--- title: "parlant vs agentos" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/emcie-co-parlant-vs-framerslab-agentos" tools: ["emcie-co-parlant", "framerslab-agentos"] --- # parlant vs agentos *GraphCanon updated Aug 20, 2026* ## Verdict Pick parlant if parlant is a specialized interaction control harness designed to ensure that AI agents, particularly those in customer service roles, behave predictably and align with predefined rules; pick agentos if agentOS supports eleven LLM providers with runtime tool forging capabilities for cognitive memory in TypeScript. [parlant](https://www.parlant.io) reports 18k GitHub stars, 1.6k forks, and 42 open issues, last pushed Jul 12, 2026. [agentos](https://agentos.sh) has 601 stars, 89 forks, and 9 open issues, last pushed Jul 22, 2026. Figures are from public GitHub metadata via [parlant's repository](https://github.com/emcie-co/parlant) and [agentos's repository](https://github.com/framerslab/agentos). | | [parlant](/tools/emcie-co-parlant.md) | [agentos](/tools/framerslab-agentos.md) | | --- | --- | --- | | Tagline | Build reliable customer-facing AI agents with Parlant: an interaction control harness optimized for controlled, consistent, and predictable LLM interactions. | TypeScript AI agent framework providing cognitive memory and runtime tool forging with support for multi-agent orchestration | | Stars | 18,253 | 601 | | Forks | 1,551 | 89 | | Open issues | 42 | 9 | | Language | Python | TypeScript | | Adopt for | Parlant is a specialized interaction control harness designed to ensure that AI agents, particularly those in customer service roles, behave predictably and align with predefined rules. | AgentOS supports eleven LLM providers with runtime tool forging capabilities for cognitive memory in TypeScript. | | Persona | - | - | | Runtime | - | - | | License | Parlant is available under the Apache-2.0 license, allowing for unrestricted commercial use as long as proper attribution is given. | Apache-2.0 | | Categories | AI Agents | AI Agents | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [parlant](/tools/emcie-co-parlant.md) | [agentos](/tools/framerslab-agentos.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Very active (96%) | | Days since push | 38d | 1d | | Open issues (now) | 42 | 9 | | Stars delta | +74 (30d) | Unknown | | Open issues delta | +3 (30d) | Unknown | | Full report | [trust report](/tools/emcie-co-parlant/trust.md) | [trust report](/tools/framerslab-agentos/trust.md) | ## Decision facts: parlant - **Pricing:** freemium - The open-source version offers community-supported functionalities which are free to use but might lack advanced support services. - **Adopt for:** Parlant is a specialized interaction control harness designed to ensure that AI agents, particularly those in customer service roles, behave predictably and align with predefined rules. - **License detail:** Parlant is available under the Apache-2.0 license, allowing for unrestricted commercial use as long as proper attribution is given. ## Decision facts: agentos - **Adopt for:** AgentOS supports eleven LLM providers with runtime tool forging capabilities for cognitive memory in TypeScript. ## Choose when ### Choose parlant if… - parlant is primarily Python; agentos is TypeScript. - Pricing: The open-source version offers community-supported functionalities which are free to use but might lack advanced support services.. - Tags unique to parlant: ai-agents, ai-alignment, customer-service, customer-success. - When you need precise control over the actions of AI agents based on specific conditions or observations. ### Choose agentos if… - agentos is primarily TypeScript; parlant is Python. - Tags unique to agentos: agent-framework, cognitive-memory, llm-orchestration, multi-agent. - Need for cognitive memory and real-time tool generation in AI agents ## When NOT to use parlant - When the requirements for agent interactions do not demand granular rules based on observable user behavior or conditions, making this level of control unnecessary. - In cases where the flexibility and spontaneous responses from general-purpose LLMs are preferred without being restricted by controlled guidelines. - If your project involves minimal interaction types that can be managed with less sophisticated frameworks, thus negating the need for Parlant's advanced condition setting capabilities. ## When NOT to use agentos - Preferring frameworks without multi-agent orchestration support - Prioritizing environments with less than eleven LLM provider options ## Common questions ### What is the difference between parlant and agentos? parlant: Build reliable customer-facing AI agents with Parlant: an interaction control harness optimized for controlled, consistent, and predictable LLM interactions.. agentos: TypeScript AI agent framework providing cognitive memory and runtime tool forging with support for multi-agent orchestration. See the comparison table for live GitHub stats and shared categories. ### When should I choose parlant over agentos? Choose parlant over agentos when parlant is primarily Python; agentos is TypeScript; Pricing: The open-source version offers community-supported functionalities which are free to use but might lack advanced support services.; Tags unique to parlant: ai-agents, ai-alignment, customer-service, customer-success; When you need precise control over the actions of AI agents based on specific conditions or observations. ### When should I choose agentos over parlant? Choose agentos over parlant when agentos is primarily TypeScript; parlant is Python; Tags unique to agentos: agent-framework, cognitive-memory, llm-orchestration, multi-agent; Need for cognitive memory and real-time tool generation in AI agents. ### When should I avoid parlant? When the requirements for agent interactions do not demand granular rules based on observable user behavior or conditions, making this level of control unnecessary. In cases where the flexibility and spontaneous responses from general-purpose LLMs are preferred without being restricted by controlled guidelines. If your project involves minimal interaction types that can be managed with less sophisticated frameworks, thus negating the need for Parlant's advanced condition setting capabilities. ### When should I avoid agentos? Preferring frameworks without multi-agent orchestration support Prioritizing environments with less than eleven LLM provider options ### Is parlant or agentos more popular on GitHub? parlant has more GitHub stars (18,253 vs 601). Stars measure visibility, not whether either tool fits your constraints. ### Are parlant and agentos open source? Yes - both are open-source projects on GitHub (parlant: Apache-2.0, agentos: Apache-2.0). ### Where can I find alternatives to parlant or agentos? GraphCanon lists graph-backed alternatives at [parlant alternatives](/tools/emcie-co-parlant/alternatives) and [agentos alternatives](/tools/framerslab-agentos/alternatives) ([parlant markdown twin](/tools/emcie-co-parlant/alternatives.md), [agentos markdown twin](/tools/framerslab-agentos/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/emcie-co-parlant-vs-framerslab-agentos.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, parlant or agentos? parlant: Steady. agentos: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for parlant and agentos? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [parlant trust report](/tools/emcie-co-parlant/trust); [agentos trust report](/tools/framerslab-agentos/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=emcie-co-parlant`](/api/graphcanon/graph?tool=emcie-co-parlant) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_