"Free and open-source GPS without an API" 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.

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 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 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.

Enables AI agents to debug and repair historical Solaris/SPARC systems by providing an out-of-band control plane with guest DTrace, QEMU monitor access, SPARC-aware GDB, host eBPF/perf tracing, and an immutable evidence ledger for cross-layer hypothesis testing.

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.

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.

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

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

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 a hand-written MCP server integrated with a LangGraph agent to benchmark multiple agent topologies and measure their failure rates.

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.

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.

Provides a deterministic failure-decision API for MCP clients, returning one of six actions (RETRY_NOW, WAIT, REPAIR_REQUEST, VERIFY_FIRST, ESCALATE, ABORT) based on failure context to guide safe next steps.