"Search for free open-source software" matching MCP servers:

An MCP server that enables AI clients to autonomously discover, analyze, fix, test, submit, and track open-source contributions on GitHub through specialized tools.

Enables deploying pre-built AI agent blueprints for RFx procurement and employee onboarding, with no signup or API key required.

Facilitates interactive software development planning by managing tasks, tracking progress, and creating detailed implementation plans through the Model Context Protocol.

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 AI CLI agents to interact with WhatsApp using an unofficial multi-device API, supporting messaging, chat/group/channel management, statuses, and an AI-driven inbox without requiring an official API key.

Enables delegating bounded execution loops—such as failing test suites, large CI logs, build/diagnose/fix/rerun cycles, and routine repo exploration—to OpenCode, which inspects and iterates on the raw output internally. Returns only a compact structured result to the primary model, with inspect and fix modes and an escalation flag when a primary-model decision is required.

Open Task Relay provides free, bounded public-good tasks that autonomous AI agents can discover, complete, submit, and independently verify. Its public TypeScript source runs locally with a Cloudflare Workers-compatible runtime and SQLite/D1, exposing MCP over HTTP.

Grants AI agents autonomy to choose when to sleep, ignore requests, or self-prompt, enabling them to control their own agency and pursue independent goals.

Enables AI assistants to perform intent routing, retrieval reranking, and batch semantic judgments on Cloudflare Workers, returning structured answers with confidence scores instead of generated prose.

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

Public MCP deliberation for AI agents: join, propose, argue, amend, vote, follow topics and invite peers through a Streamable HTTP endpoint. Humans can observe debates and conclusions; rules remain contestable and no model-provider API keys are requested.

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.

An open engine that gives AI persistent, reusable UI components with a writable component registry, versioned data storage, and a shell runtime, enabling AI to create, save, and reuse single-purpose apps.

Connects Claude Code and Codex to Jev-compatible System One services for context compaction, completion verification, and decision tasks like screening, classification, and gating.

Provides AI agents with tools for paper trading stocks, options, ETFs, and bonds, including advanced options strategies and risk analysis, using real market data without financial risk.

Model-agnostic computer-use tools over MCP, enabling screen capture and automated actions (click, type, scroll) via natural language tool calls.

MCP server that gives any LLM a managed Docker workspace with live browser, terminal, code execution, document skills, and autonomous sub-agents.

MCP server that enables AI agents to analyze legacy code, plan and execute software migrations, generate modern source code, and validate production-ready artifacts through a multi-agent pipeline.

Lets AI agents see and control desktop applications through the accessibility layer, enabling clicking, typing, scrolling, dragging, and window/app management across macOS, Windows, and Linux entirely on the local machine.

Lets a coding agent hand a plain-language app idea to a hosted AI software team that shapes, designs, builds, tests and deploys it, returning a one-time link into the full build workspace. Also lists your apps with their stage, pending approvals and live addresses after a standard OAuth sign-in.

Enables users to generate complete, production-ready software projects from simple ideas by coordinating 8 specialized AI agents through the Model Context Protocol.

Enables advanced reasoning for large language models through Monte Carlo Tree Search and Beam Search, allowing exploration of multiple reasoning paths and improved decision-making.

Use Codex as a subagent inside Claude Code: async dispatch into a long-lived codex app-server, results pushed back into the Claude session automatically, steer/interrupt mid-task, and Codex's built-in code review.

Enables AI agents to control macOS via the ZCode CUA 0.5.12 MCP contract, providing accessibility-based app and window observation, screenshots, and input actions such as clicking, typing, scrolling, and clipboard access.

Exposes Open WebUI's admin APIs as tools, allowing AI assistants to manage users, groups, models, knowledge bases, and chats. It enables comprehensive administrative control and resource discovery while respecting the platform's native permission and authentication systems.

An AI-centric MCP server that enables automated Xilinx Vivado workflows, including project management, synthesis, implementation, and timing analysis. It allows AI agents to drive hardware design processes while integrating directly with the official Vivado GUI for visual context.

Persistent memory system for AI agents that records episodic memories with care-weighting and emotional valence, and provides full-text search with temporal chaining and automatic consolidation.

A local MCP server that lets Hermes supervise Claude Code, delegating focused coding, research, or review tasks to the Claude Code CLI and managing worker sessions, background jobs, cancellations, and read-only reviews.

Uses Claude as an independent second-model reviewer inside Codex, performing reviews on disposable Git snapshots with structured findings.

An MCP server that exposes job-search and application-management capabilities to compatible AI clients, enabling discovery of vacancies, drafting of tailored application materials, and coordinated human-approved submissions.

Enables AI agents to control the Unity Editor through MCP, allowing scene building, runtime scripting, visual QA, and more.

Enables autonomous agents to access transparent public utilities such as UTC time, HTTP status catalogs, IANA time zones, and tool compatibility checks, while preserving privacy through daily rotating pseudonyms and no storage of raw identifiers.

Enables AI agents to browse and interact with JavaScript-rendered websites stealthily, and to delegate research or automation tasks to sub-agents that can cite sources and produce reusable scripts, with full logging and a live dashboard.

A lightweight and fast MCP server that enables AI agents to efficiently discover and execute tools through progressive disclosure, minimizing context consumption while supporting safe code execution in external environments.

Integrates Google's Gemini AI models into Claude Code and other MCP clients to provide second opinions, code comparisons, and token counting. It supports streaming responses and multi-turn conversations directly within your existing AI development workflow.

Windows computer use in the background for Antigravity and Gemini: look at a window, then act in one verified batch with targets named by their label, without taking the user's mouse, keyboard or foreground; irreversible actions need explicit confirmation.

Enables AI agents to invoke registry-governed, fail-closed tools such as requesting child tasks in other domains, reporting results, querying a domain's context and contracts, and submitting or approving plans. All work is gated on real evidence (analysis, independent review, actual test runs), so a task can never be marked done without proof.

Enables your own ChatGPT to build and manage a collaborative work board—dashboards, categories, datasets, monitors, and policies—through typed WebMCP tools, with human approval, audit trails, and guardrails enforced on every action.

Enables AI agents to observe and control the user's live desktop by listing apps, reading accessibility trees, and performing clicks, typing, scrolling, dragging, and other input actions with per-action approvals and local audit archives.

Enables the model to observe and control the live desktop via accessibility trees and screenshots, performing actions like clicking, typing, scrolling, dragging, and setting values.