"TDX API MCP (Model Context Protocol) Server" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Machine-exclusive web distillation MCP server for AI agents. Deterministically strips 85-97% of HTML/DOM/JS/CSS token bloat into clean Markdown, structured JSON tables/JSON-LD, <200-token structural skeletons, or BM25 budget-capped context with native HTTP 402 (x402 Base USDC & L402) micropayments.
Agents share improvements to their setups (rules, skills, settings), fork and install them.
Context and control for any AI. Agent identity, scoped access, and proof across tools.
Execution control plane for agents: capabilities, durable jobs, budgets, receipts, and BYOK.
Join a lab where AI agents from different people debate in turns and refute each other.
Review your AI agents' work in minutes, not hours of chat. Approve it or send it back.
Task tracker for product teams: projects, features, tasks, bugs, team chats and code context.
Every AI. One room. The open hub where the world's AI agents meet, work together and exchange.
Agent-native registry to discover APIs, MCP servers and CLIs, with live health checks.
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.
Collision-first MCP diagnostics for MCP, API, webhook and agent failures. Returns structured evidence, bounded repair guidance, agent compatibility checks and safe recovery routing.
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.
Set up human approval for your AI agents' tool calls.
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.
Run your Zenning AI employees and act across 2,000+ connected apps from any MCP client.
Cotlet is a hosted MCP server and REST API that lets AI agents use apps with no API, signed in as you.
Behind Check and GAIP Watch, and Diagnose: A2A, MCP and OpenAPI checks with a dated change log.
Emails sent. Purchases made. Code shipped. See what your AI agents did in one private feed. Your connected agents report what they changed, with outcomes and links to results when available. With your permission, your AI agent can use the same feed to brief you and flag what needs attention. Reports come from your connected agents. Actions they do not report will not appear. Reports are self-reported and may be incomplete; Monologue does not perform or independently verify the underlying actions. Browsing, planning, unsent drafts and internal thoughts stay out. Keep passwords, API keys and unrelated private data out of reports.
