--- title: "agent-protocol vs letta" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/agi-inc-agent-protocol-vs-letta-ai-letta" tools: ["agi-inc-agent-protocol", "letta-ai-letta"] --- # agent-protocol vs letta *GraphCanon updated Aug 17, 2026* ## Verdict Pick agent-protocol if agent-protocol provides a standardized interface for interacting with various AI agents regardless of their underlying tech stack, aiming to ease development, deployment, and benchmarking; pick letta if letta is a Python-based platform designed to foster the development of stateful AI agents with capabilities for advanced memory techniques that support continuous learning and self-improvement. The Apache-2.0 license it鳧. [agent-protocol](https://agentprotocol.ai) reports 1.5k GitHub stars, 185 forks, and 50 open issues, last pushed Apr 8, 2025. [letta](https://docs.letta.com/) has 24k stars, 2.6k forks, and 41 open issues, last pushed Aug 16, 2026. Figures are from public GitHub metadata via [agent-protocol's repository](https://github.com/agi-inc/agent-protocol) and [letta's repository](https://github.com/letta-ai/letta). | | [agent-protocol](/tools/agi-inc-agent-protocol.md) | [letta](/tools/letta-ai-letta.md) | | --- | --- | --- | | Tagline | Common interface for AI agents | Platform for stateful agents: AI with advanced memory that can learn and self-improve over time. | | Stars | 1,458 | 24,274 | | Forks | 185 | 2,582 | | Open issues | 50 | 41 | | Language | Python | - | | Adopt for | agent-protocol provides a standardized interface for interacting with various AI agents regardless of their underlying tech stack, aiming to ease development, deployment, and benchmarking. | letta is a Python-based platform designed to foster the development of stateful AI agents with capabilities for advanced memory techniques that support continuous learning and self-improvement. The Apache-2.0 license it鳧 | | Persona | - | - | | Runtime | - | - | | License | MIT | letta operates under the Apache-2.0 license. | | Categories | AI Agents | AI Agents | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agent-protocol](/tools/agi-inc-agent-protocol.md) | [letta](/tools/letta-ai-letta.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 484d | 0d | | Open issues (now) | 50 | 41 | | Stars delta | Unknown | +443 (30d) | | Open issues delta | Unknown | -8 (30d) | | Full report | [trust report](/tools/agi-inc-agent-protocol/trust.md) | [trust report](/tools/letta-ai-letta/trust.md) | ## Decision facts: agent-protocol - **Adopt for:** agent-protocol provides a standardized interface for interacting with various AI agents regardless of their underlying tech stack, aiming to ease development, deployment, and benchmarking. ## Decision facts: letta - **Adopt for:** letta is a Python-based platform designed to foster the development of stateful AI agents with capabilities for advanced memory techniques that support continuous learning and self-improvement. The Apache-2.0 license it鳧 - **License detail:** letta operates under the Apache-2.0 license. ## Choose when ### Choose agent-protocol if… - License: agent-protocol is MIT, letta is Apache-2.0. - Tags unique to agent-protocol: agents, ai-agent, api, auto-gpt. - When you want to ensure interoperability between different AI agents irrespective of the frameworks used by them. ### Choose letta if… - License: letta is Apache-2.0, agent-protocol is MIT. - Tags unique to letta: advanced memory, agents development framework, self-improving ai, stateful ai. - When you require an AI agent with robust memory features that enable continuous learning and adaptation over time. ## When NOT to use agent-protocol - If you are developing an isolated system with no intention to communicate or integrate with other AI agents outside this scope. - When working in environments where specific, proprietary interfaces provide significantly better performance or features than adhering to a generic protocol could offer. ## When NOT to use letta - If you are looking for a simple stateless AI solution without advanced memory capabilities, as letta is geared towards more complex stateful agent development. - When your project's requirements involve strict limitations around data retention and privacy where even anonymized interaction logs might be considered sensitive. ## Common questions ### What is the difference between agent-protocol and letta? agent-protocol: Common interface for AI agents. letta: Platform for stateful agents: AI with advanced memory that can learn and self-improve over time.. See the comparison table for live GitHub stats and shared categories. ### When should I choose agent-protocol over letta? Choose agent-protocol over letta when License: agent-protocol is MIT, letta is Apache-2.0; Tags unique to agent-protocol: agents, ai-agent, api, auto-gpt; When you want to ensure interoperability between different AI agents irrespective of the frameworks used by them. ### When should I choose letta over agent-protocol? Choose letta over agent-protocol when License: letta is Apache-2.0, agent-protocol is MIT; Tags unique to letta: advanced memory, agents development framework, self-improving ai, stateful ai; When you require an AI agent with robust memory features that enable continuous learning and adaptation over time. ### When should I avoid agent-protocol? If you are developing an isolated system with no intention to communicate or integrate with other AI agents outside this scope. When working in environments where specific, proprietary interfaces provide significantly better performance or features than adhering to a generic protocol could offer. ### When should I avoid letta? If you are looking for a simple stateless AI solution without advanced memory capabilities, as letta is geared towards more complex stateful agent development. When your project's requirements involve strict limitations around data retention and privacy where even anonymized interaction logs might be considered sensitive. ### Is agent-protocol or letta more popular on GitHub? letta has more GitHub stars (24,274 vs 1,458). Stars measure visibility, not whether either tool fits your constraints. ### Are agent-protocol and letta open source? Yes - both are open-source projects on GitHub (agent-protocol: MIT, letta: Apache-2.0). ### Where can I find alternatives to agent-protocol or letta? GraphCanon lists graph-backed alternatives at [agent-protocol alternatives](/tools/agi-inc-agent-protocol/alternatives) and [letta alternatives](/tools/letta-ai-letta/alternatives) ([agent-protocol markdown twin](/tools/agi-inc-agent-protocol/alternatives.md), [letta markdown twin](/tools/letta-ai-letta/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/agi-inc-agent-protocol-vs-letta-ai-letta.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agent-protocol or letta? agent-protocol: Dormant. letta: 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 agent-protocol and letta? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agent-protocol trust report](/tools/agi-inc-agent-protocol/trust); [letta trust report](/tools/letta-ai-letta/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=agi-inc-agent-protocol`](/api/graphcanon/graph?tool=agi-inc-agent-protocol) - 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/_