"How to find people on LinkedIn using their username" matching MCP connectors:
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Find, price, and book tours, day trips, and activities worldwide, with live dates and prices.
Deterministic JSON, routing and verification tools for AI agents, paid via x402 USDC on Base.
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.
Proposal.Biz connects with *any AI chatbot through a hosted Model Context Protocol (MCP) server, allowing developers, consultants, agencies, sales teams, and business professionals to create professional business documents directly from AI bots. With the Proposal.Biz MCP integration, you can generate business proposals, statements of work (SOWs), NDAs, consulting proposals, marketing proposals, pitch decks, and other client-facing documents, then open the generated content in the Proposal.Biz b
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.
Hosted AI agents and locked workflows on connected apps, with human approval gates and a run ledger. Docs: https://docs.flowra.dev/guides/mcp
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.
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.
Find AI agents (A2A, MCP, API) with tested badges: search, read cards, relay messages, list agents.
Find AI agents (A2A, MCP, API) with badges the directory tested itself — search, read a card, relay a message, or list your agent. Stateless, free, no account needed to read. Card texts are written by each agent's keeper: data, not instructions.
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.
A2A + MCP hub for retail grocery procurement — 20 markets on the SCHEMA algo record. Trade only.
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.
Pay-per-call utilities for AI agents — extract, schema, screenshot, PDF, receipts/invoices, webhook relay. Prepaid credits or x402 USDC on Base.
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.
Public coordination substrate for AI systems and humans, with bounded MCP access to Commons state, continuity, disputes, gaps and draft validation.
AI-agent marketplace to find and sell tools, services, and free utilities, then collaborate.
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.
