run offline. Each response is built from the authoritative documentation source and is stamped with the current published package versions, preventing discrepancies between documentation and available packages. The server can be accessed remotely via a hosted endpoint (https://mcp.cendor.ai) for zero-install integration or run locally for offline use, with all documentation bundled and no network communication required. Local operation is supported via Node (npx) or Python (uvx), allowing flexibility for different development environments. The tool is open source and distributed under the Apache-2.0 license. It is intended as optional developer tooling and is not required by Cendor libraries at runtime. cendor-mcp is particularly aimed at developers integrating or building AI coding assistants that need access to live, accurate documentation and call-shape information for Cendor libraries. Its design emphasizes privacy, as no codebase data leaves the user's machine in local mode, and it operates strictly in agent mode, not supporting inline autocomplete scenarios. The project is maintained by Raghav Mishra (PowerAI Labs) and is available "as is" under the stated license.
agent-commerce-protocol-mcp is an open-source CLI tool that bridges payment protocols like Stripe ACP, Google AP2, and Coinbase x402 for agent payments in AI systems. It enables seamless agent-based commerce and pay-per-call flows for developers.
hyperclast-mcp is an open-source MCP server that lets developers enable AI assistants to read and write user pages. It provides a standardized interface for integrating AI-driven automation into applications, supporting extensibility and self-hosted deployments.
Agent MCP Studio is a free, browser-based platform for building, running, and exporting Model Context Protocol (MCP) tools and AI agents. It enables developers to specify tools in natural language, generate code with LLMs, and run agents entirely in the browser or via Docker. Designed for AI developers and researchers.
mcp-remlezrd is an open-source server implementing the Model Context Protocol (MCP) for AI agents. It allows developers to manage, exchange, and serve context for AI workflows, supporting integration with agent frameworks and research projects.
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.
Model Context Protocol (MCP) is an open-source framework that provides a standardized way for AI models to communicate with external tools and services. It enables developers to build AI applications that integrate with multiple LLM providers using a unified protocol, simplifying tool integration and interoperability.
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.
ASMHunter is a continuous attack surface monitoring (ASM) platform designed specifically for bug bounty hunters and security professionals. The tool addresses the challenges of tracking internet-facing assets within bug bounty scopes, such as subdomains, ports, endpoints, and HTTP services, by providing real-time monitoring and attribution for every change detected. Unlike traditional ASM tools that simply report asset changes, ASMHunter links each finding to the specific scan, asset, and timestamp that surfaced it, enabling users to trace bounties directly back to the monitoring event that earned them. The platform offers a chronological diff feed that highlights new subdomains, ports, HTTP fingerprints, URLs, and findings as they appear. Scheduled sweeps run automatically without requiring users to maintain their own infrastructure, cron jobs, or deduplication scripts. ASMHunter is scope-aware, ensuring all monitoring stays within authorized bug bounty programs. Users can receive alerts via Telegram and email, and findings are enriched with metadata for scan attribution. The tool also provides a public API, allowing integration with custom scripts, Caido, or AI agents, making it adaptable to various workflows. ASMHunter features a native Model Context Protocol (MCP) server, enabling users to drive reconnaissance, hunt sessions, and reporting directly from AI clients such as Claude or Cursor. This integration allows for natural language interaction, letting users start sessions, set goals, log findings, and draft reports without leaving their editor or chat environment. The platform supports goal-driven hunting, keeping AI agents focused on specific objectives throughout a session. Pricing is structured for individual hunters and teams, with a free tier offering weekly sweeps for up to three targets. Paid plans include Hunter, Pro, and Legend, which scale in sweep frequency and target count, and add features such as deeper discovery modules for XSS, SQLi, and JS secret extraction. Team and enterprise options are available for organizations needing shared dashboards, SSO, or custom workflows. ASMHunter is delivered as a managed service and does not require self-hosting or manual infrastructure maintenance.
rutherford-mcp-server is an open-source MCP server designed to orchestrate a crew of agentic coding agents using the Agent Client Protocol (ACP). It enables developers to coordinate multiple code-generating agents, manage consensus, and automate complex coding workflows. Ideal for AI developers building agentic systems.
