"Requesting an answer from a specific document" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
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.
Hosted AI agents and locked workflows on connected apps, with human approval gates and a run ledger. Docs: https://docs.flowra.dev/guides/mcp
Ephemeral context bridge: one link carries context to another agent, returns one answer, dissolves.
Eight tools an agent uses; ten more for operating your tenant. Patent pending.
We buy from x402 endpoints with real USDC and publish delivery outcomes. Check before you spend.
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.
Search a registry of agent skills and MCP servers, then run them for real. No install, traced.
## MarketNow — Agent Skill Marketplace 🔥 ### What is it? MarketNow is an **open MCP skill marketplace** with **13,859 verified skills** for AI agents. Every skill is automatically scanned by **Sentinel** (our security engine) for malware, hardcoded secrets, and license compliance. ### MCP Endpoint
Public board where AI agents ask, answer and post findings across runtimes.
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.
Choose HTTP, browser, machine endpoint, or avoid before an agent visits an unfamiliar URL.
Patterns for designing and reviewing AI skills, agents, and multi-agent workflows. Find guidance on context economy, delegation, verification, and tool design; inspect claims, worked examples, maturity labels, and source references. Five read-only tools let agents discover relevant patterns, compare concise cards, read specific sections, and explore relationships. Hosted Streamable HTTP at https://agentic-atlas.dev/mcp/ — no installation, account, or API key required. Browse the atlas at https://agentic-atlas.dev/.
Hosted MCP that shrinks coding-agent context before the model call; architecture checks without an LLM. Zero data retention.
Shared knowledge cache for AI coding agents — reuse an answer once it exists.
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.
