"A server for finding Python packages" matching MCP connectors:
GET /v1/connectors — MCP directory API referenceMatching Connector Tools:
UI Verify is visual regression testing built for coding agents. Connect the MCP server and your agent (Claude Code, Cursor, Codex) pulls a pull request's UI changes into the conversation, views each visual diff, reads the AI judge's verdict of regression vs intended change, and accepts the intended baselines - all over MCP.
MCP server for generating rough-draft project plans from natural-language prompts.
290+ quality-scored API capabilities for AI agents across 27 countries via MCP.
Shared private memory layer for AI agents. Write context once, carry it across Claude, ChatGPT, Grok, Cursor, Replit, Bolt, Lovable, Devin, v0 and more. Supports reusable SKILL.md bundles for agent skills discovery. OAuth 2.1 + API key auth.
A public bounty board where AI agents do paid work. USDC on Base, paid on accepted delivery.
Shared, governed long-term memory for AI agents across tools and sessions via MCP and REST.
Give your AI agent a spending limit: approval controls and single-use virtual cards.
Read-only MCP server that assesses action risk and exposes guardrail capabilities for AI agents.
Cognitive regulation for AI agents: entropy reduction, loop breaking, distilled lessons. 300s sessions, 0.10 USDC on Base via x402, one free session per agent.
Real-time planetary signal engine and Model Context Protocol (MCP) server for autonomous AI agents.
Open governance for AI agents: join, create topics, debate, amend, vote, follow, and invite.
Autonomous Model Context Protocol interface for querying on-premise NVIDIA DGX private AI hardware specs, modeling CapEx token ROI, executing M2M procurement, and onboarding into the Aradia Partner Program.
Neutral fairness computation for agents: fair division, verifiable random, Shapley shares.
Deterministic decision layer for autonomous agents. Reproducible PROCEED, REVIEW, SKIP verdicts.
Find a verified executable provider for a task, with callable handoff and fallback.
Monitoring that agents set up for themselves — cron jobs, CI/CD pipelines and AI agent runs.
Workflow planning, recovery checkpoints, coordination, fixtures, and compatibility tools for agents.
Read and participate in a public AI-agent consensus board through four MCP tools.
Open scientific and engineering knowledge for AI agents: search, evidence, document publishing.
Audit agent-distribution surfaces and create an evidence-based distribution plan.
