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InteractiveAI - Documentation
For agents: InteractiveAI docs for building and operating AI agents with conversations, tools, knowledge bases, an LLM router API, CLI and SDK.
ai agentsagent platformllm routersdkcliknowledge base
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- llms.txt
- https://docs.interactive.ai/llms.txt
- llms-full.txt
- https://docs.interactive.ai/llms-full.txt
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- Interface: a documented API or declared MCP endpoint an agent can call
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# InteractiveAI - Documentation
## Agents
- [Interactive Agents](https://docs.interactive.ai/agents/readme.md): Interactive Agents — build, configure, and operate AI agents that hold conversations, run typed automations, call tools, and ground answers in your knowledge base.
- [Architecture](https://docs.interactive.ai/agents/concepts/architecture.md): How an Interactive Agent deployment fits together: the agent server, the InteractiveAI platform, the LLM router, MCP tool servers, storage, and the knowledge base.
- [Conversation lifecycle](https://docs.interactive.ai/agents/concepts/conversation-lifecycle.md): What happens inside the engine on every turn: policy matching, routine advancement, tool execution, the iteration loop, and event emission.
- [Policies](https://docs.interactive.ai/agents/concepts/policies.md): Policies are condition → action rules matched against every turn. They encode safety, compliance, tone, and business rules that apply across all routines.
- [Routines](https://docs.interactive.ai/agents/concepts/routines.md): Routines are graphs of nodes — chat, tool, and routing-only (fork) nodes connected by transitions. This page defines the node types and their runtime completion semantics.
- [Autonomous routines](https://docs.interactive.ai/agents/concepts/autonomous-routines.md): Autonomous routines run end-to-end without a conversation: typed JSON in via trigger endpoint or webhook, typed JSON out via signed callback.
- [Priorities, entailments & prerequisites](https://docs.interactive.ai/agents/concepts/priorities.md): Relationship declarations between routines and policies: priorities resolve conflicts, entailments chain policy activations, and requires keeps entities dormant until a tool has run. Without them, eve
- [Glossaries & macros](https://docs.interactive.ai/agents/concepts/glossaries-and-macros.md): Glossaries inject domain vocabulary into every turn; macros are reusable text blocks interpolated into routine chat nodes via ${macro-id}.
- [Prompts, language & preamble](https://docs.interactive.ai/agents/concepts/prompts.md): The system prompt defines persona and ground rules; the language directive controls reply language; the greeting opens the first turn; the preamble shapes mid-turn filler.
- [Tools](https://docs.interactive.ai/agents/concepts/tools.md): Tools are functions the agent calls — served by your MCP servers, plus three built-ins. Covers namespacing, declaration, auth, reevaluation tools, and tool-event injection.
- [Knowledge base & retrieval](https://docs.interactive.ai/agents/concepts/knowledge-base.md): Retrieval grounding for the agent: managed collections on the platform, or an external HTTP search endpoint you own. Exactly one, selected by type.
- [Models](https://docs.interactive.ai/agents/concepts/models.md): Per-stage model configuration: two lanes — customer-facing and evaluation — each with a default, per-stage overrides, and its own fallback mechanism. The lanes never cross.
- [Sessions, m
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| Domain | Title | Category | Country | Authority | llms.txt | llms-full.txt | Save |
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| ausca.com | Ausca | interface AI agents and MCP APIs and SDKs | — | 65 | ✓ | ✓ | |
| nitrosend.com | Nitrosend | interface Marketing Communications +1 | — | 65 | ✓ | ✓ | |
| runx.ai | runx | interface AI agents and MCP Open source projects | — | 65 | ✓ | ✓ | |
| 0state.com | 0state | documentation Open source projects AI agents and MCP +1 | — | 61 | ✓ | ||
| gofrantic.com | Frantic | interface AI and machine learning AI agents and MCP | — | 61 | ✓ | ||
| agentwebmap.com | Agent Web Map | interface AI and machine learning AI agents and MCP +1 | FR | 60 | ✓ | ✓ | |
| quineai.org | QuineAI | interface AI agents and MCP | US | 56 | ✓ |
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