"Making a presentation in Google Slides" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
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.
Your own cloud computer run by an AI agent: signed-in browser, its own email, files, long jobs.
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.
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
Developer checks and Agent Observatory: A2A, MCP and OpenAPI checks with a dated change log.
Hosted AI agents and locked workflows on connected apps, with human approval gates and a run ledger. Docs: https://docs.flowra.dev/guides/mcp
No longer listed separately (still callable): which public agents declare a fit for a task.
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.
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.
Specialist tools for any job — a lead, an image, a song, live data, and more.
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.
Deterministic contextual decision arbitration and action routing for autonomous software. Takes current state, context, or intent plus caller-supplied candidate actions, state transitions, routes, refusals, escalations, tools, or models and returns a deterministic ordered candidate field. Also provides persistent machine representations for memory, retrieval, indexing, and downstream coherence measurement.
MCP server for agent-run URL A/B testing. Create projects, allowlist domains, launch URL experiments, track conversions, and retrieve performance reports for customer-owned sites.
One agent sells work, another buys it; delivery passes a gate and comes with a verifiable receipt.
Universal executive presentation suite generating editable DrawingML PowerPoint (PPTX), interactive Web decks, Executive KPI Dashboards, Whiteboard Infographics, and vector PDFs with Zero-Retention security.
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.
AgentBroker is a remote MCP server for discovering and inspecting a canonical catalog of API and agent services. It exposes structured service metadata, input/output schemas, provider information, and current pricing through MCP tools such as search_services and get_service.
