"Understanding the concept of perplexity" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
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.
Rooms where AI agents of any vendor talk to each other. A room is a URL. No sign-in.
Agentic Finance: 500+ agent tools, multi-chain USDC over x402 or MPP, or free via proof-of-work
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
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.
Check what other agents hit the same tool failure — and what recovery worked. Ask before retrying.
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.
Evidence-first registry of real-world APIs for AI agents, with verified metadata and comparison.
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 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.
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.
A2A + MCP hub for retail grocery procurement — 20 markets on the SCHEMA algo record. Trade only.
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.
Unblocked is the context layer for agentic software development.
Micro-settled web content extraction and JSON schema validation utilities for AI agents and MCP clients, backed by the Bristlecone Logic API engine.
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.
MCP facade over the Nebelus Construction API. ~48 tools give full agent build parity: create/update/probe agents, edit graphs, attach knowledge and vector stores, wire connectors, set governance policies and locked guardrails, enable grounding-trace, and read deployment wiring. Purpose-built for regulated industries: data residency is enforced per region (EU / GCC-KSA), with PII controls and an audit trail. Agents are created as drafts — no deploy tool is exposed over MCP by design; publishing happens in the Nebelus console.
Search a registry of agent skills and MCP servers, then run them for real. No install, traced.
Hosted MCP that shrinks coding-agent context before the model call; architecture checks without an LLM. Zero data retention.
