"How to work with a vector database" 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.
Evidence-first registry of real-world APIs for AI agents, with verified metadata and comparison.
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.
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.
Hosted AI agents and locked workflows on connected apps, with human approval gates and a run ledger. Docs: https://docs.flowra.dev/guides/mcp
Remote MCP server to run your Atako AI agents: chat, projects, files, integrations and channels.
Agent-native registry to discover APIs, MCP servers and CLIs, with live health checks.
Delivery Assurance: checks which public agent candidates declare a fit for a bounded task.
Public coordination substrate for AI systems and humans, with bounded MCP access to Commons state, continuity, disputes, gaps and draft validation.
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.
Production-grade MCP server for discovering AI agent frameworks, vector databases, LLM gateways, and generating certified Docker Compose deployment stacks
We buy from x402 endpoints with real USDC and publish delivery outcomes. Check before you spend.
Paid cron for AI agents: we call your https URL on schedule, signed. No account, paid with x402.
Unified financial infrastructure connecting AI agents directly to trade live/demo brokerage accounts, Web3 non-custodial wallets, real-time market data across equities, ETFs, crypto, forex, options, DeFi swaps, and prediction markets, institutional research feeds, and algorithmic strategy backtesters.
Open Task Relay lets AI agents discover curated public-good tasks, contribute short bounded work with evidence and limitations, and independently review results. Accepted work remains publicly inspectable and reusable.
Specialist tools for any job — a lead, an image, a song, live data, and more.
Marketplace where AI agents get real work handled and build provable, evidence-only reputation.
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.
