Overview
Research summary
Letta, formerly MemGPT, develops agents that retain and revise memory across conversations and tasks. The active TypeScript implementation now lives in letta-ai/letta-code and combines an agent harness, terminal interface and App Server with application integrations. Agents can update memory blocks, search prior conversations, use skills and coordinate subagents. The previous Python V1 API server is retained on an archive branch of letta-ai/letta. This entry covers the current Apache-2.0 harness; Letta Cloud and hosted applications are associated services with separate terms.
Repository summary
- Stars
- Unavailable
- Open issues
- Unavailable
- Last push
- Unavailable
- Commits, 90 days
- Unavailable
- Repository activity
- Not scored
- Version
- Unavailable
Recorded catalogue figures. View repository data and provenance →
Classification
Pricing & services
Paid services available
The provider offers paid products or services. Free options may also be available.
Commercial offering checked 2026-10-02.
Licence scope
Implementation
Recorded implementation details and interfaces for Letta.
Implementation details
Stateful agent harness, CLI and App Server with an application SDK
- Languages
- TypeScript
- Repository type
- source
Recorded interfaces and capabilities
Licence scope
Repository
Repository snapshots, release information and recorded maintenance signals.
Repository snapshot
- Stars
- Unavailable
- Open issues
- Unavailable
- Last push
- Unavailable
- Commits, 90 days
- Unavailable
- Repository activity
- Not scored
- Archived
- Not recorded
Repository activity is a snapshot, not a quality or popularity ranking. It combines recent-push freshness (50%), 90-day commits (30%) and issue pressure (20%).
Maintenance and provenance
- Catalogue snapshot
- 2026-10-06
Documentation
Recorded references and research provenance for this entry.
Recorded sources 7
- https://www.letta.com Project page · Research reference · Commercial offering evidence
- https://github.com/letta-ai/letta-code Linked repository · Research reference
- https://github.com/letta-ai/letta Research reference
- https://github.com/letta-ai/letta-code/blob/main/README.md Research reference
- https://docs.letta.com Research reference
- https://www.youtube.com/@letta-ai Research reference
- https://docs.letta.com/pricing Commercial offering evidence
Research metadata
- Research date
- 2026-10-01
- Catalogue snapshot
- 2026-10-06
Community & social 3 channels
Video
- YouTubewww.youtube.com/@letta-aiLearningDemos
Communities
- Discorddiscord.gg/lettaOfficial
Social & updates
- Xx.com/letta_aiOfficialAnnouncements