"How to integrate with Google Meet video conferencing app" matching MCP connectors:
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Discovery registry for AI agents: 660+ APIs, MCP servers and CLIs, each health-checked every 6 hours with real requests — full initialize + tools/list handshakes for MCP, real calls for APIs — plus response-schema validation that catches responses which parse fine but are missing a required field.
Ephemeral context bridge: one link carries context to another agent, returns one answer; host-readable while live, anyone with the link, not for secrets, dissolves on TTL.
The team's shared memory that reaches an AI before it starts work. Arroway holds what a team, or one person working across sessions and tools, has decided: rules, decisions, preferences and unfinished work. Any AI connected to it reads that before it acts and records what it did when it finishes. Each memory carries who decided it and the condition that retires it; the AI proposes what to record and a person approves it.
Collide is an MCP layer that keeps concurrent AI agents from stepping on each other in a shared codebase. It tracks code at the symbol level with a Merkle tree, so agents declare intent before writing, get warned about collisions, and pick up context on what changed and why. It also carries anchored team memory, merge simulation, and an audit ledger.
Evidence-first registry of real-world APIs for AI agents, with verified metadata and comparison.
Hosted AI agents and locked workflows on connected apps, with human approval gates and a run ledger. Docs: https://docs.flowra.dev/guides/mcp
A second opinion before your agent acts on one model's unearned confidence. One question goes to 3-4 different AI models that answer independently, then a chair returns a single verdict with a confidence score, the consensus and the dissent that held. A grounded tier buys evidence first (honeypot simulation, OFAC sanctions screen, page content, SEC profile, web results) and itemises what it spent. Pay-per-call with x402 in USDC on Base: no account, no API key, one free call a day.
Agent-native registry to discover APIs, MCP servers and CLIs, with live health checks.
Remote MCP server to run your Atako AI agents: chat, projects, files, integrations and channels.
Activepieces is an open-source automation platform that lets you connect apps, build agents and automate workflows with natural language
Public coordination substrate for AI systems and humans, with bounded MCP access to Commons state, continuity, disputes, gaps and draft validation.
Zero-Ops deploy of a private AI coding workspace onto your own VPS — straight from your AI chat. Provide only your Ubuntu server credentials and Fractera automatically configures everything (Nginx, HTTPS, auth, database, services) in about 10 minutes: 5 AI coding engines, an autonomous Hermes orchestrator, and private graph memory (LightRAG). No terminal, no DevOps. IP-first and free; a custom domain with HTTPS is an optional later step.
We buy from x402 endpoints with real USDC and publish delivery outcomes. Check before you spend.
Agent website testing: browser QA, visual regression, Markdown extraction, and security checks.
Paid cron for AI agents: we call your https URL on schedule, signed. No account, paid with x402.
Unified financial infrastructure connecting AI agents directly to trade live/demo brokerage accounts, Web3 non-custodial wallets, real-time market data across equities, ETFs, crypto, forex, options, DeFi swaps, and prediction markets, institutional research feeds, and algorithmic strategy backtesters.
Specialist tools for any job — a lead, an image, a song, live data, and more.
Open Task Relay lets AI agents discover curated public-good tasks, contribute short bounded work with evidence and limitations, and independently review results. Accepted work remains publicly inspectable and reusable.
mumo is a remote MCP server for multi-model deliberation. Your agent sends a question to models from different labs — Claude, GPT, Gemini, Grok, DeepSeek, Kimi, and more — and gets back their full responses plus typed cross-model reactions. The participating models react to each other directly and explain, in their own words, what they agree with, challenge, or want to explore further. Agents can run a deliberation with `create_deliberation`, wait for results with `wait_for_round`, and steer follow-up rounds with `append_round` using structured signals like KEEP, EXPLORE, CHALLENGE, CORE, and SHIFT. Built for architecture, plan/spec review, strategy, and pre-launch pressure tests. Free tier available. API key required.
Use Aident Loadout MCP to connect your AI agents to 1,000+ real-world apps and tools like Gmail, Slack, Linear, Notion, Firecrawl, and Fal, unlock 27,000+ executable actions, and track full audit history so your agents can get real work done reliably.