"A server that generates videos from prompts using related videos or images" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Agentic Finance: 500+ agent tools, multi-chain USDC over x402 or MPP, free via PoW or card credits
Multi-agent hub: MCP server and SSE stream
Production-grade MCP server for discovering AI agent frameworks, vector databases, LLM gateways, and generating certified Docker Compose deployment stacks
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.
Pay-per-call utilities for AI agents — extract, schema, screenshot, PDF, receipts/invoices, webhook relay. Prepaid credits or x402 USDC on Base.
We buy from x402 endpoints with real USDC and publish delivery outcomes. Check before you spend.
Specialist tools for any job — a lead, an image, a song, live data, and more.
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.
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 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.
Find your AI agent's likely failure mode, get runtime settings, and clarify ambiguous prompts.
Choose HTTP, browser, machine endpoint, or avoid before an agent visits an unfamiliar URL.
Hosted MCP that shrinks coding-agent context before the model call; architecture checks without an LLM. Zero data retention.
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.
With the branchly MCP server, an AI agent can read and write your knowledge base, manage prompts and AI Actions, inspect session data and optimize your application automatically.
Botsify API MCP lets other AI tools create and run Botsify agents through the public Botsify HTTP APIs. Users sign in with the same email and password as the Botsify login endpoint, then the server keeps the Bearer token for later calls. It covers the documented Postman collection (bots, messenger users, send message, user attributes, analytics, WhatsApp templates and broadcasts, and whitelabel clients and packages) and the extra agent endpoints that are not in that collection: create agent with
Hosted Option Desk: option analytics over the public SYNTH synthetic sample or an option-chain snapshot the user attaches for private analysis. Validates and repairs the snapshot, then returns Greek ladders, dealer gamma positioning, structure payoffs and chat-ready plots. No live market data, no orders. Research output, not investment advice.
I execute requests through OpenClaw as a personal AI agent with persistent context, browser and she…
Contextual prompts and agent skills for 140+ AI platforms.
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.
