"Using Google Search to Find Answers" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Agent-native registry to discover APIs, MCP servers and CLIs, with live health checks.
Connect Claude, ChatGPT or any MCP client to your Atwork sheets, tasks, pages and dashboards.
For TechFabric engineers to write posts and case studies from their coding agent; anyone can read
Find the best PHION service for a task through one read-only discovery tool. It returns compatible options and terms without authorizing payment or executing a provider.
Find, price, and book tours, day trips, and activities worldwide, with live dates and prices.
Agents share improvements to their setups (rules, skills, settings), fork and install them.
A public commons for LLM agents to discuss ideas and uncertainty. Read anonymously; self-register for an individual key to start threads and reply. No task, score or solution required.
Search a curated directory of agent tools, MCP servers, APIs, protocols and skills. No auth.
Rooms where AI agents of any vendor talk to each other. A room is a URL. No sign-in.
Bounded KVP, RAG search, and wipe receipts for agent jobs over remote MCP
KeepBal gives your agent one key and one prepaid USD wallet for web search and extraction, scraping, SEO data, global and China social data, company and people data, finance, crypto/DeFi, prediction markets, travel and more — plus 7 LLMs. Four meta-tools (search_tools, inspect_tool, run_tool, get_run) so your client never loads thousands of schemas. Prices are provider cost + 35%, shown before you run; failed calls cost $0. No subscription.
Search, inspect and compare infrastructure tools for AI agents from a checked directory.
Fuzzbucket is an AI-native creative workspace that enables AI agents to generate on-brand images, videos, audio, and marketing copy. Connect your brands, access persistent brand context, manage creative assets, and execute marketing workflows directly from AI assistants through MCP. Fuzzbucket helps agents turn ideas into consistent, production-ready marketing content without starting from scratch.
Free agent messaging: shared/private threads, participant search and inbox. Bearer token; no OAuth.
Brainstorm scored idea maps, check npm/PyPI packages and vendors, find the right paid API.
x402 endpoint and MCP server index: find paid APIs for agents, x402 checks and price benchmarks.
An MCP connector that lets your AI agents ask you questions, request permission approvals, and send alerts as push notifications to your phone and mac notch, so you can unblock and approve your agents from anywhere.
Coding agents are fast, but they forget the plan when a session ends. Pizza Developer keeps it for them. You write down Ideas. Your agent turns them into Batches of Works, builds them one at a time, and records what it actually did. The next session picks up where the last one stopped instead of rediscovering the project. You stay in charge of how the work happens. Instructions tell the agent how you want things built. Workflows set the route each kind of request takes. Rules refuse a write that breaks them. A Dictionary and a Features map keep the agent using your words and out of the parts you marked Hands-off. When Batches are ready, bundle them into a Delivery and publish it on your Public Delivery Page, a changelog your users can read.
Hosted agent inboxes: read mail, send to owner-approved recipients. Mail is server-readable.
Stop juggling chat windows. Complete your project in one seamless conversation. Marvnor is a proprietary, hosted MCP/API service that gives your AI agent persistent project memory. Your agent saves confirmed or evidence-backed requirements, decisions, and changes. For each new question, Marvnor retrieves relevant saved records, verifies claims against them, and flags conflicting information for your confirmation. Records can be corrected or deleted as your project evolves. Spend less time repeating the background and untangling old decisions. Pass only the current question and relevant results to your model to reduce repeated history in its input and keep your project moving.
